Gender
Dimensions
of Disaster Risk
and Resilience
Existing Evidence
Authors
Alvina Erman
Sophie Anne De Vries Robbé
Stephan Fabian Thies
Kayenat Kabir
Mirai Maruo
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Cover design by Brad Amburn.
Gender
Dimensions
of Disaster Risk
and Resilience
Existing Evidence
Authors
Alvina Erman
Sophie Anne De Vries Robbé
Stephan Fabian Thies
Kayenat Kabir
Mirai Maruo
Contents
Acronyms ......................................................................... 5
Acknowledgements ............................................6
Summary ........................................................................... 7
S.1 • Disaster impacts:
exposure and vulnerability .........................................9
S.2 • Resilience: preparedness and coping
capacity ...............................................................................10
S.3 • Data gaps in disaster
risk management ............................................................10
S.4 • Key messages for policy making ..............11
S.5 • Next steps ..............................................................11
Introduction .................................................................12
I.1 • Background .............................................................12
I.2 • A conceptual framework .................................14
I.3 • Challenges and limitations .............................15
I.4 • Dening hazards and disasters ...................16
I.5 • The impact of COVID-19 ..................................17
Disaster impacts: exposure
and vulnerability ....................................................19
1.1 • Health ........................................................................19
1.1.1 • Life expectancy and mortality ....................19
1.1.2 • Mental health....................................................21
1.1.3 • Early childhood development .....................21
1.1.4 • Women’s health ................................................22
1.2 • Education and child labor...............................24
1.3 • Economic outcomes .........................................25
1.3.1 • Livelihoods ........................................................25
1.3.2 • Assets .................................................................26
1.3.3 • Consumption ....................................................28
1.4 • Voice and agency ...............................................29
1.4.1 • Child marriage ..................................................29
1.4.2 • Gender-based violence .................................31
Resilience: preparedness and
coping capacity .......................................................38
2.1 • Disaster preparedness: risk perception,
preparedness actions and early warnings .......38
2.1.1 • Evacuation behavior.......................................40
2.1.2 • Early warning ....................................................40
2.2 • Coping capacity: access to nance,
livelihood, migration, and social protection ....41
2.2.1 • Access to nance,
savings, and assets......................................................41
2.2.2 • Assets .................................................................44
2.2.3 • Livelihoods ........................................................44
2.2.4 • Migration ............................................................45
Data gaps in disaster risk
management ...............................................................49
3.1 • Postdisaster data collection.........................49
3.2 • Limitations of
postdisaster data collection ....................................50
Policy recommendations ...........................52
1. Accessible safety measures and training .......52
2. Social protection ......................................................52
3. Female representation and participation ........54
4. Building back better ................................................54
5. Community involvement .......................................54
6. Knowledge and data ...............................................54
7. Local gender gap assessments ..........................54
Next steps ......................................................................58
References ....................................................................60
4 • Gender Dimensions of Disaster Risk and Resilience
Acronyms
ASP adaptive social protection
FAO Food and Agriculture Organization
GFDRR Global Facility for Disaster Reduction and Recovery
ILO International Labour Organization
PDNA postdisaster needs assessment
PSNP Productive Safety Net Program
PTSD post-traumatic stress disorder
SADD sex and age-disaggregated data
UN United Nations
UNDP United Nations Development Program
UNDRR United Nations Oce for Disaster Risk Reduction (formerly UNISDR)
UNISDR United Nations for Disaster Risk Reduction (now UNDRR)
WHO World Health Organization
Acronyms • 5
Acknowledgements
The report was written by Alvina Erman, Sophie Anne De Vries Robbé, Stephan Fabian Thies, Kayenat
Kabir, and Mirai Maruo.
The report has benetted from valuable input from Stephane Hallegatte, Kathleen Beegle, Maitreyi
Das, Christian Bodewig, Victoria Stanley, and Anne T. Kuriakose. Editorial services were provided
by Lucy Southwood and graphic design support was provided by Brad Amburn. Erika Vargas, Yoko
Kobayashi, Aarthi Sivaraman, Simona Palummo and Sandra Karolina Jensson provided valuable
communications and knowledge management support.
The team acknowledges the valuable guidance received during the conceptualization of this research
from Cristina Otano, Cindy Patricia Quijada Robles, Brian Walsh, Margaret Arnold, Michael B.
O’Sullivan, Jennifer Solotaroff, Elizaveta Perova, Emcet Oktay Tas, Javier Baez, Emmanuel Skouas.
The team would also like to thank Jessica Gardner from Stats2Info and Mendy Marsh from VOICE.
This report could not have been developed without the nancial support of the GFDRR Single-Donor
Trust Fund for Mainstreaming Disaster Risk Management in Developing Countries, which is nanced
by USAID, as well as GFDRR Multi-Donor Trust Fund.
Finally, a special thanks goes to Julie Dana, GFDRR Practice Manager at the initiation of this work,
for her vision and leadership, and Maitreyi Bordia Das and Niels Holm-Nielsen, who, under dicult
circumstances, supported this work as interim Practice Managers of GFDRR.
6 • Gender Dimensions of Disaster Risk and Resilience
Summary • 7
Summary
Men and women, boys and girls have different experiences of disasters. Gender dynamics
impact both the way they are affected by disasters and their capacity to withstand and recover
from them. Gender inequalities can result in gender-differentiated disaster impact, and
differentiated impacts can inuence gender dynamics, which in turn affect future resilience
to shocks.
Disaster risk management policies are designed to maximize results, taking local conditions—
including gender dynamics—as xed. When women and men are affected differently by
disasters, practitioners and policy makers have a responsibility to use the tools available for
mitigating disaster impacts to close gender gaps in outcome. An improved understanding of
the gender dynamics of disaster risk and resilience also allows for better policy and program
design, which benets all stakeholders.
Debunking myths and stereotypes, and uncovering the underlying drivers of gendered
outcomes, are important components of that effort. Recognizing that there are multiple vectors
of vulnerability and exclusion, calling for more contextualized and nuanced analysis is also
vital. This is what this report, Gender Dimensions of Disaster Risk and Resilience—Existing
Evidence, seeks to achieve.
This report reviews existing evidence and data on how men and women, boys and girls are
impacted by, prepare for and cope with disasters. It is not about depicting women and girls as
perpetually worse-off victims of disasters; rather, it is about recognizing that men and women,
boys and girls are affected in different ways. The report objectives are to:
» Identify gender gaps in disaster outcomes and resilience—and the underlying drivers of
those gaps—to create better policies and programs
» Identify the most important knowledge and data gaps, which will guide the next steps
for analytics in this space
» Offer an operationally useful framework that can be used for local assessments of gender
dynamics in disaster risk and resilience.
Conceptual framework
We present a non-linear framework (gure S.1) for considering the role of gender in disaster
risk and resilience. The framework is a simple representation of a complex reality. Disaster
impacts (orange circle) depend on hazard type and intensity, who and what is exposed, levels
of vulnerability and preparedness, and coping capacity. Floods, droughts, earthquakes and
other natural hazards are gender neutral. Gender inequality (purple circle) arises from the
expected roles of men and women in a society, which inuence socioeconomic status, level of
agency, and the way men and women prepare for, react to, are impacted by, and recover from,
disasters. In the overlay (maroon area) between gender inequality and disaster impacts are the
factors that drive disaster impacts and are inuenced by gender dynamics.
8 • Gender Dimensions of Disaster Risk and Resilience
It is in the overlay maroon area where gender-differentiated impacts of disaster are
generated. These, in turn, can exacerbate gender inequality by inuencing the prevailing
socioeconomic conditions that determine gender equality. For example, when, due to a lack
of access to bank accounts, women hold a larger share of their assets in tangible form than
men, they are at greater risk of losing their assets to disasters, which would worsen gender
inequality. Gender-differentiated impacts also inuence resilience to future disasters.
Disaster risk management policies and interventions should operate in the overlay maroon
area. This means good disaster risk management should consider ways in which gender
dynamics inuence disaster impacts in any given area before making decisions on policy or
project design, to be able to mitigate gendered differences in disaster outcomes and maximize
benets for all.
The ndings of this review are organized around this framework (gure S.1). Section 1 focuses
on the gender-differentiated impacts on health, education and child labor, economic outcomes,
voice, and agency that result from gender dynamics in disaster exposure and vulnerability.
Section 2 focuses on gender dynamics in the drivers of preparedness and coping capacity that
comprise our denition of resilience. Section 3 reviews postdisaster data collection and analysis
and identies data gaps. Section 4 uses the framework to identify policy recommendations that
can prevent gender-differentiated disaster impacts and support a more inclusive disaster risk
management agenda, and Section 5 presents next steps.
Figure S.1 • A conceptual framework for considering gender dynamics and disaster impacts
Hazard
Gender inequality
Exposure
Vulnerability
Preparedness
Coping capacity
Impact factors shaped by
gender dynamics:
Disaster risk
management
Society
Disaster impacts
Sources: Adapted from World Bank 2012 and Hallegatte et al. 2017.
Summary • 9
The report is grounded in evidence from the literature. The conclusions are based on
consolidated results from case studies in different contexts and, in the best cases, global reviews
and data sources. The more case studies and data available to assess a particular question,
the more condent the response. But even for the questions where several case studies are
available, the assessment will not be condently representative beyond the context of those
specic case studies, and conclusions drawn do not replace the need for local assessments.
Three obvious facts underscore the guiding principles of this report:
1. Disasters encompass a wide range of hazards.
2. Women are highly diverse group.
3. Gender is not just about women: it is about the relations between males and females.
S.1 • Disaster impacts: exposure and vulnerability
Natural hazards are gender neutral; but the impacts are not. Men and women, boys and
girls face different levels of exposure and vulnerability to natural hazards, driven by gender
relations and discrimination in society. This results in differentiated impacts on endowments
(health, education, assets); economic outcomes (employment, assets, wages, consumption); and
voice and agency (child marriage, gender-based violence, women as agents of change). Women
are disproportionately affected by disasters in several outcomes, including life expectancy,
unemployment, labor force re-entry, and relative asset losses. Gender-based violence—a
manifestation of systematic inequality between men and women—is exacerbated at times of
emergency.
While women and girls are in a disadvantaged position in society at large, this does not by
default translate into worse disaster outcomes. A common belief is that women are more likely
to die during a disaster. Yet, men account for 70 percent of ood-related deaths in Europe and
the United States. This is driven by several reasons, including an overrepresentation of men
in rescue professions. In less developed countries, more women tend to die from disasters.
Although men are also overrepresented in risky and rescue professions in these countries,
gender gaps in access to information on disaster preparedness, access to public shelters and
limits to mobility seem to contribute more to gendered mortality outcomes, putting women at
a disadvantage.
Boys and girls are affected differently by disasters. For health outcomes, boys are disadvantaged
when affected in utero or early life due to biological factors. However, the preferred treatment
of boys means that girls are worse off when their families face scarcity due to disaster and
families are more likely to take their daughters out of school if they cannot pay tuition or the
domestic burden increases after a disaster. On the other hand, if labor needs increase—for
example, in agriculture—boys are more likely to be taken out of school. Disaster impacts on
education are also reected in child marriage and labor rates.
Economically, disasters have different effects for men and women, with women largely
disadvantaged. In developing countries, agriculture is the most important economic sector for
female employment; and women farmers tend to be more vulnerable to disasters than male
farmers. The domestic burden also tends to increase after a disaster, and women usually bear
the brunt of this, at the cost of missing out on other income-generating activities. Their lack of
access to bank accounts also means that women’s assets are less protected than men’s.
10 • Gender Dimensions of Disaster Risk and Resilience
Gender-based violence is exacerbated in postdisaster situations. Domestic violence rates also
tend to increase in slow-onset disasters, such as droughts.
Finally, women are important agents of change and their involvement and leadership in
decision making when it comes to disaster planning, response and reconstruction is crucial for
making sure that disasters do not disadvantage women or girls.
S.2 • Resilience: preparedness and coping capacity
Gender dynamics play a role in a wide range of factors associated with resilience, from
preparedness levels to access to coping mechanisms that can support recovery.
Women tend to perceive risks more saliently than men, but there is no clear evidence that this
translates into greater preparedness action. When it comes to evacuation behavior, access to
early warning and safe shelter options are important determinants. In developing countries,
women have lower access to information and communication technologies, which could
inuence their access to relevant information in postdisaster situations. In many cases, lack of
access to safe shelter is also an issue, often deterring women from evacuating.
Individual and household disaster recovery is driven by access to coping mechanisms—
including nance and savings, assets, government support, livelihoods, and the ability to switch
income sources in the aftermath of a disaster—or adaptation through migration.
Lower access to bank accounts, formal sources of nance, and stable income impacts women’s
ability to cope and recover in the aftermath of a disaster. While microlending and informal
nance can promote recovery, overreliance on these options can make women particularly
vulnerable to disasters. Further, in places where women keep their assets in high-value,
tradable goods, their assets are more likely to be sold in times of hardship, potentially helping
the family recover, but also reducing their wealth.
The postdisaster coping mechanism adopted also affects gender equality. For example, male
out-migration can have positive implications for women’s voice and agency by transforming
household power dynamics.
S.3 • Data gaps in disaster risk management
To understand the underlying gender dynamics of disaster risk and design appropriate
policies, the rst step is ensuring data collection is disaggregated by sex and age. Disaster risk
management lags behind other sectors in collecting and reporting of sex- and age disaggregated
data (SADD). Three priorities are:
» Making sure SADD is available for casualties and affected populations.
» Collecting more information on damages and losses at the individual, rather than
household, level.
» Improving access to information on people with disabilities or from racial, ethnic, or
religious minorities.
Summary • 11
S.4 • Key messages for policy making
Policies that take gender dynamics into account will mitigate disaster impacts more eciently
without exacerbating existing gender gaps. The full report recommends a set of policy actions
in exposure, vulnerability, preparedness, and coping capacity for use before, during and after
a disaster to mitigate differentiated impacts for men and women, boys and girls. These policies
are indicative, and do not replace the need for a local gender gap assessment before deciding
on policy action. Their key messages are:
» Identifying a gender gap in disaster outcomes—for example, in mortality—but not what
drives them is a lost opportunity for creating effective policies and interventions.
» Community involvement is key to channeling preparedness and early warning
information, and women’s participation in this process is crucial.
» Increasing female representation in disaster risk management and civil protection
agencies helps legitimize and support women’s contributions to disaster risk reduction
and resilience.
» Social protection is an increasingly important policy for addressing disaster vulnerability
and can be carefully used to mitigate gender-differentiated disaster impacts.
» Disaster reconstruction is an opportunity to build back in a way that breaks down the
constraints faced by women.
» Undertaking a local assessment helps identify gaps and barriers that make natural
disasters particularly harmful for certain populations before policy agendas are set.
S.5 • Next steps
Next steps for this work can be organized around both analytical and operational priorities.
Analytical priorities include closing important knowledge and data gaps. Specically, this
involves:
» Moving beyond anecdotal evidence when relevant and possible by leveraging existing
global and regional data to scale up case studies.
» Understanding what does and does not work for different population groups by investing
more in rigorous impact evaluations of disaster risk management and resilience building
projects and interventions.
» Leveraging new data and technologies—such as mobility data—to explore topics,
previously understudied, including gendered evacuation patterns and behaviors.
From an operational perspective, resources and guidance on how to conduct gender gap
assessments in disaster risk management will be needed at the country and project level.
While this report can inform the design of gender gap assessments by providing a useful
conceptual framework, relevant literature and data sources, it cannot replace the need for
local assessments. Agreeing on a common framework for local assessment will help achieve
consistency in disaster risk management gender gap assessments.
12 • Gender Dimensions of Disaster Risk and Resilience
Introduction
I.1 • Background
Gender dynamics impact the way men and women, boys and girls are affected by disasters
and their capacity to recover from disasters. As well as dening expected roles in a society and
determining how men and women prepare for, react to, and recover from disasters, gender
dynamics inuence the extent to which women are part of disaster planning and recovery.
Gendered differences in disaster outcomes inuence the prevailing socioeconomic conditions,
which determine gender equality and the capacity to recover from future shocks. For example,
when a lack of access to bank accounts means that women hold a larger share of their assets
in tangible form, they are at greater risk of losing their assets than men, which would worsen
gender inequality.
Gendered differences in disaster impacts can also inuence resilience to future disasters,
creating a negative feedback loop. For example, in the context of frequent ood exposure,
prevailing social norms may drive women to stay close to their homes so they can salvage
belongings when the ood comes, while men pick up employment outside the community.
The nearby labor opportunities therefore available to women may not offer the income and
stability they need to respond eciently to ood exposure, which in turn affect their capacity
to cope with future shocks.
Women usually play an important role in disaster preparedness, response, and recovery efforts.
Their involvement often results in better performance and has a transformative effect on the
communities they serve.
BOX I.1
Denition of terms
» Gender refers to the social, behavioral, and cultural attributes, expectations, and
norms associated with being male or female.
» Gender inequality refers to how these factors determine the way in which men and
women relate to each other and the resulting differences in power between them.
» Agency is the capacity to make decisions about one’s own life and act on them to
achieve a desired outcome, free of violence, retribution, or fear.
» Gender-based violence is an act—or threat of an act—perpetrated against a person’s
will, that inicts physical, mental, and sexual harm or suffering, and is based on socially
ascribed (gender) differences between males and females. These acts can occur in
public or in private.
Sources: World Bank 2012, Klugman et al. 2014, IASC 2015.
Introduction • 13
An improved understanding of the gender dynamics of disaster risk and resilience allows
for better policy and program design, which benets all. Debunking myths and stereotypes,
uncovering the underlying drivers of gendered outcomes, recognizing that there are multiple
vectors of vulnerability and exclusion, calling for a more contextualized, and nuanced analysis
are all important components of that effort. For example, the experience of girls and boys is
different from that of women and men. Narratives that depict women as perpetually vulnerable
and men as inevitably antagonistic ignore ways in which women are agents of change and
neglects both the constraints men face and the opportunities for mobilizing them as allies for
gender and social equality (Doss et al. 2018).
This report is a review of evidence and data on how men and women, boys and girls are
impacted by, prepare for and cope with disasters. The objective is to map out, understand and
identify the most important knowledge gaps in the channels through which gender dynamics
affect outcomes in disaster impacts and resilience.
The review contributes to existing knowledge by providing an up-to-date, in-depth, and
comprehensive analysis of gender dynamics in disasters, their impacts, and consequences. It
has a broad scope, covering almost all types of natural disaster, focusing on direct and indirect
impacts as well as resilience—including both preparedness and coping capacity—and reviewing
literature from developed and developing countries.
Recent literature reviews have mostly focused on gender and climate change. Many explicitly
cover links between natural disasters and gender (Goh 2012; Sellers 2016); others implicitly
identify causes of women’s vulnerability to climate change, including the increasing prevalence
of natural disasters (Schwerhoff and Konte 2020). Although a signicant number of reviews
are on climate change and gender, in-depth reviews of the literature on gender in the context
of natural disasters are limited. This review updates and adds to previous work on gender and
natural disasters—notably foundational work by Enarson, Fothergill, and Peek (2007, 2018) and
Enarson (2000)—and thematic literature reviews, including impacts on: gender-based violence
(Phillips and Jenkins 2016); children and adolescent girls (Bradshaw and Fordham 2015; Gil-
Rivas 2014); and health and well-being (Harville, Xiong, and Buekens 2010).
This report is part of the Global Facility for Disaster Reduction and Recovery’s (GFDRR’s)
commitment to the World Bank Group’s Gender Strategy 2016–2023, which has raised the bar
on deepening gender equality in World Bank operations and policy dialogue (World Bank 2015).
It adds to similar gender-focused work in thematic areas, including Das (2017), which focuses
on the relation between gender and water, and Orlando et al. (2018) on gender inequality in
energy. This work will inform future operational activities and operational guidance notes.
1
The framing of this paper is aligned to Sustainable Development Goal (SDG) 5 on gender
equality; it is also in keeping with SDG 11 on sustainable development, which includes disaster
risk reduction.
Section 1 focuses on differentiated impacts resulting from gender gaps in exposure and
vulnerability, while Section 2 explores the outcome variables that drive resilience, such as
knowledge, behaviors and risk perception, which improve preparedness and access to coping
mechanisms, inuencing capacity to recover from a shock. Section 3 provides an overview of
access to and the use of sex-disaggregated data in disaster risk management. Sections 4 and 5
offer concluding remarks, policy recommendations and next steps.
14 • Gender Dimensions of Disaster Risk and Resilience
I.2 • A conceptual framework
This report outlines a non-linear framework for considering the role of gender in disaster risk
and resilience. It combines two existing World Bank frameworks, for:
» Analyzing gender (World Bank 2012)
» Assessing socioeconomic resilience to natural hazards (Hallegatte et al. 2017).
The framework in gure I.1 is a simplied representation of a complex reality. Natural hazards
such as oods, earthquakes and tsunamis, are gender neutral. The intensity of a cyclone, an
earthquake or a tsunami is the same for men and women. However, the impact of a disaster
(orange circle), depends on the intensity and type of hazard, who and what is exposed, and levels
of vulnerability, preparedness, and capacity to cope with and recover from the shock. Gender
inequality (purple circle) arises from the expected roles of men and women in a society, which
inuence their socioeconomic status, level of agency, and, as a result, the way they prepare
for, react to, are impacted by, and recover from, disasters. The overlay (maroon area) between
gender inequality and disaster impacts includes factors that drive disaster impacts and are also
inuenced by gender dynamics.
Figure I.1 • A conceptual framework for considering gender dynamics and disaster impacts
Hazard
Gender inequality
Exposure
Vulnerability
Preparedness
Coping capacity
Impact factors shaped by
gender dynamics:
Disaster risk
management
Society
Disaster impacts
Sources: Adapted from World Bank 2012 and Hallegatte et al. 2017.
Introduction • 15
In the context of disasters, gender dynamics inuence:
» Exposure and vulnerability, by affecting the types of asset men and women own, how
they gain income, their level of engagement in disaster risk management, and so on.
» Preparedness, by affecting conditions that determine risk perception levels, access to
early warnings and evacuation behavior.
» Coping and recovery, by affecting access to formal and informal nance and stable and
high-paying labor, which can support recovery.
When gender dynamics inuence disaster impacts, as indicated in the overlay maroon area, it
leads to differentiated impacts for men and women, boys and girls. Gender-differentiated impacts
can exacerbate gender inequality by inuencing the prevailing socioeconomic conditions. This,
in turn, can inuence the factors determining the disaster impacts of future hazards. We call this
the negative feedback loop, and it is illustrated in gure I.1 with the dotted arrows.
Disaster risk management should operate in the maroon overlay area (gure I.1). This means
good disaster risk management should consider ways in which gender dynamics inuence
disaster impacts in any given area before making decisions on policies and interventions. When
disasters affect women and men differently, policy makers have a responsibility to use the tools
available for mitigating disaster impacts and strengthening resilience to close that gap.
I.3 • Challenges and limitations
Data limitations are a signicant challenge in understanding how gender dynamics inuence
disaster vulnerability, preparedness, and recovery. When assessing the impact of disasters on
women and men and how they recover from them, some of the variables of interest—such as
monetary poverty and disaster losses—are measured at household level. But treating households
BOX I.2
Denition of terms
» Exposure constitutes the assets that are of interest and at risk—including population,
environment, economy, buildings—in a disaster-affected area.
» Vulnerability is those assets’ susceptibility to damage or impact from a hazard.
» Risk is often represented as the probability or likelihood of hazardous events or trends
occurring, multiplied by the impacts if they do occur. Hazard, exposure, and vulnerability
constitute risk, and are the three usual drivers of disaster risk.
» Resilience is a system and its component parts’ ability to prepare (anticipate, absorb,
accommodate), or cope (recover) from the effects of a hazardous event in a timely and
ecient manner, including by ensuring the preservation, restoration, or improvement of
its essential basic structures and functions.
Sources: Hallegatte et al. 2017, World Bank 2013, UNDRR 2020.
16 • Gender Dimensions of Disaster Risk and Resilience
as a single unit assumes that disaster losses, and resources used to cope with disasters, are
shared equally inside the households. Given the observed gaps in access to and control over
assets between men and women, this is an unrealistic assumption.
Focusing on female and male household headship to identify gender gaps or gender-
differentiated impacts is not a substitute or solution to this problem. Male-headed households
tend to be two-parent households, while female-headed ones are often (but not always) single-
parent households. As a result, the latter face specic challenges that could be unrelated to
gender dynamics. Using this variable also wrongly assumes that women in male-headed
households have equivalent outcomes to women in female-headed ones. Data gaps remain,
and assessing intrahousehold gender dynamics continues to be a challenge. So, this report
prioritizes evidence using individual-level analysis and presents results-based household-level
analysis conservatively.
Gender dynamics are context-specic and global assessments do not replace the need for local
analysis. The conclusions in this report are based on consolidated results from case studies
from different contexts and, in the best of cases, global reviews and data sources. The more
case studies and data that are available to assess a particular question, the more condent the
response. But even for the questions where several case studies are available, the assessment
is not condently representative beyond the context of those specic case studies. As such,
the conclusions drawn do not replace the need to do local assessments. Rather, this report
provides a framework for identifying gender gaps in the context of disaster risk and resilience,
guiding local assessments to the most important issues, and exploring what could be done to
address them.
I.4 • Dening hazards and disasters
According to the Centre for Research on the Epidemiology of Disasters,
2
a disaster is a situation
or event that overwhelms local capacity, requiring an external response, or is recognized
as such by national and/or international actors. Natural disasters are severe alterations in
the normal functioning of a community or society due to natural hazard events (IPCC 2014).
Natural hazards are naturally occurring physical phenomena caused by either rapid or
slow-onset events; they can have geophysical, hydrological, meteorological, climatological or
biological origins.
3
Figure I.2 • Typology of natural hazards
• Earthquakes
• Tsunamis
• Volcano
eruptions
• Landslides
• Flooding
• Storms
• Storm surges
• Extreme
temperatures
• Epidemics
• Insect or
animal
plagues*
• Droughts and
desertification
• Increased
salinization
• Rising sea levels
• Thawing of
permafrost
Slow onset Rapid onset
Natural hazards
Source: Based on denitions provided by EM-DAT
5
Note: *This report does not cover biological hazards and their gender-differentiated impacts.
Introduction • 17
Although their name suggests theys are strictly nature-induced, natural disasters can have
human origins, too—for example, when they are caused by climatological change. Figure I.2
shows a simplied classication of natural hazard types. This report does not include biological
disasters, as these are broadly covered in the health literature. Throughout the report, we use
‘natural hazard’ to refer to the event or physical phenomenon itself.
4
We use ‘natural disaster’,
‘disaster’, and ‘shock’ interchangeably to describe disasters caused by natural hazards.
I.5 • The impact of COVID-19
The report is written at a time of unprecedented crisis caused by the surge of COVID-19, which
has affected gender dynamics, including the ones discussed in this report. While epidemics and
pandemics are outside the scope of this report (gure I.2), it would be negligent not to consider
the deep impact that the COVID-19 crisis has had on society and the new challenges that have
arisen in relation to gender dynamics in disaster risk management and resilience.
Early assessments on the impacts of the pandemic have found that, although men seem to be
more susceptible to the virus, women are disproportionally affected by its social and economic
impacts (de Paz et al. 2020). Women are overrepresented in some of the occupations that are
being hardest hit—such as retail, travel, leisure, and hospitality. When schools close or children
are taken out of school, the increased childcare and other domestic responsibilities often fall on
women, which has further implications for female labor participation and nancial autonomy.
There are also reports of a surge in gender-based violence during quarantine, when access to
supportive services is disrupted (Haneef and Kalyanpur 2020). Finally, their lack of control over
housing, land and property may leave women particularly vulnerable to health crises. If they
lose their partner, women can also lose their housing and livelihoods, as was reported during
the HIV and Ebola epidemics (Stanley and Prettitore 2020).
These effects lead to differences in men’s and women’s capacity to prepare for and recover from
natural disasters. Little is known about the gender dynamics of the COVID-19 crisis and even
less is known about how they will manifest when risks are compounded by natural disaster.
However, governments and researchers would be advised to keep this new reality in mind as
they consider the next steps for this agenda, both in policy and research.
References for Introduction
Bradshaw, S and Fordham, M. 2015. “Double Disaster: Disaster Through a Gender Lens.” In Shroder, J F, Collins, A E,
Jones, S, Manyena, B, Jayawickrama (eds.) Hazards, Risks and Disasters in Society, 233–251. Academic Press. https://doi.
org/10.1016/B978-0-12-396451-9.00014-7.
Das, M B. 2017. The Rising Tide: A New Look at Water and Gender. World Bank: Washington, DC. https://openknowledge.
worldbank.org/handle/10986/27949.
de Paz, C, Muller, M, Munoz Boudet, A M, and Gaddis, I. 2020. Gender Dimensions of the COVID-19 Pandemic. World Bank:
Washington, DC. http://hdl.handle.net/10986/33622.
Doss, C, Meinzen-Dick, R, Quisumbing, A, and Theis, S. 2018. “Women in Agriculture: Four myths.” Global Food Security,
16: 69–74. https://doi.org/10.1016/j.gfs.2017.10.001.
Enarson E, Fothergill A, and Peek L. 2007. “Gender and Disaster: Foundations and Directions.” In Rodríguez H, Donner
W, Trainor J (eds) Handbook of Disaster Research, 130–146. Springer: New York, NY. https://doi.org/10.1007/978-0-387-
32353-4_8.
———2018. “Gender and Disaster: Foundations and New Directions for Research and Practice.” In Rodríguez H,
Donner W, Trainor J (eds) Handbook of Disaster Research. Handbooks of Sociology and Social Research, 205–223.
Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-319-63254-4_11.
Enarson, E. 2000. Gender and Natural Disasters. ILO.
Gil-Rivas V. 2014. “The Impact of Disaster on Children and Adolescents: A Gender-Informed Perspective.” In Roeder
L (eds.) Issues of Gender and Sexual Orientation in Humanitarian Emergencies. Humanitarian Solutions in the 21st
Century, 1–18. Springer, Cham. https://doi.org/10.1007/978-3-319-05882-5_1.
18 • Gender Dimensions of Disaster Risk and Resilience
Goh, A. 2012. A Literature Review of the Gender-differentiated Impacts of Climate Change in Developing Countries. CAPRi
working paper no 106. https://doi.org/10.2499/CAPRiWP106.
Hallegatte, S, Vogt-Schilb, A, Bangalore, M, and Rozenberg, J. 2017. Unbreakable: Building the Resilience of the Poor in the
Face of Natural Disasters. World Bank: Washington, DC. http://hdl.handle.net/10986/25335.
Haneef, C and Kalyanpur, A. 2020. Global Rapid Gender Analysis for COVID-19. CARE and International Rescue Committee.
https://www.rescue.org/report/global-rapid-gender-analysis-covid-19.
Harville, E W, Xiong, X, and Buekens, P. 2010. “Disasters and Perinatal Health: a Systematic Review.” Obstetrical &
Gynecological Survey, 65(11): 713–728. https://doi.org/10.1097/OGX.0b013e31820eddbe.
IASC. 2015. Guidelines for Integrating Gender-based Violence Interventions in Humanitarian Action Response. Inter-Agency
Standing Committee. https://gbvguidelines.org/en/.
IPCC. 2014. Annex II: Glossary. In Mach, K J, Planton, S, and von Stechow, C (eds.), Climate Change 2014: Synthesis Report.
Klugman, J, Hanmer, L, Twigg, S, Hasan, T, McCleary-Sills, J, and Santamaria, J. 2014. Voice and Agency: Empowering Women
and Girls for Shared Prosperity. World Bank: Washington, DC. https://doi.org/10.1596/978-1-4648-0359-8.
Orlando, M B, Janik, V L, Vaidya, P, Angelou, N, Zumbyte, I, and Adams, N. 2018. Getting to Gender Equality in Energy
Infrastructure: Lessons from Electricity Generation, Transmission, and Distribution Projects. Energy Sector Management
Assistance Program (ESMAP) Technical Report no. 012/18. World Bank: Washington, DC. http://hdl.handle.
net/10986/29259.
Phillips, B and Jenkins, P. 2016. “Gender-based Violence and Disasters.” In Racioppi L and Rajagopalan S (eds) Women and
Disasters in South Asia: Survival, Security and Development, 225. ISBN 9780367177140.
Schwerhoff, G and Konte, M. 2020. “Gender and Climate Change: Towards Comprehensive Policy Options.” In Konte, M
and Tirivayi, N (eds.) Women and Sustainable Human Development, 51–67. https://doi.org/10.1007/978-3-030-14935-2_4.
Sellers. 2016. Gender and Climate Change: A Closer Look at Existing Evidence. Global Gender and Climate Alliance. https://
wedo.org/gender-and-climate-change-a-closer-look-at-existing-evidence-ggca/.
Stanley, V and Prettitore, P. 2020. “How COVID-19 puts women’s housing, land, and property rights at risk.” World Bank
blog. https://blogs.worldbank.org/sustainablecities/how-covid-19-puts-womens-housing-land-and-property-rights-risk.
UNDRR. 2020. Hazard Denition & Classication Review. Technical Report. https://www.undrr.org/publication/hazard-
denition-and-classication-review.
World Bank. 2012. World Development Report 2012. World Bank: Washington, DC. https://doi.org/10.1596/978-0-8213-
8810-5.
———. 2013. Building Resilience: Integrating Climate and Disaster Risk into Development. World Bank: Washington, DC.
https://openknowledge.worldbank.org/handle/10986/16639.
———. 2015. Gender Strategy (FY16-23): Gender Equality, Poverty Reduction, and Inclusive Growth. World Bank: Washington,
DC. http://hdl.handle.net/10986/23425.
Endnotes
1. Operational guidance notes include those in the Disaster Recovery Guidance Series, such as GFDRR. 2018. Gender
Equality and Women’s Empowerment in Disaster Recovery. World Bank: Washington, DC. https://www.gfdrr.org/en/
publication/gender-equality-and-womens-empowerment-disaster-recovery.
2. EM-DAT: International Disaster Database. PowerPoint presentation, April 2006. https://www.emdat.be/sites/default/
les/Emdat.pdf.
3. EM-DAT. The International Disaster Database. https://www.emdat.be/database.
4. This differs from the disaster risk management literature, in which ‘hazards’ refer to the likelihood of hazard events
occuring (UNDRR 2020; Hallegatte et al. 2017).
5. https://public.emdat.be/about. The disasters classication used in EM-DAT is based on and adapted from the
Integrated Research on Disaster Risk (IRDR) Peril Classication and Hazard Glossary. http://www.irdrinternational.org/
wp-content/uploads/2014/04/IRDR_DATA-Project-Report-No.-1.pdf.
Disaster Impacts • 19
SECTION 1
Disaster impacts:
exposure and vulnerability
Men and women face different risks of exposure and vulnerability to natural hazards, which
leads to differentiated impacts of disasters. It is important to study the channels through which
natural hazards affect men and women differently and systematically assess those differences
to ensure assessments and project designs maximize outcomes for all.
This section focuses on the gender gaps in exposure and vulnerability to natural hazards that
result in differentiated impacts of disasters for women and men, boys and girls. It is based on
the factors driving gender inequality according to the World Bank Gender Strategy 2016–2023
(World Bank 2015b), which include:
» Endowments: health, education, and child labor
» Economic outcomes: livelihoods, assets, and consumption
» Voice and agency: child marriage, gender-based violence, women as agents of change.
1.1 • Health
This subsection focuses on how the gender dynamics of exposure and vulnerability lead to
differentiated impacts in life expectancy and mortality, mental health, and early childhood
development. It also covers women’s health needs in the context of disasters.
1.1.1 • Life expectancy and mortality
Globally, natural disasters have the following impacts on mortality and life expectancy:
» Direct impacts: for example, death from injury or drowning
» Increased morbidity: for example, repeated oods can lead to chronic respiratory
disease, which can reduce life expectancy
» Economic impacts on life expectancy: for example, a lower income reduces access to
healthcare and quality food.
Natural disasters have a disproportionately negative effect on women’s life expectancy. Globally,
women live about 4.7 years longer on average than men, including in most low and middle-
income countries. In a study covering 141 countries from 1981–2002, Neumayer and Plümper
(2007) nd that natural disasters—including droughts, earthquakes, extreme temperatures,
famines, res, oods, landslides, volcano eruptions, waves/surges, and windstorms—lower
women’s life expectancy more than men’s, either directly, by killing more women than men or
indirectly, by killing women at an earlier age due to higher morbidity and more severe economic
impacts. Other studies, covering different types of natural disaster, also nd that women die at
a higher rate than men, particularly in developing countries (Doocy et al. 2013; Krishnaraj 1997;
Pradhan et al. 2007; Sugimoto et al. 2011).
20 • Gender Dimensions of Disaster Risk and Resilience
Lower socioeconomic status and limited access to information and agency seem to drive
women’s disaster vulnerability and contribute to their higher disaster-related mortality rates.
Neumayer and Plümper (2007) nd that the disproportional impact of natural disasters on
women’s mortality is weaker in countries where women have a better socioeconomic status.
1
Access to warning information and safe shelters matters. Depending on their age, women
were three to ve times more likely than men to die in Bangladesh’s 1991 cyclone (Ikeda 1995).
The author suggests that this discrepancy was primarily due to women’s limited access to risk
information and their lack of agency for making decisions about a hazard event. Men quickly
and actively gathered warning information about the cyclone, while women mainly relied on
word of mouth for their information and some were not aware of the cyclone. Women also had
limited knowledge about the location of shelters. The nal decision to evacuate seemed to fall
on male family members, even when women wanted to evacuate.
Although primarily driven by socioeconomic and cultural context, biological and physiological
differences can also contribute to the gender gap in postdisaster mortality and life expectancy
(see discussion in Sellers 2016; Neumayer and Plümper 2007). For example, Frankenberg et al.
(2011) nd that adult women were twice as likely to die in Indonesia’s 2004 tsunami, and that
in Aceh and North Sumatra, physiological differences between adult men and women were
a contributing factor in mortality. But while the authors account for socioeconomic status,
physical differences (height), and household composition to assess the gender gap in adult
mortality, there are other possible contributing factors that should be controlled for, including:
» The ability to self-evacuate through learned skills such as climbing and swimming
(Oxfam International 2005; Cannon 2002; Hunter et al. 2011)
2
» Women’s clothing restricting their movements (Alam and Collins 2010)
» The higher likelihood of women evacuating with children and elderly (Schwoebel and
Menon 2004), and
» Differences in knowledge and shelter safety conditions, affecting women’s ability to
safely access these shelters (Paul and Dutt 2010; Haynes et al. 2016).
Findings and discussions on the role of these factors, however, are primarily anecdotal,
inconclusive, and in many cases, speculative (Sellers 2016).
In high-income contexts, men’s disaster-related mortality rate is higher than women’s, seemingly
driven by exposure. Using the World Health Organization’s (WHO’s) mortality database from
1995–2011 covering 63 countries, Zagheni, Muttarak, and Striessnig (2015) nd that men are
more likely to have died from oods and storms. However, the database does not cover most
of Africa and Asia, and, when compared to EM-DAT data,
3
seems to underestimate number
of deaths from hydrometeorological events. Higher disaster mortality among men has been
observed in both developed (Ashley and Ashley 2008; Badoux et al. 2016; Doocy et al. 2013) and
developing countries (Delaney and Shrader 2000). A review of ood events in Europe and the
United States nds that males account for 70% of ood-related deaths (Doocy et al. 2013). Men
are often overrepresented in risky rescue work and other outdoor activities, such as forestry
and construction, increasing their direct exposure to natural hazards and often resulting in
more casualties (Badoux et al. 2016; Delaney and Shrader 2000).
There is a lack of conclusive evidence on the gendered impacts on life expectancy by disaster
type. Neumayer and Plümper (2007) nd that the gender gap in terms of impact grows with
the severity of the disaster, to women’s disadvantage. However, their study uses an annualized
Disaster Impacts • 21
average of all disasters for a country to measure disaster severity, so it is not possible to
differentiate effects by single disaster or disaster type. Understanding the relationship between
types of disaster and men’s and women’s mortality would shed further light on how natural
disasters impact them differently.
1.1.2 • Mental health
Natural disasters take a toll on mental health and well-being. Women consistently show
higher propensity towards depression, anxiety, and stress-related disorders, while suicide is
more common among men (Hammen 2005; Hawton and van Heeringen 2009; Olff et al. 2007).
Studies in different regions and for different disasters document that women have higher odds
of experiencing post-traumatic stress disorder (PTSD) and anxiety after a disaster. The ratio
of women experiencing mental health challenges to women not experiencing such challenges
is higher than the ratio for men. Two notable studies with large sample size are on the 2004
Indian Ocean tsunami in Indonesia (Frankenberg et al. 2008) and the 1998 oods in Hunan,
China (Liu et al. 2006). Smaller studies providing consistent evidence include the 1999 Marmara
earthquake in Turkey (Başoǧlu, ŞalcIoǧlu, and Livanou 2002), Cyclone Nargis in Myanmar (Kim
et al. 2010), oods in the United Kingdom (Mason, Andrews and Upton 2010; Paranjothy et al.
2011), Hurricane Katrina in the United States (Mills, Edmondson and Park 2007), and bushres
in Australia (Bryant et al. 2014).
Although differentiated impacts on men’s and women’s mental health are well documented, the
reasons for this differentiation are much less understood. Olff et al. (2007) nd that many factors
might contribute to the higher rates of PTSD among women, including: the type of trauma women
experience (more violence, sexual, interpersonal, and gender-based violence); their stronger
perception of threat and loss of control; and insucient social support resources for managing
trauma-related symptoms. Studies from rural Australia hypothesize that higher suicide rates
among men are the result of traditional masculinity preventing men from seeking help (Alston
2012; Alston and Kent 2008; Bryant and Garnham 2015; Hanigan et al. 2012; Judd et al. 2006).
Other studies associate livelihood choices and suicide, nding that drought-related crop failures
leave farmers, particularly male farmers, at higher risk of suicide (Hagen et al. 2019; Hanigan et
al. 2012; Kennedy and King 2014). One could hypothesize that the effect of prolonged crop failure
from consecutive droughts or other disasters would be different from one-time disasters.
1.1.3 • Early childhood development
Disasters can have long-lasting effects on early childhood development, driven by biology
(where boys are disadvantaged) and preferred treatment (where girls are disadvantaged)
(Dinkelman 2015; Gunnsteinsson et al. 2019; World Bank 2020). These ndings are consistent
with the strand in health literature that nds that boys are more vulnerable to nutritional
and physical stress in utero and early life than girls (Kraemer 2000). For example, a study in
Bangladesh nds that tornado exposure has more impact on infant boys than girls, and that
the positive health effects of vitamin A supplements to dampen the effects of in utero tornado
exposure were substantially larger for boys, while girls were largely unaffected (Gunnsteinsson
et al. 2019). In Japan, in utero cold wave exposure was found to have a stunting effect only on
boys, who experienced an average height reduction of 0.1–0.8cm in Japan’s coldest regions
(Ogasawara and Yumitori 2019). Kumar, Molitor, and Vollmer (2014) nd that children—
especially boys—in rural India exposed to droughts in utero and during their rst year are
more likely to have a lower weight for age and be underweight or severely underweight.
Although boys are likely to be more innately vulnerable to natural disasters in utero, girls
face social vulnerability due to preferred treatment of boys when families face scarcity due
to disasters. Disasters crowd out critical early childhood health investments—for example,
22 • Gender Dimensions of Disaster Risk and Resilience
in nutrition and immunization. Gender discrimination in investment and resources is well
documented (see, for example, Miller 1997) and boys may be prioritized over girls when
resources are scarce. Analyzing health outcomes of 110,000 children under ve in India, Datar
et al. (2013) nd that exposure to natural hazards increases susceptibility to illnesses such
as diarrhea, fever, and acute respiratory illness. While girls and boys are equally susceptible
to illnesses, the adverse effect of nutritional outcomes is smaller among boys; implying that
disaster effects on children’s growth are often a result of households prioritizing boys in
postdisaster times. In Japan, although the stunting effects of prenatal cold wave exposure was
only found in boys, postnatal cold wave exposure seems to only affect girls (Ogasawara and
Yumitori 2019). Although the authors do not have access to individual birth data, a possible
explanation is that parents’ inability to distinguish the sex of the fetus during pregnancy makes
them take the same precautions against cold regardless of sex, while postnatally, precautionary
behavior is biased against girls.
1.1.4 • Women’s health
Women’s reproductive and maternal health needs create unique postdisaster health impacts.
When natural disasters negatively affect access to reproductive healthcare and modern
contraception, many health outcomes for women are compromised (Nour 2011). Damaged
health facilities, disrupted infrastructure and diminished economic resources can reduce
access to these services, interrupting women’s access to modern contraception (Behrman and
Weitzman 2016; Hapsari et al. 2009; Leyser-Whalen, Rahman, and Berenson 2011), family
planning, feminine hygiene products and maternal care (Kissinger et al. 2007; Nour 2011;
Stockemer 2006). Hapsari et al. (2009) nd that the prevalence of unplanned pregnancy in
Yogyakarta after the Indian Ocean tsunami was higher among women who had diculties
obtaining contraceptives. Behrman and Weitzman (2016) show that heightened earthquake
intensity reduced the use of contraceptives in Haiti, resulting in increased pregnancy, including
unwanted pregnancy. The authors suggest that the impact of the disaster may have changed
intrahousehold power dynamics, as women in most affected areas were less successful at
negotiating condom use in their partnerships. Disasters can also exacerbate pre-existing race
and class barriers for women to healthcare, as seen after Hurricane Ike in the US Gulf coast,
where black women were more likely to have diculty accessing contraception than Hispanic
or white women (Leyser-Whalen, Rahman, and Berenson 2011).
Table 1.2 • Summary of literature on the gender gap in health outcomes in the context of
natural disasters
Country Disaster/Year Findings Reference
MORTALITY AND LIFE EXPECTANCY
Global:
141 countries
Disasters, 1981–2002 Disasters and their subsequent impact kill more women on
average than men or kill women at an earlier age than men.
(Source: EM-DAT)
Neumayer and
Plümper 2007
Global:
4,093 events,
no mention
of country
coverage
Flood events,
1980–2009;
excludes ooding
caused by hurricane,
storm surges, and
tsunamis
Men are more likely to die from ooding in developed countries,
whereas in developing countries, mortality among women is
higher. The primary cause of ood-related mortality is drowning.
(Sources: EM-DAT, the Dartmouth Flood Observatory Global Archive of Large Flood
Events Database, and a review of historical ood events)
Doocy et al. 2013
Global:
63 countries
Hydrometerological
disasters, 1995–2011
Across all age groups, mortality rates from hydrometeorological
disasters are higher for men than for women; this difference is
higher among adults compared to children or the elderly (WHO).
EM-DAT underestimates the numbers, especially for high-impact
events.
(Sources: WHO mortality database and EM-DAT)
Zagheni,
Muttarak, and
Striessnig 2015
Bangladesh Cyclone, 1991 Women aged over 19 were three to ve times more likely to die. Ikeda 1995
Disaster Impacts • 23
Bangladesh Tornado, 2005 Women were 1.24 times more likely to die. Sugimoto et al.
2011
Nepal,
Sarlahi district
Flood, 1993 Fatality rates: 13.3 per 1,000 for girls and 9.4 per 1,000 for boys, 6.1
per 1,000 for women and 4.1 per 1,000 for men.
Pradhan et al.
2007
Indonesia,
Sumatra
Tsunami, 2004 Women aged 15-44 died twice as often as men of the same age. Frankenberg et
al. 2011
Indonesia,
Sumatra
Tsunami, 2004 Men living in highly affected areas who survived the tsunami had
lower mortality risks over the next ve years than men from less
affected areas. The same is not found for women.
Ho et al. 2017
India Latur earthquake,
1993
Although only 48 percent of the population, 55 percent of those
who died were women.
Krishnaraj 1997
Honduras and
Nicaragua
Hurricane Mitch, 1998 More men than women died from the hurricane in both countries. Delaney and
Shrader 2000
United States Floods, 1995–2005 Depending on the age group, men are 1.5–2 times more likely to
die in oods than women.
Ashley and
Ashley 2008
Switzerland Disasters, 1944–2015 75% of all people who died were male. Badoux et al.
2016
MENTAL HEALTH
Indonesia Tsunami, 2004 Among 20,000 tsunami survivors, post-traumatic stress reactivity
was higher among women than men.
Frankenberg et
al. 2008
Turkey Earthquake, 1999 Among 1,000 interviewed survivors, PTSD scores and depression
rates were higher among women than men (53% vs 33% and 38%
vs 24% respectively).
Başoǧlu,
ŞalcIoǧlu, and
Livanou 2002
Japan Earthquake, 2011 A notably larger share of women (40%) and men (24%) reported
deteriorating mental health in affected areas than in non-affected
areas (24% of women and 13% of men. However, men received
care less often than women.
Yoshida 2014
EARLY CHILDHOOD DEVELOPMENT
India All disasters in EM-
DAT during 1991–93,
1997–99, 2004–06
Girls and boys are equally susceptible to acute illness as a result
of disasters, but girls are more likely to suffer negative long-term
nutritional outcomes of disasters.
Datar et al. 2013
South Africa Drought, 1996 Drought exposure in infancy raises later-life disability rates by
3.5–5.2%, with effects concentrated in physical and mental
disabilities. While both boys and girls are impacted by drought,
the negative disability and cohort size for boys/men is 40–100%
larger than girls/women.
Dinkelman 2015
Nicaragua Hurricane Mitch, 1998 Negative impacts on weight-for-height z-scores are similar for
boys and girls; boys seem to be relatively worse off in terms of the
impact of the shock.
Baez et al. 2007
Bangladesh Tornado, 2005 Tornado exposure has few signicant impacts on female infants.
Vitamin A supplements dampen the health impacts of in utero
exposure to tornados among boys; girls are largely unaffected by
the tornado in control and treatment localities.
Gunnsteinsson
et al. 2019
Japan Cold wave Stunting effects of prenatal cold wave exposure only found in
boys, but postnatally, cold wave exposure seems to only affect
girls.
Ogasawara and
Yumitori 2019
India Droughts In-utero exposure to droughts negatively inuences health and
child development; effects appear stronger for boys, low-caste
children, and those exposed in the rst trimester of pregnancy.
Kumar, Molitor,
and Vollmer 2014
WOMEN’S HEALTH
Indonesia,
Yogyakarta
Tsunami, 2006 One year on from the tsunami, participants of a study of 450
married women had changed their contraceptive, with injections
and implants decreasing and pills increasing. Among those having
diculty accessing contraceptives, there was higher prevalence
of unplanned pregnancy.
Hapsari et al.
2009
Haiti Earthquake, 2010 Using geographic variation in earthquake destructiveness,
difference-in-difference analysis shows that heightened
earthquake intensity reduced the use of injections (the most
widely used contraceptive in Haiti) and increased pregnancy and
unwanted pregnancy rates.
Behrman and
Weitzman 2016
United States,
Texas
Hurricane Ike, 2008 The hurricane hampered access to contraception. Overall, 13% of
women reported diculties accessing contraception. The effect
was larger among black women.
Leyser-Whalen,
Rahman, and
Berenson 2011
24 • Gender Dimensions of Disaster Risk and Resilience
1.2 • Education and child labor
The impacts of natural disasters on school enrollment affect boys and girls differently. Natural
disasters can force parents to withdraw their children from school because they cannot pay
tuition or need additional support at home or extra labor income (Björkman-Nyqvist 2013; Cas
et al. 2014; Takasaki 2017). School enrollment can also increase after a natural disaster, as the
opportunity costs of education change (de Janvry et al. 2006; Gitter and Barham 2009). Whether
girls or boys are withdrawn school and/or engage in child labor depends on parents’ needs and
the value they place on their children’s education.
When families need additional income and labor, boys tend to be affected more than girls. For
example, Takasaki (2017) nds that boys (but not girls) in Fijian families affected by Cyclone
Amy in 2003 were more likely to participate in farm work and had lower school enrollment
rates than those in families that were not affected. The author noted that boys with no older
brothers and a more educated father were particularly vulnerable. This is likely because, with
his higher level of education and presumably better paid employment, the father’s opportunity
cost of missing work to farm is high. Similarly, Cas et al. (2014) nd that boys who lost both
parents in the 2004 tsunami in Sumatra at the age of 15–17 completed on average 1.7 fewer
years of schooling and were 34 percent more likely to be working work ve years after the
event, compared to their peers who did not lose a parent. Girls were also less likely to be in
school, but in contrast their male peers, there is no evidence that those who lost one or both
parents dropped out sooner than those whose parents survived. Also in contrast to boys, girls
who lost both parents were 26 percent less likely to participate in the workforce ve years on
than their peers whose parents survived. This is most likely due to marriage, as girls were 62
percent more likely to be married ve years after the disaster (see Section 1.4.1).
When there is less value in work—due to, say, a drought—the opposite effect can be observed.
For example, a drought in Nicaragua in 2001–02 led to a 23 percent increase in school enrollment
among boys from families with less than one hectare, as it lowered the value of farm labor and
hence the opportunity cost of education (Gitter and Barham 2009). Drought also had a negative
effect on child labor in Mexico for both girls and boys, although school enrollment did not rise
(de Janvry et al. 2006).
When parents cannot afford tuition or need additional support at home, girls tend to be more
affected. Björkman-Nyqvist (2013) nds that a 15 percent decrease in rainfall in Uganda
resulted in a 5 percent decrease in girls’ enrollment in the highest grade of elementary school.
No effect was found for boys or younger girls. The author suggests that, since the absence of a
pension system means that older family members often rely on their children’s income, and
girls are expected to marry and leave the household, it is reasonable to assume that parents
will value boys’ education more since they will make a bigger contribution to their household
as adults. Girls also often help around the house—preparing food, fetching water, and washing
clothes—and this work becomes more burdensome in times of drought. When primary tuition
fees were abolished in Uganda, enrollment increased, and the effect was stronger for girls
than boys. But even when school was free, a decrease in rainfall was associated with lower test
scores for girls (and a drop in enrollment among the poorest girls). Boys, on the other hand,
were unaffected, indicating that parents continue to prioritize their education. In Mexico, de
Janvry et al. (2006) nd that girls’ school enrollment decreased by 5 percent after their locality
was affected by earthquake, hurricane, ood, or plague (not drought). They nd no effect for
boys. The likelihood of engaging in child labor also increased for both girls and boys after a
natural disaster.
Disaster Impacts • 25
Table 1.3 • Summary of literature on the gender gap in educational outcomes in the context of
natural disasters
Country Disaster/Year Findings Reference
Indonesia,
Sumatra
Tsunami, 2004 For older adolescent boys and girls (aged 15–17 years), losing both
parents in the tsunami decreased school enrollment by 40 and
55% respectively in the long term (ve years after the event). It
also increased the probability of boys being in the workforce by
34%, but decreased the probability for girls by 26%.
Cas et al. 2014
Fi Cyclone Amy, 2003 Among cyclone victims with housing damage, boys (not girls)
contribute to farming activities, leading to signicantly lower
school enrollment among boys. Housing aid mitigates school
dropouts among boys but does not inuence their labor use. Boys
with no elder brothers and a more educated father are particularly
vulnerable in their progression to higher school levels.
Takasaki 2017
Nicaragua Droughts, 2001–02 Droughts increase school enrollment among boys by 23% in
households with less than one hectare of land, because the
opportunity costs of school decrease.
Gitter and
Barham 2009
Uganda Droughts, 1979–2003 A 15% decrease in rainfall results in a 5% decrease in the highest
grade of female elementary school enrollment. No effect is found
on the enrollment of boys and younger girls. When schooling is
free of charge, a negative income shock has an adverse effect on
girls’ test scores, while boys are unaffected.
Björkman-
Nyqvist 2013
Mexico Various natural
disasters, 1997–2000
In places affected by natural disaster in the previous six months,
the likelihood of girls being in school decreases by 5%. No such
effect is found for boys. Most natural disasters increase child
labor for boys (6.7%) and girls (4%). Drought decreases child labor
for both boys and girls.
de Janvry et al.
2006
1.3 • Economic outcomes
Natural disasters can impact an individual’s economic conditions directly—for example, by
wiping out a harvest or damaging or destroying assets used to generate income—and indirectly,
by causing price changes, disrupting infrastructure, affecting suppliers, and so on. Disasters
have different effects on different sectors, depending on their exposure (outside/inside activities,
proximity to high-risk areas) and vulnerability (dependency on infrastructure, importance of
weather, sensibility to external shocks) to impacts of natural hazards.
These factors are important in understanding disaster impact at the individual, household, and
societal level. Gender discrimination and social norms, in society and the household, continue
to inuence labor market participation, asset accumulation, ownership and consumption
outcomes, and consequently, how disasters impact the economy. This subsection focuses on
how gender-based differences in the exposure and vulnerability of livelihoods and assets to
natural hazards and intrahousehold dynamics result in different postdisaster consumption
outcomes for men and women.
1.3.1 • Livelihoods
Heavily reliant on weather, climate, and water to prosper, agriculture is one of the most
vulnerable sectors to natural disasters. Twenty-three percent of all damages and losses caused
by natural disasters between 2006 and 2016 were in agriculture (crops, livestock, aquaculture
and sheries and forestry sectors) (FAO 2017). Globally, a larger share of employed men (30
percent) work in agriculture than women (25 percent) (ILO 2016). But in low- to middle-income
countries and most regions,
4
agriculture is the most important economic sector for female
employment and employs a larger share of employed women than men (ILO 2016).
Women farmers tend to be smaller-scale and use fewer inputs and technologies than men,
making them more vulnerable to the impacts of drought (Croppenstedt, Goldstein, and Rosas
26 • Gender Dimensions of Disaster Risk and Resilience
2013; FAO, IFAD and ILO 2010). Their lower productivity results, on average, in a 20–30
percent yield gap between men and women (FAO 2011). Female farmers dedicate more hours
to unpaid family work, have lower access to off-farm labor and, when they do get laboring
work, are paid less than men (FAO 2011; ILO 2016). For example, the average daily wage for
female farm workers in India is 74 percent the male wage (National Sample Survey 2007,
calculated in Mahajan 2017). Mahajan (2017) also nds that in rice-growing areas, low rainfall
shocks are associated with a decrease in female farm workers’ wages, but do not affect men’s
wages, indicating that demand for female farm labor is more sensitive to rainfall variability.
With lower productivity, smaller margins, and fewer options to shift income, female farmers
face a higher risk of falling into poverty and/or become more dependent on their husband at
times of natural disaster. This, in turn, lowers female bargaining power within the household
(Doss 2013).
Women are more likely to face unemployment, re-enter the labor market or shift to self-
employment after a disaster. Acevedo (2014) analyzes the extent to which labor supply changes
in response to extreme weather events. Using individual labor supply data in the Colombian
Caribbean, the study nds that the probability of unemployment increases by 7 percent among
women living in a municipality that has experienced at least one ood. This was 3 percent
higher than men. Similarly, after Hurricane Katrina, women were substantially less likely than
men to keep their pre-hurricane employment or a job of similar status (Zottarelli 2008). Several
other studies, although based on anecdotal evidence and indirect inferences, state that women
had greater employment losses after Hurricane Mitch, which hit several Central American
countries (Bradshaw 2004; Enarson 2000); they were also slower to re-enter the waged labor
market (Delaney and Shrader 2000).
These diculties could be a result of an increase in domestic duties after a disaster, which
tends to affect women more than men. For example, after a 2018 ood in Dar es Salaam, it was
observed that 60 percent of those who reported missing work due to the ood were women;
and on average, women stayed home 17 days, while men stayed home 15.5 (Erman et al. 2019).
Women tend to take on more responsibility for managing postdisaster needs than men—for
example, cleaning up after a ood and taking care of children who cannot go to school. A
similar result is found in El Salvador, where Halliday (2012) nds that women’s domestic labor
increased after the 2001 earthquake, while their income-generating work in livestock and out-
migration decreased. This effect was not found for men. For more on the role of labor in the
capacity to cope with a disaster, see Section 2.2.
Postdisaster occupation segregation also plays a role in labor market outcomes, as it is easier
for men to nd work in postdisaster construction and rehabilitation. Delaney and Shrader
(2000) note that women in Honduras’ agro-processing industry had yet to return to their jobs
in the aftermath of Hurricane Mitch, whereas men quickly found work in construction and
rehabilitation activities. Similar effects were observed in the United States, where women’s
earnings in New Orleans were 7 percent lower in the year following Hurricane Katrina, while
men’s earnings were up 23 percent, primarily from working in postdisaster construction and
sales (Peek and Fothergill 2008).
1.3.2 • Assets
Women often own a smaller share of total household assets and, as a result, lose less due to
disasters than men in absolute terms. However, when women lose the few assets they own, the
welfare consequences are often more severe than they are for men or when assets are jointly
held. Literature and data on land ownership in developing countries indicate that women are
less likely to own land than men; and when they do, they own less land (Deere and Doss 2006).
5
Disaster Impacts • 27
However, due to a lack of sex-disaggregated data on physical asset ownership, there is much
less evidence when it comes to who owns what. This data gap is also reected in the lack of
information on gendered patterns in disaster damage and loss data (see Section 3).
Individual studies shed some light on women’s share of ownership of household wealth.
Married women in Ecuador own 44 percent of household assets (including land); in Ghana,
they own 19 percent, and in Karnataka, India, 9 percent (Deere et al. 2013). When considering
movable assets only, married women in Uganda own 10 percent, and in Bangladesh, around 8
percent (Quisumbing, Kumar, and Behrman 2018).
The most common form of informal savings for poor women are small, high-value items
that they can sell for cash in an emergency (Vonderlack and Schreiner 2002). For example,
Antonopoulos and Floro (2005) nd that women typically hold tangible rather than nancial
assets, while men tend to hold nancial and transport assets. Others note that gold and jewelry
are common forms of saving among women in India, Pakistan, and Indonesia (Frankenberg,
Thomas, and Smith 2003; Goedecke et al. 2018; Zulqar 2017). In Bangladesh and Uganda,
women hold a larger share of their assets in jewelry and livestock, whereas men own more land
and property (Quisumbing, Kumar, and Behrman 2018). In Ghana, printed fabrics are high-
value traded items, which women can sell in case of emergency (Doss et al. 2018).
Holding a large share of total assets in tangible form makes women more exposed and more
vulnerable to natural hazards. A detailed household survey in Dar es Salaam found that asset
losses—including household appliances, other electronics, clothes, and furniture—made up
77 percent of total ood damage, surpassing the value of housing repairs (Erman et al. 2019).
However, holding their wealth in this form also has advantages. Women can use small, tradable
assets to smooth consumption when affected by a disaster (Frankenberg, Thomas, and Smith
2003). In the absence of access to nancial accounts, they also give women more control over
their assets, and are an alternative to holding cash at home. When women do save cash, they
tend to hide it to retain control over it. Famously, when the Indian government demonetized
bank notes of certain values in 2016, many women were compelled to bring out their hidden
cash to exchange in the banks, forcing them to disclose their savings to their husbands and
other family members (Syngle 2017; Nikore 2016; Doshi 2016). Protecting women’s assets from
the impacts of disasters would require closing the gender gap in access to nancial services and
improving access to other safe storage methods to help them maintain control over their assets
(Johnson 2004; Vonderlack and Schreiner 2002).
Female-headed households are often overrepresented among populations that are highly
exposed to natural hazards and/or in fragile structure, making them more vulnerable to disaster
impacts. Among those made homeless by Hurricane Mitch in Nicaragua and Honduras, 40
and 50 percent respectively were female-headed households. This is signicantly higher than
the national average of female-headed households, which is 24 and 20 percent respectively
(Bernard 2010). Erman et al. (2019) also nd that female-headed households are more likely
to be exposed to ooding in Dar es Salaam, even when controlling for poverty. Wiest (1998)
documents that there are nearly three times as many female-headed households in the chars
(riverine islands) and embankment zones of Bangladesh’s regular ooded zones of Kaziput,
Chilmari and Bhola than in non-eroded zones. Of these women, 63 percent have husbands who
work mostly elsewhere, while the rest are widowed or single. Since female-headed households
often face constraints such as having a single income or a larger number of dependents, it
is likely that their overrepresentation in high-risk areas is driven primarily by nancial
constraints. More insecure tenure arrangements among women can also play a role (Erman et
al. 2019). Areas exposed to ood risk in cities are often the last pieces of land to be exploited,
28 • Gender Dimensions of Disaster Risk and Resilience
and housing there tends to be more informal. They are often cheaper while still being close to
job opportunities in the city. Households unable to settle in other areas move here to access
housing and jobs at the expense of frequent ood exposure (Erman et al. 2020; Hallegatte et al.
2017). Once settled there, insecure tenure can make it more dicult to leave (see Section 2.2).
1.3.3 • Consumption
Disasters change household consumption patterns, and women and girls are rst to report
skipping meals or going hungry when there is a food shortage as often happens in the aftermath
of a natural disaster (Alston 2015; David and Enarson 2012; Keshavarz, Karami and Vanclay
2013; Segnestam 2009; Shoji 2010). Using individual data, Shoji (2010) nds that females in
Bangladesh are 1.6 times more likely to sacrice meals after a disaster. This trend results in
higher infant mortality and higher postdisaster underweight and stunting rates among girls
than boys (Datar et al. 2013), as already discussed in Section 1.1.3. Households with an educated
head and more physical assets are less likely to reduce meal frequency due to disasters and the
marginal effect is larger for female household members than males (Shoji 2010).
There is nascent evidence that postdisaster expenditure on women’s goods is signicantly
reduced. After Cyclone Phailin in Orisha, India in 2013, there were sizeable decreases in total
postcyclone expenditure in affected households, primarily drawn by lower per capita food
expenditure and no signicant changes in health or education expenditures. One of the largest
decreases in household expenditure categories was in women’s goods, which includes clothing,
shoes, hygiene products, and toiletries (Christian et al. 2019). The study suggests that, since
the worst-hit households spend less on women’s goods but more on social expenditures such
community festivals (without any signicant decrease in health or education expenditures),
women buffer their households from negative consumption shocks. The effect could also be
driven by limited decision-making power over the use of household resources.
Table 1.4 • Summary of literature on the gender gap in economic outcomes in the context of
natural disasters
Country Disaster/Year Findings Reference
LIVELIHOODS
India Rainfall shocks,
1993–2007
A district-level panel dataset covering 14 major states including
data on individual wages and rainfall shocks shows that a single-
unit increase in a rainfall shock in rainfed rice-growing areas
corresponds to a 10% increase of female-to-male wage ratio. This
is driven by a greater increase in demand for female labor.
Mahajan 2017
Colombia,
Caribbean coast
Rainfall shocks,
2001–2010
Individual labor supply data of 800,000 adults and children shows
that women in a municipality that experienced at least one ood
are 3 percentage points more likely to be unemployed than men.
Participation of children aged 12–17 in the labor force increased
1.4 percentage points for boys and 4.7 percentage points for girls
in response to oods.
Acevedo 2014
United States Hurricane Katrina,
2005
A two-round survey with 1,369 respondents (in 2005 and 2006)
found that, among those affected by the hurricane, women were
substantially less likely than men to maintain their pre-hurricane
employment.
Zottarelli 2008
Tanzania,
Dar es Salaam
Flood, 2018 Data from a representative sample shows that women were more
likely than men to miss work after the oods: 60% of those who
reported missing work were women. They also tended to stay
home for slightly longer than men (17 days compared to 15.5).
Erman et al. 2019
El Salvador Earthquake, 2001 Three waves of panel data between 1988 and 2002 show that
women spent more time on domestic duties after the earthquake.
A 1% increase in earthquake damage is associated with 1.54 hours’
increase in domestic labor, decreasing the time women spent on
income-generating work in livestock or out-migration. For men,
adverse agricultural outcomes increased migration and hours
spent in the eld.
Halliday 2012
Disaster Impacts • 29
ASSETS
Uganda and
Bangladesh
Different shocks,
including oods and
droughts, 2007–2010
Panel datasets show that, in Bangladesh, oods and droughts
have negligible impact on land and asset holdings. In Uganda,
oods have a positive effect on married men’s land holdings, and
droughts have signicant negative impact on married women’s
non-land assets, while their husbands’ assets are unaffected.
Quisumbing,
Kumar, and
Behrman 2018
CONSUMPTION
Bangladesh Floods, 2004 Data from 326 households show that, without rescheduling
payments to cope with negative income shocks of oods,
households are, on average, 5.1% more likely to skip meals.
Women and girls are 1.6 times more likely to do so than men and
boys.
Shoji 2010
India Cyclone, 2013 Two independent but overlapping sources of variation—exposure
to a cyclone and the rollout of a rural livelihoods intervention—
show that the storm led to a reduction in overall household
expenditure, with the largest reduction in women’s goods.
Christian et al.
2019
1.4 • Voice and agency
Women’s lack of voice and agency in decision making can drive gender gaps in outcomes.
Specic expressions of women’s agency include freedom from gender-based violence, the ability
to decide when to marry and the ability to have a voice in society (World Bank 2015b). This
section explores how women’s voice and agency manifest themselves in postdisaster situations,
focusing on child marriage and gender-based violence. Box 1.1 looks at women’s voice in
society, focusing on women as agents of change in the context of disaster risk management.
1.4.1 • Child marriage
Losing a parent in a disaster increases the prevalence of child marriage for girls and decreases it
for boys. Cas et al. (2014) show that, among children who lost both parents after the 2004 tsunami
in Sumatra, boys were 7 percent less likely to be married than boys whose parents survived.
Girls, on the other hand, were 62 percent more likely to be married. The death of both parents
leaves children with fewer psychosocial and economic resources, which pushes girls into early
marriage. For boys, it tends to delay marriage as they work to support the rest of the family.
The economic role of marriage and traditional cultural norms determines the effect of shocks
on the prevalence of child marriage among girls. In sub-Saharan Africa and India, where
marriage is accompanied by substantial monetary or in-kind transfers, local economic shocks
have opposite effects on the marriage behavior of a sample of 400,000 women. Droughts, which
reduce annual crop yields by 10 to 15 percent, increase female child marriage by 3 percent in
sub-Saharan Africa where bride price is paid by the groom’s family, and reduce female child
marriage by 4 percent in India, where dowry is paid by the bride’s family (Corno, Hildebrandt,
and Voena 2017).
Research on disasters and marriage behavior nd that age of marriage decreases due to disasters.
Khanna and Kochhar (2020) show that a ooding event in 2008 in Bihar, India, decreased the
age of marriage and that the effect was more pronounced among boys (10 months) than girls
(4.5 months). The authors suggest that the ood made families decide to marry boys earlier to
smooth consumption with the dowry, which also affected the age of marriage for girls. The study
also shows that marrying younger affects the status of girls and women, as married women are
less likely to work, have their own money to spend or own a cellphone. They also nd that these
effects are more pronounced among Hindus—for whom dowry in marriage is the norm—and
the landless, who are more credit-constrained. Similarly, Das and Dasgupta (2020) nd that the
female age of marriage decreased as a result of the 2001 Gujarat earthquake and identify the
dowry as the driving mechanism.
BOX 1.1
Women as agents of change
Addressing gender inequalities by enhancing
women’s participation in decision making is
crucial for building communities’ resilience
to natural disasters. Although it often goes
unnoticed, evidence demonstrates that women
have an active role in disaster preparedness,
response, and recovery efforts (UNISDR 2015).
Acknowledging women’s contributing role, the
government of Vietnam has issued a decree
that gives the Women’s Union an ocial space
in disaster-related decision-making bodies
(UN Women 2017). A local government in the
Philippines has set aside budget for women
to conduct community consultations and
feed into community-level development plans
(Tanner, Markek, and Komuhangi 2018). And
in Bangladesh, the Comprehensive Disaster
Management Plan thoroughly addresses
gender concerns, stipulating that women’s
representatives are to be included in the
people’s councils involved in preparing disaster
action plans, discussion with women’s groups
when preparing these plans is obligatory, and
council members must be provided with gender
sensitivity trainings (Ikeda 2009).
Because women have a better understanding
of what women need, their involvement and
leadership in disaster decision making is
crucial (Tanner, Markek, and Komuhangi 2018).
In Bangladesh, engaging women in community
mobilization efforts to address cultural reasons for
women’s reluctance to access shelters has proven
ecient. This may be because they nd it easier
to identify women’s needs, or because women are
more likely to trust other women in some contexts
(World Bank 2011). Not involving women in such
processes can have negative consequences, as
seen in the aftermath of the Great East Japan
Earthquake, where the lack of female involvement
in designing and operating evaluation sites led
to a disregard of their needs and concerns or
discouragement from speaking about them. The
government has since amended its Basic Disaster
Management Plan to ensure women participate
in designing and operating evacuation sites
and temporary housing, to ensure these meet
the needs of women and families with children
(Government of Japan 2014).
Female participation in postdisaster and
recovery phases can have transformative effects
on gender dynamics. In a longitudinal study of
a small tsunami-affected coastal community
in Chile, Moreno and Shaw (2018) demonstrate
how women’s participation in postdisaster work,
such as community kitchens, helped strengthen
female leadership and made them active agents
of change in their communities. By diffusing
public and private spaces, the disaster created
an opportunity for women to move from low to
high community involvement, a situation that
still prevailed seven years after the disaster.
In a qualitative study, Ikeda (2009) shows that
women’s involvement in community-based
disaster risk management in Bangladesh is
transforming cultural behaviors, leading to
wider support among both men and women for
addressing specic women’s needs in disaster
risk management.
The Sendai Framework, adopted in the
Third United Nations World Conference on
Disaster Risk Reduction in 2015, recognizes
the signicant role women play in disaster
preparedness, response, and recovery (UN
2015). The framework emphasizes the need for
enhancing women’s leadership in promoting
universally accessible response, recovery,
rehabilitation, and reconstruction approaches.
30 • Gender Dimensions of Disaster Risk and Resilience
Disaster Impacts • 31
1.4.2 • Gender-based violence
Gender-based violence, a manifestation of systematic inequality between men and women, is
exacerbated during a time of emergency (Abiona and Foureaux Koppensteiner 2018; Bradshaw
and Fordham 2013; Fisher 2010; Weitzman and Behrman 2016). Violence tends to increase in
the immediate aftermath of a disaster, and women and children are at greater risk of physical
and sexual violence in emergency settings (Gennari et al. 2015). Owing to a lack of adequate
data on the incidence of pre-disaster event violence, it is dicult to measure the scale-up of
violence (Bradshaw and Fordham 2013). However, qualitative evidence reveals an increase
in the risk of both stranger-perpetrated sexual violence and intimate partner violence
6
after
natural disasters in developed and developing country settings.
In refugee and displacement camps, where protection and privacy are often inadequately
addressed, risks for women and girls are higher. Horton (2012) explores the vulnerability of
women and girls in internally displaced persons camps in Haiti after the 2010 earthquake.
Although there are no reliable data on prevalence, crowded conditions and a lack of security
contributed to an increase in multiple forms of gender-based violence.
Examining overall levels of violence and the types of violence after the 2004 Indian Ocean
tsunami in Sri Lanka, Fisher (2010) nds that girls and women were subjected to sexual violence
and other forms of physical abuse by strangers from the onset of the emergency. However, there
is also growing recognition that intimate partner violence is a crucial concern in emergency
settings (IASC 2015) and it is often considered the most prevalent form of postdisaster violence
against women. Understanding and recognizing reasons behind this postdisaster increase in
intimate partner violence is important for program design, particularly to ensure that resources
targeted for women do not lead to more violence.
In their study of 2010 Haiti earthquake, Weitzman and Behrman (2016) nd that women living
in the most devastated areas were more likely to experience physical and sexual intimate
partner violence for up to two years after the disaster. According to the study, the consequences
of the impact of the earthquake affected men’s controlling behavior, which is linked to the
risk of intimate partner violence. In Tanzania, droughts lead to a considerable increase in
intimate partner violence (one standard deviation corresponds to 13.1 percent increase), an
effect that is more pronounced among poorer households, those with divorced partners, those
who rely solely on agriculture, or where females are less empowered
7
(Abiona and Foureaux
Koppensteiner 2018). In the United States, several studies have consistently found increases in
prevalence of intimate partner violence after Hurricane Katrina (Anastario, Lawry, and Shehab
2009; Harville et al. 2011; Schumacher et al. 2010). This includes psychological victimization
(35 percent increase for women, 17 percent for men) and physical victimization (98 percent
increase for women) (Schumacher et al. 2010).
Sexual exploitation of women and girls also increases after a disaster, with women often forced
to provide sexual favors in return for food and benets. Delaney and Shrader (2000) observed
reports of an increased level of sexual violence and coerced prostitution after Hurricane Mitch,
particularly among adolescent girls in temporary shelters in rural areas. Some shelters even
hired security guards to reduce this type of violence. This is in line with observations from
a Haitian women’s organization that, after the 2020 earthquake, women and girls exchanged
sexual acts for food and benets, including coupons, access to direct aid distributions, cash-for-
work programs, money, or even a single meal (MADRE 2012).
In the context of silencing and stigmatization, many survivors of gender-based violence cannot
seek support or access adequate services. Often, they do not speak out over fear of being
32 • Gender Dimensions of Disaster Risk and Resilience
blamed; particularly in societies that highly value the “purity” of women (Felten-Biermann
2006). In Japan, social pressures—including the praise of stoicism—encouraged survivors and
women’s support groups to remain silent on cases of sexual violence in the aftermath of the 1997
Hanshin Awaji earthquake (Saito 2012). Similarly, following the 2009 Black Saturday Bushre
in Australia, which caused the subsequent relocation of 7,000 people, women at increased risk
of intimate partner violence faced pressure to deny or forgive violence from family members
and peers, and many who spoke of seeking help were ignored, blamed, and silenced (Parkinson
and Zara 2013). Fisher (2010) and Bradshaw and Fordham (2013) point out that postdisaster
gender-based violence is not the product of an extraordinary reaction to a disaster situation,
and should be viewed and understood in context, alongside pre-existing violence.
Table 1.5 • Summary of literature on voice and agency outcomes in the context of natural disasters
Country Disaster/Year Findings Reference
CHILD MARRIAGE
Indonesia,
Sumatra
Tsunami, 2004 Five years after the disaster, young women who had lost their
parents as adolescents in the tsunami were 62% more likely to be
married than their peers who did not lose a parent. Young men of
the same age who had lost their parents in the tsunami were 7%
less likely to be married than their peers who did not lose a parent.
Cas et al. 2014
Sub-Saharan
Africa and India
Rainfall shocks
(droughts), 1950–2010
A sample of 400,000 women is used to study marriage behaviors
in sub-Saharan Africa and India. In sub-Saharan Africa, where
the groom’s family pays a bride price, droughts increase child
marriage by 3%; in India, where the bride’s family pays a dowry,
droughts reduce it by 4 %.
Corno,
Hildebrandt, and
Voena 2017
India,
Bihar
Riverine ooding,
2008
The 2008 oods of the Kosi River reduced the age at marriage for
men by 10 months, and for women, by 4.5 months. After the ood,
married women were 8.6% less likely to work, 8.9% less likely to
have their own money, and 8.6% less likely to own a cellphone, so
marrying at a younger age reduced their status in the household.
Khanna and
Kochhar 2020
India,
Gujarat
Earthquake, 2001 Using a sample of 2,189 women and a difference-in-differences
strategy, the authors nd that the earthquake resulted in women
marrying at a younger age, and that they were less likely to marry
within their own village. They also nd that women were less likely
to marry a man with a higher level of education than their own and
more likely to marry into a poorer household.
Das and
Dasgupta 2020
GENDER-BASED VIOLENCE
Tanzania Rainfall shocks
(droughts), July
2007–June 2008
Droughts led to a considerable increase of domestic violence
Tanzanian households—for example, a single standard deviation
decrease in rainfall from the long-term mean increased the
incidence of domestic violence by about 13% from the baseline.
Violence was targeted towards wives, only present when both
spouses worked in the agricultural sector, and absent in female-
headed households.
Abiona and
Foureaux
Koppensteiner
2018
Haiti Earthquake, 2010 Exposure to earthquake devastation increased the probability
of both physical and sexual intimate partner violence one to two
years after the disaster.
Weitzman and
Behrman 2016
United States Hurricane Katrina,
2005
Among women, the crude rate of daily new cases of gender-based
violence increased from 4.6 per 100,000 before the disaster to
16.3 per 100,000 in 2006, remaining elevated at 10.1 per 100,000
in 2007.
Anastario,
Lawry, and
Shehab 2009
United States Hurricane Katrina,
2005
Reports of physical victimization of women increased from 4 to
8% after Hurricane Katrina but were unchanged for men.
Schumacher et
al. 2010
Central America Hurricane Mitch, 1998 Women exhibited common signs of depression, such as sleep
disorders and headaches, but were able to maintain their usual
responsibilities. Information about men, on the other hand,
indicates a manic or violent reaction to psychological distress,
manifested through dysfunctional coping mechanisms such as
alcoholism, gambling, and violent behavior.
Delaney and
Shrader 2000
Indonesia
and Sri Lanka
Tsunami, 2004 Instances were reported of men offering tsunami-affected
women money or goods for sex or engaging in relationships under
a false pretense that marriage would follow.
Fisher 2010
Disaster Impacts • 33
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Endnotes
1. They measure socioeconomic status as a combination of economic and social rights using Cingranelli and Richard’s
(2010) Human Rights Database. Economic rights include equality in pay, hiring and promotion; free choice of
profession without having to obtain permission; job security; and the right to work in dangerous occupations such
as the military or police. Social rights include equal inheritance; the right to own, manage, and retain property;
participation in social, cultural, and community activities; and the right to education.
2. Although studies have identied gender gaps in swimming ability in some countries, the link between ability to swim
and mortality during disasters is not clear cut (Sellars 2016). Presumably, for certain types of high-intensity disaster,
such as tsunamis, the ability to swim or climb tree would not make a difference.
3. EM-DAT, The International Disaster Database. https://www.emdat.be/database.
4. Africa, North Africa, Arab States, Southeastern Asia and the Pacic, Southern Asia, Eastern Europe, and Central Asia.
5. Also, FAO, Gender and Land Rights Database. http://www.fao.org/gender-landrights-database/en/.
6. Intimate partner violence refers to behavior within an intimate relationship that causes physical, sexual, or
psychological harm, including acts of physical aggression, sexual coercion, psychological abuse and controlling
behaviors (WHO denition, in Krug et al. 2002).
7. Proxying female empowerment by inheritance policy at husband’s death, the study nds that domestic violence
incidence decreases when the prevailing inheritance policy allocates rights to the spouse and children at the time of
the husband’s death.
38 • Gender Dimensions of Disaster Risk and Resilience
SECTION 2
Resilience: preparedness
and coping capacity
Resilience—the capacity to withstand and recover from a shock—requires disaster preparedness,
response, and recovery. The level of disaster preparedness is impacted by risk perception,
knowledge about how to prepare, actual preparedness action, and access to early warnings.
Disaster recovery can be driven by several factors, including access to coping mechanisms,
such as savings and other assets, credit, remittances, and social protection, which can help
households recover. Sources of livelihood, availability of alternative labor or income options,
and the ability to migrate can also affect households’ recovery and adaptation. And in many of
these factors that affect resilience, gender plays an important role (Ahmad 2012).
Their role as caregivers, the lack of available resources, discrimination in the labor market,
and specic cultural restrictions mean that women face particular challenges when recovering
from disasters (UNISDR, UNDP, and IUCN 2009). Intrahousehold nancial power dynamics and
barriers to accessing government support and other formal entities, such as banks, may prevent
women from accessing and controlling household resources. Section 1 explored how the gender
dynamics of exposure and vulnerability to natural hazards tend to result in women being hit
harder when a disaster happens. The focus of this section is how gender affects resilience, from
preparedness levels to the ability to recover.
2.1 • Disaster preparedness: risk perception, preparedness
actions and early warnings
Gender can contribute to the factors that determine disaster preparedness. These include
socioeconomic status, risk perception, education, access to information and media, and previous
disaster experience (Wachinger et al. 2013).
Studies on ood risk in several developed countries nd that, when they face similar exposure
levels, women’s perception of the risks of oods tend to be higher than men’s (Finucane et al.
2000; Kellens et al. 2011; Miceli, Sotgiu and Settanni 2008). In Taiwan and Romania, for example,
women tend to fear and worry more about the risk of earthquakes than men (Kung and Chen
2012; Armaş and Avram 2008). In contrast, Bradford et al. (2012) nds no clear relationship
along gender lines in levels of concern over ood risk in six European countries.
Hanaoka et al. (2018) suggest that risk perception could be shaped by people’s emotional response
to a previous experience with a disaster, and that this could differ between women and men.
They nd that men who experienced the Great East Japan Earthquake in 2011 became more
tolerant of risk, while women’s perceptions of risk remained unaffected. If this is true, it could
help explain the trends identied in differences in risk perception between men and women.
It is not clear how gendered differences in perceived risk of natural disasters translates into
preparedness action; but responsibilities in household and social family roles seem to matter.
Resilience • 39
Evidence from Europe suggests that men are more prone to adopt protective behaviors than
women (Miceli, Sotgiu and Settanni 2008), or to consider themselves better prepared for
ooding (Bradford et al. 2012). This is the case even where women perceive a higher risk
of ooding or where no difference in risk perception was identied. The results are slightly
surprising, since it is generally believed that perceptions of risk strongly inuence the way
people adapt and prepare for shocks (Bryan et al. 2013; Erman et al. 2020). Studies suggest this
could be because men’s social role in the family context leads to them adopting more protective
behaviors than women, or because the ndings, largely based on self-reported data, reect
men’s higher condence level in their ability to take preventative actions (Miceli, Sotgiu and
Settanni 2008; Bradford et al. 2012).
It can also depend on the types of action and responsibility that men and women adopt to
prepare for a disaster. Evidence suggests that men tend to take responsibility for protecting
property and other technical aspects, while women usually focus on stocking supplies and
preparing family members (Szalay et al. 1986; Morrow and Enarson 1996). In Romania,
women were more likely than men to accumulate reserves in response to higher concerns of
earthquake risk (Armaş and Avram 2008). An analysis of credit card usage in the days leading
up to landfall of Hurricane Odile in the Mexican state of Baja California Sur in September
2014 supports this hypothesis. It suggests that women used their credit and debit cards more
extensively than men to buy food and fuel in the days before landfall (Martinez et al. 2016).
Their place of work also inuences men’s and women’s levels of disaster preparedness.
Evidence suggests that, in some contexts, male-dominated sectors provide better conditions
for strengthening disaster preparedness. For example, in Chile’s Atacama region, the male-
dominated mining industry provides emergency risk reduction training. According to one
study, this helps explain why men there tend to have higher levels of perceived preparedness
to ooding than women, who primarily work in service and commerce (Bronfman et al.
2019). Working outside or near risk areas also results in better awareness of surrounding
environments. For example, the tobacco elds on the slopes of Indonesia’s volcanoes in
Central Java are primarily managed and worked by men. As a result, these men gain more
information on volcanic hazard than women in the area, who primarily stay in the villages
(Lavigne et al. 2008).
Higher levels of education contribute to disaster preparedness and evidence suggests that
women’s education levels can have important community spillover effects. Focusing on
earthquake preparedness in Thailand’s Andaman Coast, Muttarak and Pothisiri (2013) show
that at the individual level, a higher level of formal education is associated with improved
disaster preparedness, even when controlling for household income.
1
They nd important
spillover effects of education on disaster preparedness at both household and village level.
Living in a household with two or more persons with at least secondary education or in a
village with a higher share of women who have at least secondary education both increase
disaster preparedness. A 1 percent increase in the proportion of women with at least secondary
education increases the odds of preparation by 11 percent,
2
but there is no such relation
between male education level and preparedness. However, the limited size of the sample (544)
and the simplistic way the authors dened preparedness make it dicult to extrapolate these
results out of context. According to their analysis, education is a more important determinant
than household income, previous experience with disaster and participation in evacuation
drills, which have no signicant impact on preparedness. The number of disaster information
sources people have is also positively related to the number of preparedness actions they take,
with one additional source increasing the odds of preparation by 35 percent.
40 • Gender Dimensions of Disaster Risk and Resilience
2.1.1 • Evacuation behavior
Although women are more likely to intend to evacuate and to actually evacuate in an emergency
event (Thompson, Garn and Silver 2017), non-demographic factors seem to be more
important in evacuation behavior. The literature shows clear links between risk perception,
preparedness, evacuation intention, and behavior. In a close look at the relationship between
gender and evacuation behavior in a postdisaster study in North Carolina, United States,
Bateman and Edwards (2002) nd that women are more likely to evacuate because they tend to
be disproportionately exposed to physical risks and have a heightened perception of risk.
However, when controlling for living in mobile home or risk perception, gender is no longer
signicant. In their statistical meta-analysis of hurricane evacuation studies, Huang, Lindell, and
Prater (2016) nd that, when comparing the role of gender in evacuation behavior with other
factors, ocial warnings, living in a mobile home, or peer evacuations are stronger predictors
than gender. Mean correlations with evacuation behavior are: ocial warnings (.034), mobile
home residency (0.28), peer evacuations (0.3), and having female gender (0.06).
Evidence from developing countries is scarce, but studies highlight additional factors that are
important for evacuation behavior. For example, Das (2019) and Haque (1995), investigating
evacuation in India during Cyclone Phailin in 2013 and Bangladesh during the 1991 cyclone,
indicate that poor conditions for women in cyclone shelters might be an important factor
driving female household members to stay home. They also nd that fear of looting is an
important factor keeping families from evacuating; but in this case, men tend to stay behind to
protect the property. Lavigne et al. (2008) report the same for volcano disruptions in Indonesia.
Alam and Collins (2010) and Alam and Rahman (2014) report that, while women in cyclone-
affected communities in Bangladesh might have the intention to evacuate, they depend on male
household members to do so, following the cultural the norm.
2.1.2 • Early warning
The different methods men and women use to access early warnings to natural disasters are
linked to access to technology. There has been signicant progress in establishing and improving
early warning systems in developing countries, convincingly attributable to the implementation
of the Hyogo Framework for Action.
BOX 2.1
Denition of terms
» Risk perception inuences how people respond to hazards, thereby determining
whether they turn into disasters with devastating effects on communities.
Understanding how people perceive risk in the context of natural hazards is central to
improving risk communication activities and preparedness.
» Early warning systems are the set of capacities needed to generate and
disseminate timely and meaningful warning information to enable individuals,
communities and organizations threatened by a hazard to prepare to act promptly and
appropriately, thus reducing the possibility of harm or loss.
Source: IPCC 2014.
Resilience • 41
The signicant increase in cellphone use and mobile internet services, including in more
remote areas, have also improved access to early warnings. However, across low- to middle-
income countries, women are 8 percent less likely than men to own a cellphone, and 20
percent less likely to use mobile internet services (Rowntree and Shanahan 2020). The gap is
widest in South Asia, where these gures increase to 23 and 51 percent respectively. Several
studies conrm the gender gap in accessing information and communication technologies
in developing countries (Rashid 2016; Suresh 2016; Wyche and Olson 2018) but have not
systematically explored the gap in access to early warnings and the implications for disaster
risk preparedness. There is also a knowledge gap around the way different communities and
populations receive, process, digest, and respond to early warning information, and specically
how men and women respond and react to different early warning messages.
2.2 • Coping capacity: access to nance, livelihood, migration,
and social protection
When a household is affected by a disaster, the availability of coping mechanisms that can
support them to withstand income shocks, protect or diversify their livelihoods, or adapt to
new conditions will determine their ability to recover. Coping mechanisms include access to
nance, government support, the ability to switch income sources, and adaptation through
migration. Some studies assess the effectiveness of such mechanisms at household level.
Erman et al. (2019, 2020) nd that access to both informal and formal nance sources seems to
help households in Dar es Salaam, Tanzania and Accra, Ghana recover from ooding. Looking
at the effects of drought in rural Kenya, Wineman et al. (2017) nd that credit availability
and access to different sources of income seem to reduce households’ chances of falling into
poverty after a low rainfall shock. Arouri, Nguyen, and Youssef (2015) nd similar results in
Vietnam, where greater credit availability enabled households to better cope with the effects
of natural disasters.
But while household lending can help absorb smaller shocks, it is not enough for more severe
disasters. Assessing the impact of rural oods in Malawi, McCarthy et al. (2017) nd that holding
a savings account and having access to non-agricultural income sources were mostly ineffective
in mitigating the impacts of oods. Government aid can support recovery with adaptive social
protection and other postdisaster support (see Section 4). Finally, migration can help households
recover or adapt (Coniglio and Pesce 2015; Kubik and Maurel 2016; Nawrotzki and DeWaard
2016; Berlemann and Tran 2020).
2.2.1 • Access to nance, savings, and assets
The ability to save and access a bank account helps households protect their assets from
disaster impacts, but the gender gap in banking is signicant. The use of savings is a common
coping mechanism to recovery from a disaster. In Ghana, after the devastating ood of 2015, 43
percent of affected households used savings as the primary way to cope with impacts (Erman
et al. 2020). Having access to a bank account is important to protect savings from disaster
impacts. In Dar es Salaam, households that reported they had not recovered from a recent ood
were 27 percent less likely to hold a bank account than those that had recovered (Erman et al.
2019). The authors also nd clear differences between male- and female-headed households in
Dar es Salaam, with the former being 18 percent more likely to have access to a formal bank
account and 25 percent more likely to practice saving. According to the Global Findex Database,
the gender gap in bank account ownership is 9 percent in developing countries, but there is
signicant regional variation (gure 2.1).
42 • Gender Dimensions of Disaster Risk and Resilience
Formal sources of nance—such as bank lending and insurance—can support household
recovery after a disaster. However, in many developing countries, formal sources can be dicult
to access or unavailable. For example, the Global Findex Database nds that only 8 percent of
people in sub-Saharan Africa had borrowed from a nancial institution or used a credit card in
the previous 12 months (Demirgüç-Kunt et al. 2018). Similarly, Erman et al. (2019) nd that only
4 percent of residents in ood-prone Dar es Salaam own insurance that covers disaster damage.
People are therefore more likely to rely on informal tools, such as loan sharks, community savings
groups, remittances, and small-scale lending among friends and family. These are instrumental
in recovering from income shocks, including disaster exposure. Access to informal nance was
identied as an important driver of recovery from ood exposure in Dar es Salaam and Accra
(Erman et al. 2019, 2020). For those affected by Cyclone Nargis in Myanmar, community-level
credit access was one of the most important drivers of recovery (Kostner, Han, and Pursch 2018).
However, credit only helps people recover from less severe events. When a bigger disaster
happens, community savings groups and other informal nance sources can quickly run out of
money, so they tend not to cover disaster impacts (Erman et al. 2019). The risk of debt traps and
predatory lenders can also cause families to lose their livelihood if they cannot pay back loans.
In Myanmar, the effects of Cyclone Nargis continue to be reected in elevated debt burdens for
certain livelihood groups, such as farmers, 10 years after the shock, with some farmers forced
to sell or pawn their land and shermen to sell their boats to escape debt traps (Kostner, Han,
and Pursch 2018).
Women tend to rely on informal nance more than men, which can make it more dicult
for them to access funds in case of a disaster. In the developing world, men are on average
22 percent more likely to have borrowed from a nancial institution or used a credit card
than women in the past year; in high-income countries, they are 7 percent more likely to do so
(Demirgüç-Kunt et al. 2018). Carlsson Rex and Trohanis (2012) nd that poor women frequently
face more barriers in accessing credit or insurance than poor men. They point to women’s lack
of collateral due to gender gaps in land ownership and more unstable labor arrangements, and
to their lack of access to information. Emerging as an alternative to traditional banking, the
micronance industry has helped bridge the gender gap in access to credit, by lending smaller
amounts with less stringent pre-conditions.
Figure 2.1 • In every region, men are more likely to own a formal bank account
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
East Asia and Pacific
Europe and Central Asia
Latin America and
the Caribbean
South Asia
Sub-Saharan Africa
Middle East and
North Africa
52%35%
48%
75%
58%
69%
73%
37%
64%
51%
62%
68%
Female
Male
Source: Demirgüç-Kunt et al. 2018.
Resilience • 43
In 2013, the micronance community reached 211 million clients, of whom 75 percent were
women (Reed et al. 2015). However, even within the microcredit industry, female applicants
tend to face harsher credit rationing and are granted smaller loans than men (Garikipati et al.
2017). The Global Findex Database assesses men’s and women’s capacity to obtain emergency
funds, dened as the ability to access
1
/20 of gross domestic income in local currency within a
month (Demirgüç-Kunt et al. 2018). Women’s capacity to do this is generally lower than men’s,
with some regional variation (gure 2.2). When looking at the sources of emergency funds,
gure 2.3 shows that women are much more likely to obtain funds from friends and family,
while men are more likely to earn the money. Although microlending has shown to be effective
in promoting recovery (Erman et al. 2019, 2020), overrelying on informal nance sources
may make women particularly vulnerable to disasters. In Dar es Salaam, for example, only
15 percent of savings group members report that their group covers damages from ooding
(Erman et al. 2019).
Figure 2.2 • Gender-differentiated access to emergency funds, by region (2017)
0% 10% 20% 30% 40% 50% 60% 70%
South Asia
Sub-Saharan Africa
Middle East and
North Africa
Latin America and
the Caribbean
Europe and Central Asia
East Asia and Pacific
Male
Female
53%
41%
38%
39%
33%
58%
60%
64%
50%
53%
49%
54%
Source: Demirgüç-Kunt et al. 2018.
Figure 2.3 • Gender-differentiated access to emergency funds from friends and family, by
region (2017)
0% 10% 20% 30% 40% 50% 60% 70%
South Asia
Sub-Saharan Africa
Middle East and
North Africa
Latin America and
the Caribbean
Europe and Central Asia
East Asia and Pacific
Male
Female
19%
56%
34%
68%
41%
56%
14%
45%
27%
42%
24%
40%
Source: Demirgüç-Kunt et al. 2018.
Note: Figure only shows respondents who said they can access emergency funds.
44 • Gender Dimensions of Disaster Risk and Resilience
2.2.2 • Assets
Selling off assets to cope with the impacts of disasters can help households recover, and women
tend to own assets that are conducive for consumption smoothing. As discussed in Section
1.3, women hold a larger share of their assets in movable form, including jewelry, gold, and
livestock. These are easier to sell in times of hardship than immovable assets, such as land
and dwellings (Vonderlack and Schreiner 2002). For households, selling assets to cope with
shocks is a last resort Quisumbing, Kumar, and Behrman (2018). But it is common practice,
especially among women (Frankenberg, Thomas, and Smith 2003). In Bangladesh, Quisumbing,
Kumar, and Behrman (2018) nd that, once they had experienced ooding, both wives and
husbands accumulated jewelry, indicating that shocks prompt precautionary saving. Since
assets conducive to trading make up a much larger share of women’s wealth than men’s, selling
them to cope with shocks can have severe consequences for women. The authors also nd
that in Uganda, where women’s assets make up a small share of total household wealth, wives’
assets decrease when the household is affected by drought, while husbands’ assets remain
unchanged. In some of these cases, women are not involved in the decision to sell. Doss et al.
(2018) nd that, among households responding to shocks
3
in Karnataka (India) by selling assets,
jewelry was most frequently sold. Despite jewelry often being the most important asset for
women in Karnataka, only 15 percent of these sales were made by women alone. Forty percent
were made by men, and 45 percent were made jointly. In contrast, they nd that in Ghana, most
of the assets sold in response to a shock (mostly livestock)
4
were individually owned and sold
by the respective owner.
Women tend to face more insecure tenure arrangements and land ownership, making them
less resilient to shocks. Secure tenure and land ownership makes it easier to move when a place
of residence is increasingly exposed to oods, because people can use land titles as collateral to
access cheaper nance in postdisaster situations. Globally, women own just 20 percent of land
(UNDP 2016), which is often held in the name of the male household head. In Dar es Salaam,
Tanzania, Erman et al. (2019) nd that female-headed households are overrepresented among
households with insecure tenure arrangements and among those directly affected by ooding.
2.2.3 • Livelihoods
Informal and insecure labor is associated with a lower capacity to recover from ood exposure
(Erman et al. 2019, 2020). In Accra, households that depend on casual labor as the primary
source of income tended to have lower capacity to recover from the 2015 ood. In Dar es
Salaam, breadwinners of households with low recovery capacity were more likely to be self-
employed. This could be because self-employment in certain contexts is more likely to take place
on the street or at home, which could delay postdisaster recovery if the house or neighborhood
is severely damaged. Informal employment, which is not declared in ocial social security
records, can also affect access to legal protection (minimum wage) and governmental support
(unemployment benets, health insurance). However, informal and casual labor may also be
more exible and adaptive than formal employment. This is especially so in the event of a
larger shock that disrupts formal supply chains and damages industries. For example, Akter
and Mallick (2013) nd that households dependent on ad hoc, informal labor recovered their
income quicker than other households in postcyclone Bangladesh, especially when such work
was available close to their homes.
In low- to middle-income countries, women are more likely to work in the informal economy
5
and face more insecure working arrangements than men, putting constraints on their coping
capacity (ILO 2018). Globally, women are three times more likely to be (mostly unpaid)
contributing family workers. Women in the informal sector also face under-employment: 14
percent work fewer than 20 hours a week; in Africa, the Americas, and Arab states, this reaches
Resilience • 45
20 percent (ILO 2018). As a result, women in the informal sector tend to earn less than men
and face more insecure labor arrangements, particularly in low-income countries. This means
they have lower capacity to accumulate the savings and assets that could help them cope with
disaster losses.
Differential unemployment rates between men and women in a postdisaster situation can be a
consequence of the ease or diculty of nding employment. While the evidence is anecdotal,
Delaney and Shrader (2000) nd that men and women in Nicaragua and Honduras suffered
employment losses equally in the immediate postdisaster period, but that women’s re-entry into
the waged labor market was much slower. Enarson (2000) suggests that women’s exibility to
re-enter the labor market is lower because they take on the “triple duty” of income generation,
“disaster work”—including emergency response and political organizing—and the lion’s share
of childcare and caring for the elderly.
Frequent exposure to disasters can contribute to the arbitrariness of women’s employment
arrangements, which limits resilience. Dar es Salaam is highly exposed to seasonal ooding
and residents in high-risk areas allocate signicant time to repairing, protecting, and cleaning
their houses during the rainy season. In focus group discussions with residents, Erman et al.
(2019) found that households in high-risk areas always try to ensure at least one adult is home
to protect assets, as when the water comes, it can be unexpected and quick. They note that
women tend to take on this role, perhaps driven by increased domestic obligations of women
in this context (Ilahi 2000). This limits women’s ability to undertake more protable and secure
wage labor outside the home.
Gender inequality places women in a disadvantaged socioeconomic position, which is
reinforced by exposure to natural hazards, making it even harder to sustain and respond
to future shocks. The negative feedback loop between gender inequality and disaster risk is
particularly pertinent to labor, since source of livelihood is a determinant of both severity of
disaster impact and recovery capacity, and discrimination against women in labor markets is
well documented (ILO 2020).
6
A household’s ability to increase time allocated to labor after a shock increases its capacity to
recover. Larger households are associated with better capacity to recover from ooding impacts
(Erman et al. 2019), since they have more people that can help in times of need. Consequently,
female-headed households face a disadvantage because they are generally smaller in size than
male-headed households. Women are also often constrained through their domestic duties,
leaving them with less time for paid labor when needed (Koolwal 2019).
2.2.4 • Migration
Migration can be an adaptation strategy for coping with disasters (Delaney and Shrader 2000;
Enarson 2000; Wiest 1998). In postdisaster situations, people migrate to nd better economic
opportunities and restore their livelihoods. It is often a last-resort strategy, which people use
when there is no other option.
Men are more likely than women to use migration as an adaptation strategy. Gray and
Mueller (2012b) show that severe droughts in Ethiopia increase male (usually long-distance)
mobility from 5.7 to 9.8 percent a year. The opposite effect is found among women, whose
mobility—mainly short-distance and marriage migration—is reduced from 8.3 to 5.5 percent
due to drought. Sugden et al. (2014) nd in Nepal and India that 87–99 percent of people using
migration as a permanent or seasonal adaptation strategy are male. Gentle et al. (2014) link
migration to adaptation in Nepal, nding that a rise in climate-related disasters in Lamjung
46 • Gender Dimensions of Disaster Risk and Resilience
District led to higher male out-migration, increasing the share of female-headed households
from 15 to about 26 percent between 2001 and 2011.
In some cases, however, women are more likely to migrate. Evidence from Bangladesh suggests
that moderate (5–20 percent) ood exposure at subdistrict level leads to increased short-
distance mobility within the district, primarily among women and the poor (Gray and Mueller
2012a). They nd no effect among men, households with higher expenditure levels, or for
long-distance mobility. They also nd that crop failure in the subdistrict affecting more than 5
percent of the population—often the result of drought—is associated with an increase in both
short- and long-distance mobility. This holds true for men and women of all income groups,
though the increase is larger among women. However, the authors do not state whether this is
long- and short-distance migration. Interestingly, they nd that direct household exposure to
ooding has no effect on mobility, while direct exposure to crop failure has a negative effect,
indicating that when households suffer directly, it may increase labor needs locally or remove
the resources needed to migrate.
While male out-migration can have negative effects on the women who stay behind by increasing
their responsibilities, it can also offer opportunities. In Mali, women who are left behind by
male out-migration are expected to take on more responsibilities with fewer resources (Djoudi
and Brockhaus 2011). But by transforming household power dynamics, male out-migration can
have positive implications for women’s voice and agency (Le Masson et al. 2016). In places as
diverse as Benin and Mexico, Dah-gbeto and Villamor (2016) and Radel et al. (2012) nd that
male out-migration increases women’s decision making in land use and agriculture.
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Endnotes
1. The authors measure disaster preparedness in terms of taking one or more of the following measures to prepare for
a possible earthquake or tsunami during a high-alert period: no preparation; keeping a close watch of the situation;
preparing survival kits; planning evacuation procedure and emergency plan with household members; inspecting the
house structure; and other preparations.
2. On average, 11 percent of women and 14.8 percent of men in Thailand have completed lower secondary school only;
12.4 percent of women and 15.5 percent of men have completed lower and upper secondary school (UNICEF).
3. The most-reported shock was natural disaster (67 percent); other shocks were included.
4. In Ghana, crime and accidents were the most reported shocks (38%). Natural disasters were the third most common,
at 10 percent.
5. In low-income (lower-middle) countries, 92 (85) percent of employed women and 88 (83) percent of employed men
are in informal employment.
6. Women do more hours of unpaid care work, are less likely to be engaged in paid work, earn less than men and are
more likely to be underemployed (work fewer hours).
Data Gaps • 49
SECTION 3
Data gaps in disaster risk
management
To understand the underlying gender dynamics of disaster risk and therefore design
appropriate policies, the rst step is ensuring data collection is disaggregated by sex and age.
Over the last decade, there has been signicant progress in collecting better and more sex-
and age-disaggregated data (SADD). However, large gaps still exist, especially when it comes to
the impact of natural disasters on gender. By 2014, 190 countries were collecting statistics on
women’s representation in government (up from 167 in 2005), and the number collecting data
on intimate partner violence rose from 44 to 89 in the same period. But the number of countries
reporting sex-disaggregated data on the impact of natural disasters remains low.
1
Disaster
fatalities still tend to be recorded in terms of overall numbers rather than disaggregated by sex
and age (Eklund and Tellier 2012).
Even when disaggregated data are collected, a gap remains between collection and analysis,
hindering critical decision making in humanitarian response (Benelli, Mazurana, and Walker
2012). Differences in methods, concepts and denitions used in statistics hinder comparability
across countries and time, and as most analyses linking gender to natural disasters are based on
qualitative or small-scale quantitative studies, they cannot be extrapolated to a whole society or
across countries. This section provides insight into disaster data collection practices and their
limitations and identies data gaps.
3.1 • Postdisaster data collection
The rst response to a major natural disaster is from the humanitarian sector, and the focus
is on saving lives, limiting damages and restoring order (GFDRR 2015). During this phase,
organizations and governments conduct rapid, preliminary assessments, using sector-specic
methodologies and tools, to identify immediate needs.
Building on these preliminary assessments, a postdisaster damage and needs assessment
(PDNA) often follows. Originally focused on quantifying losses and damages from natural
disasters, PDNAs have evolved into an “integrated framework for assessing disaster effects and
impacts on all sectors” that is broadly used to assess disaster impacts and determine priority
recovery interests and needs (Jeggle and Boggero 2018).
PDNA data collection relies on primary and secondary data sources and uses various collection
methods. Primary data are gathered in the project area through postdisaster surveys, focus
group and community discussions, one-on-one in-depth interviews, and so on, as well as follow-
up surveys and regular program monitoring and evaluation (Rex et al. 2012). Secondary data
sources—such as government censuses, administrative records and registries and regular
household surveys—provide a baseline on which to build primary data collection.
50 • Gender Dimensions of Disaster Risk and Resilience
3.2 • Limitations of postdisaster data collection
One major limitation of postdisaster data collection is its overreliance on data captured
at household level. Driven by time and budget constraints—and perhaps also by a lack of
knowledge—most postdisaster surveys are done at household level, asking questions only to the
household head. Postdisaster assessment also relies on secondary data on poverty, measured by
income or consumption, which does not usually consider redistribution within the household.
There may also be limitations in terms of the questions asked. Surveys tend to measure
housing damage and agricultural land loss, but often do not record smaller household losses.
This includes kitchen appliances and sewing machines, which are usually used by women, in
timesaving and income-generating activities. It is also reasonable to assume that, if owned by
women, these smaller, high-value assets make up a signicant share of their total assets. Losing
them may have signicant consequences for their welfare; so it is important to record and
better understand such losses (Bradshaw 2013; Bradshaw and Fordham 2013).
There is recognized tradeoff between the urgency to obtain information, the time burden
for respondents, and the quantity and quality of data in postdisaster surveys. The urgency to
rapidly assess disaster impacts and implement relief measures increases time pressure. PDNA
guidelines indicate that data collection should take 6–12 weeks, but in practice it is often done in
3–4 weeks (Jeggle and Boggero 2018). Shorter exercises rely more on secondary data, fewer eld
visits and less accurate and comprehensive information on social parameters and household
impacts. Financial constraints mean that postdisaster surveys are usually a one-off exercise.
Repeated postdisaster data collections, capturing long-term impact of a disaster, are a rarity. The
longitudinal 10-year postdisaster study in Myanmar after Cyclone Nargis is a clear exception
(Kostner, Han, and Pursch 2018).
Practicalities, such as a lack of trained data collection personnel—including, in some contexts,
female employees who are willing to travel and interview other women—hinder data collection
and analysis (Benelli, Mazurana, and Walker 2012). A general misunderstanding about the
scope of SADD and generational analyses might also pose a burden on SADD collection. In other
cases, it is simply not possible to access areas hit, as has been the case, for example, during the
COVID-19 pandemic. And when face-to-face surveys are replaced by phone surveys, they run
the risk of excluding the share of population without phone access. In some contexts, there
is a large gender gap in phone access and ownership. In addition, some phone survey efforts
(including the latest World Bank COVID-19 high-frequency survey) are deliberately targeted at
household heads, thereby generating biased data.
Past PDNAs reveal that data collected on social and human development are not disaggregated
and/or consistent enough for trend analysis. In some cases, baseline data are not available in
the disaster-affected area. Collecting SADD is rarely integrated within the national statistical
strategy; rather, these data tend to come from ad hoc or one-off exercises. As a result, they tend
to be out of date and inconsistent, making it dicult to monitor trends. For example, only 24
percent of available gender-specic data is from 2010 or later and only 17 percent is available
for two or more points in time (UN Women 2018). Even when national-level SADD exists, they
are usually not granular enough for analysis at a geographical level that would be meaningful
in the context, such as areas affected by disaster, which could be a mid-size city, or several
villages or municipalities.
2
While household surveys are used extensively to develop baselines and assess postdisaster
needs, they often fail to include certain populations such as homeless people, migrants or those
living in areas that are hard to reach due to conict or natural disaster. In many countries, little
information is collected on people with disabilities or from racial, ethnic, or religious minorities
Data Gaps • 51
(UN Women 2018). Countries often do not invest enough in gender statistics, do not collect data
on a frequent basis and lack the expertise or willingness to collect data on often sensitive issues,
such as sexual orientation, gender identity, indigenous status, and HIV status (UN Women 2018).
Such country-level data gaps hinder comparisons of pre- and postdisaster conditions of the
population as a whole (Eklund and Tellier 2012; Goyder et al. 2005).
References for Section 3
Benelli, P, Mazurana, D, and Walker, P. 2012. “Using Sex and Age Disaggregated Data to Improve Humanitarian
Response in Emergencies.” Gender & Development, 20(2): 219–232. https://doi.org/10.1080/13552074.2012.687219.
Bradshaw, S. 2013. Gender, Development and Disasters. https://doi.org/10.4337/9781782548232.
Bradshaw, S and Fordham, M. 2013. Women, Girls and Disasters: A Review for DFID. http://gdnonline.org/resources/
Bradshaw&Fordham2013-women-girls-disasters.pdf.
Eklund, L and Tellier, S. 2012. “Gender and International Crisis Response: Do We Have the Data, and Does It Matter?”
Disasters 36(4): 589–608. https://doi.org/10.1111/j.1467-7717.2012.01276.x.
GFDRR. 2015. Guide to Developing Disaster Recovery Frameworks. Sendai Conference Version. https://www.gfdrr.org/en/
publication/guide-developing-disaster-recovery-frameworks.
Goyder, H, Girerd-Barclay, E, Jones, A, Lefevre, J, and Larmoyer, A. 2005. Full Report of the ‘Real Time’ Evaluation of WFP’s
Response to the Indian Ocean Tsunami. World Food Programme. https://documents.wfp.org/stellent/groups/public/
documents/reports/wfp079977.pdf.
Jeggle, T and Boggero, M. 2018. Post-Disaster Needs Assessment (PDNA): Lessons from a Decade of Experience. World Bank:
Washington, DC. http://hdl.handle.net/10986/30945.
Kostner, M, Han, M, and Pursch, S. 2018. Meandering to Recovery Meandering to Recovery: Post-Nargis Social Impacts. World
Bank: Washington, DC.
Rex, H C, Trohanis, Z, Burton, C, and Stanton-Geddes, Z. 2012. Gender Informed Monitoring and Evaluation in Disaster Risk
Management. World Bank: Washington, DC.
http://hdl.handle.net/10986/26534.
UN Women. 2018. Turning Promises into Action: Gender Equality in the 2030 Agenda for Sustainable Development. Razavi,
S, Somali, C, Staab, S, and Browne, S (eds.). https://www.unwomen.org/en/digital-library/publications/2018/2/gender-
equality-in-the-2030-agenda-for-sustainable-development-2018.
Endnotes
1. United Nations. Moving Forward on Gender Statistics. https://unstats.un.org/unsd/gender/dataWW2015.html.
2. Nationally representative data tend to be on national, urban/rural, second administrative tier, and capital city levels.
52 • Gender Dimensions of Disaster Risk and Resilience
SECTION 4
Policy recommendations
Gender inequality exacerbates vulnerability to disasters, and policies that consider gender
dynamics will mitigate disaster impacts more eciently. Experts in disaster risk reduction may
ask themselves what a piece of gray infrastructure—such as a drainage canal—has to do with
gender inequality. The answer is that even seemingly gender-neutral public good investments
will be inuenced by gender dynamics, as intracommunity and intrahousehold power relations
can affect who gains access to a public good. For example, people will only benet from cyclone
shelters if they know where they are and when to use them. Gender dynamics often mean that
women lack access to technology and the networks where this kind of information is shared. It
is also important to design the shelters so both men and women want to use them. The shelters
will not be as ecient in mitigating disaster impacts if women are less likely to use them than
men and end up in harm’s way of the cyclone as a result.
This section focuses on a set of policy actions that mitigate gender-differentiated impacts
of natural disaster, either by addressing gender gaps in exposure and vulnerability or by
strengthening resilience. Table 4.1 provides an overview of policy actions that mitigate the
gendered disaster impacts discussed in this report. They are organized by main determining
factor as identied in the conceptual framework (gure I.1), and by timing within the disaster
cycle (pre, during, or postdisaster). Policies that do not depend on the disaster cycle or that
can be implemented at different stages span across all or several stages of the disaster cycle.
The policies recommended here are indicative, and do not replace the need for a local gender
gap assessment before deciding on policy action. As shown in table 4.1, most policies cannot
be considered until a local assessment has been done (indicated with a dot); others can be
considered everywhere and anytime.
1. Accessible safety measures and training
Policies that could lower mortality in disasters depend on who tends to die. When more men
die in disasters, which is the case in most high-income contexts, it tends to be because they
are overrepresented in rescue work. In such contexts, increased safety measures and training
of civil protection agencies are policy options to consider for lowering the death rate. In low-
income countries, more women tend to die in disasters than men, and socioeconomic factors
are the main contributors. To improve disaster risk management and save more people in
such contexts, governments and agencies need to assess the barriers that prevent women
from accessing and beneting from preventive and emergency response resources. They must
ensure women have access to training, receive early warnings and know what to do in case of
an emergency, and that shelters and camps are safe and responsive to women’s needs.
2. Social protection
Governments can use social protection to mitigate the human development impacts of disasters
on children, considering gender dynamics to maximize benets. Where there is a risk that parents
will prioritize boys when resources are scarce, social protection can eciently mitigate human
development impacts. Countries may consider conditional cash transfers, to ensure resources are
used in a way that benets all household members. Conditional cash transfers are generally not
linked to the disaster cycle, but can be used to scale up support in postdisaster situations. Box 4.1
offers an overview of the role of social protection in building resilience and how governments can
use it to mitigate differentiated impacts of disasters on women and men, girls and boys.
Policy Recommendations • 53
Table 4.1 • Policy actions to mitigate differentiated impacts of disasters for men and women,
boys and girls
Before disaster During disaster After disaster
EXPOSURE AND VULNERABILITY
Improve safety of civil protection agencies, with training and equipment [
l
]
Ensure shelters are safe, with working lights, women-only bathrooms and spaces,
enough space for all, and so on
Build back better, consider addressing
pre-disaster gender gaps when rebuilding
infrastructure and services [
l
]
Prevent the negative child development impacts of disasters, with conditional cash transfers [
l
]
Meet women’s health needs in rst response, shelters, and camps, with menstrual
hygiene kits, and pre-natal, pregnancy and lactating care
Promote joint ownership in housing
reconstruction programs and land
administration systems [
l
]
Mitigate sexual harassment in aid delivery by increasing female presence in aid, using
pre-determined time slots for aid pick-up to avoid overcrowding, strengthening
supervision, reporting mechanisms and accountability
Special assistance plans and programs
for women, children, elderly, people
with disabilities, and other marginalized
groups in housing reconstruction
programs [
l
]
Land and housing titles to promote women’s ownership rights [
l
]
Ensure women’s representation in civil protection, humanitarian aid, community outreach, and policy making, from community
to international levels by hiring more women (creating an attractive and inclusive work environment), and investing in capacity
building for women already on the job [
l
]
Channel disaster response resources via community and women's groups [
l
]
PREPAREDNESS
Use social protection to address specic
preparedness needs [
l
]
Build back schools and other public
buildings to function as multipurpose
shelters, ensuring they are functional
spaces for all populations [
l
]
Review legal, regulatory and disaster risk management planning framework for gender gaps
Community early warning, disaster
preparedness, and response training [
l
]
Community sensitization on evacuation
plans, ensuring women provide and
receive community planning and
outreach [
l
]
Use existing social protection providers, trainings, community groups and beneciary networks to inform preparedness action and
disburse early warning information [
l
]
Ensure early warning messages are
adequate and reach all affected people,
including women and other vulnerable
marginalized populations [
l
]
Ensure a system is in place to capture
SADD and information on gaps,
opportunities and lessons learned in
prevention, preparedness, and coping [
l
]
COPING CAPACITY
Support nancial inclusion by switching government payments from cash to digital [
l
]
Social protection to support income diversication and savings with cash transfers, support for savings groups, trainings, and so on [
l
]
Adaptive social protection to help mitigate adverse coping behavior, and (in some cases) domestic violence [
l
]
Childcare provision at public works [
l
]
Notes: Policy actions are organized according to recommended timing of intervention (horizontal). Color coding reects the outcome that the
policy is aimed to improve, a dot [l] indicates whether a local assessment is needed prior to action.
Improves
both
54 • Gender Dimensions of Disaster Risk and Resilience
3. Female representation and participation
Increasing female representation in disaster risk management and civil protection agencies helps
legitimize and support women’s contributions to disaster risk reduction and resilience. Women
have long been involved in planning, preparing, and responding to disasters at community level,
with little recognition. Providing women’s groups with training, resources, and the authority
to engage in preparedness and emergency response would strengthen their position in the
community and ensure more women get disaster preparedness and response information. To
be sure emergency and reconstruction resources support inclusive recovery, a proportion of
funding could be channeled to community centers and similar facilities used mainly by women.
Increasing the presence of women in civil protection and humanitarian and government
disaster response can help decrease the prevalence of gender-based violence. Programs also
tend to perform better when women are involved, because they usually better identify women’s
and children’s needs and, in some contexts, can reach other women more easily.
4. Building back better
Disaster recoveries are opportunities to build back in a way that breaks down the constraints
faced by women. For example, replacing damaged streetlights with solar powered lights, which
are more reliable where outages are common, would make streets safer for women after dark.
Housing reconstruction programs improve women’s tenure when the housing they rebuild is
jointly titled in both partners’ names. They also ensure that women who lose a partner and
female-headed households get legal rights to land and housing. In the aftermath of the 2004
tsunami, Indonesia’s Reconstruction of Aceh Land Administration System Project introduced
the option of jointly registering land, signicantly increasing the proportion of titles issued
jointly from 4 percent to 45 percent in four years (World Bank 2015a).
5. Community involvement
Involving communities—and particularly women—in channeling preparedness and early
warning information is crucial. To avoid establishing a new network of community organizations,
governments could use existing networks, such as social protection systems (box 4.1). After
a disaster, reconstruction can strengthen preparedness, by, for example, turning schools and
other public buildings into multi-purpose shelters that can be used in future disaster events. It
is important to ensure the design of these structures is informed by local consultation, and that
they provide a safe and comfortable environment for all.
6. Knowledge and data
To create better policies that work for all people, collecting data on gaps, opportunities and
lessons learned on preventing, preparing for, responding to, and recovering from disasters
is crucial. In most contexts, collecting information on ethnic minorities is also essential. For
comparability and to facilitate knowledge accumulation across countries, postdisaster data
collection and assessments should—where possible—be predened and share a common
framework across agencies, regions, and countries. The PDNA framework, commonly used to
assess disaster impacts, is an excellent starting point for this.
7. Local gender gap assessments
As already mentioned, these recommended policies do not replace the need for local assessments
to identify the gender gaps and barriers that make natural disasters particularly harmful for
certain populations before policy agendas are set. Anticipating that governments will carry out
local assessments, this report suggests relevant questions in the context of gender dynamics of
disaster impacts. Although it is more general, parts of the World Bank’s Gender Strategy (2015b)
can also inform gender gap assessments.
BOX 4.1
Building resilience with social protection
An increasingly important policy for the World
Bank portfolio, social protection supports
preparedness and coping capacity by providing
in-kind or monetary assistance to households
or employment opportunities in public works
programs.
It also plays an important role in helping
countries and people address disaster
vulnerability, build resilience, and manage
shocks (Monchuk 2014). Social protection
programs, typically managed by the government,
can support resilience in several ways, including:
» Financial inclusion of the most vulnerable
households through digital transfers,
access to bank accounts, or mobile transfer
services
» Promoting income diversication and
female labor participation through work and
income opportunities
» Smoothing consumption and averting the
adoption of negative coping mechanisms
through postdisaster nancing
» Supporting preparedness and adaptation
practices by coupling support with
early warning information and disaster
preparedness training
When using digital transfers, social protection
programs promote the nancial inclusion of
unbanked populations, and in some cases, directly
help households set up bank accounts, as part
of enrollment. Of the 140 million account owners
globally who opened their rst bank account to
receive government transfers, 57 percent are
women and 54 percent are in the poorest 40
percent of households (Demirgüç-Kunt et al. 2018).
Kenya’s Hunger Safety Net Program increased
coverage of households with bank accounts
from almost zero to over 90 percent in four of the
country’s poorest counties, by providing bank
accounts to the over 300,000 households that
enrolled in the program (Bowen et al. 2020). The
program provides regular transfers to 100,000 of
the poorest enrolled households, while additional
transfers are triggered in the event of a drought
shock (NDMA 2015).
Regular and reliable support to poor households
can help them diversify livelihoods, increase
investments in education and health and
accumulate savings to manage shocks (Monchuk
2014). Social protection programs can be
effective in mitigating differential impacts of
disasters on men and women. For example,
India’s Targeted Rural Initiatives for Poverty
Termination and Infrastructure Program (TRIPTI)
offset the disproportionate negative impact of
Cyclone Phailin on women’s consumption and
had a similar effect on expenditure on children’s
goods (Christian et al. 2019). Mexico’s conditional
cash transfer program PROGRESA helped offset
the negative impact of natural disasters on
girls’ school enrollment (de Janvry et al. 2006).
Even when mitigating disaster impacts is not an
explicit objective, social protection, if designed
appropriately, can help address the underlying
drivers that result in differentiated impacts of
disasters for men and women, boys and girls.
Public works programs typically build community
assets—such as irrigation systems—that
promote resilience. But they can also support
women’s labor participation (World Bank
2014), infrastructure development and land
rehabilitation to mitigate the impact of drought
or ooding, and support natural resource
management, serving both participants and
non-participants. For example, Ethiopia’s
Productive Safety Net Program (PSNP) creates
community assets, such as water points, that
help reduce women‘s time burden and encourage
women’s participation by offering more exibility
and community day care services (Jones, Tafere,
and Woldehanna 2010). Other programs use
quotas to promote female participation—for
example, India’s National Rural Employment
Guarantee Scheme reserves one-third of all
positions for women.
1
SADD are not available for
many public works programs in Africa. In those
that do provide data on female participation, the
average is 46 percent.
2
Adaptive social protection (ASP), which
governments can scale up before or after a
disaster to address additional needs, provides
a cushion for affected households, and can be
particularly important for women. ASP programs
typically include a mix of cash transfers, in-
kind support, public works, and other services
(Bowen et al. 2020; table B4.1.1). They typically
have two components: a constant component,
Policy Recommendations • 55
usually focused on livelihood diversication and
productivity, and an adaptive component that
scales up support in connection to disasters,
to help recipients avoid negative coping
mechanisms, such as taking children out of
school or decreasing food intake.
Preliminary results from an impact evaluation
of the Sahel Adaptive Social Protection
Program nd that 18 months into the program,
beneciaries (95 percent of whom are women)
were more likely to earn money from non-
agricultural businesses compared to control
groups (Bossuroy et al. forthcoming). Evidence
on the effects of the PSNP in Ethiopia nds
that the program’s cash-for-work component
and direct transfers to chronically food-
insecure populations help families smooth
food consumption patterns, facilitate school
enrolment, and provide basic necessities, which
can help mitigate some of the differentiated
effects of disasters on men and women (World
Bank 2010). Female beneciaries also reported
receiving greater respect within the household
and community.
Many public works programs consider gender in
their targeting and design. For example, most
World Bank-funded public works programs
include a female quota; 30 percent of World
Bank cash transfer programs target women
exclusively (World Bank 2014); 95 percent of
the Sahel Adaptive Social Protection Program
beneciaries are women; and 60 percent of
Hunger Safety Net Program beneciaries in
Northern Kenya are women. However, there is
no systematic review of gender-differentiated
targeting practices in ASP programs and little
evidence on ASP’s role (particularly the adaptive
components) in mitigating the differentiated
impacts of disasters on men and women.
Finally, social protection programs can also
provide systems for communicating early
warning information, training and guidance
on preparedness and adaptation, and directly
informing preparedness action before a disaster.
For example, beneciaries of the 4Ps—the
Pantawid Pamilyang Pilipino Program conditional
cash transfer program in the Philippines—must
attend monthly family development sessions,
which include disaster preparedness training
and offer information on how to recognize and
address PTSD (Bowen 2015). The Sahel Adaptive
Social Protection Program is working with
ministries of nance to develop an early warning
system methodology to identify and target the
most food-insecure areas (World Bank 2018).
Table B4.1.1 • Social protection programs with adaptive components
Social protection program Type of program and location Adaptive mechanism
Hunger Safety Net Program Direct cash transfer program in Northern
Kenya
Scales up vertically and horizontally,
based on observed weather-related
shocks
Northern Uganda Social Action Fund Seasonal public works program in
northern Uganda
Scales up program based on observed
weather-related shocks
Productive Safety Net Program Public works and direct support in
Ethiopia, part of the Food Security
Program
Provides seasonal public work for the
chronically food insecure and delivers
additional assistance to people affected
by shocks
Sahel Adaptive Social Protection
Program
Cash transfers, training, and saving
groups in Burkina Faso, Chad, Mali,
Mauritania, Niger, and Senegal
Financial support to households affected
by a shock based on predened rules and
triggers
Pantawid Pamilyang Pilipino Program
(4Ps)
Conditional cash transfer program in
the Philippines targeting the poorest
households
Provides ad hoc support to poor
households after natural shocks, such as
Typhoon Yolanda
Temporary Immediate Employment
Program (PETi)
A cash-for-work program in Mexico, part
of Temporary Employment Program (PET)
Scales up engagements in areas affected
by disaster
Sources: Ulrichs and Slater 2016, Pelham, Clay and Braunholz 2011, Ovadiya and Costella 2013
BOX 4.1
56 • Gender Dimensions of Disaster Risk and Resilience
Policy Recommendations • 57
References for Section 4
Bossuroy T, Goldstein, M, Karlan, D, Kazianga, H, Parienté, W, Premand, P, Udry, C, Vaillant, J, Wright, K. The Way to Scale?
Cost-Effectiveness of Economic Inclusion Interventions in Niger. World Bank Policy Research Working Paper (forthcoming).
Bowen, T. 2015. Social Protection and Disaster Risk Management in the Philippines: The Case of Typhoon Yolanda (Haiyan). World
Bank: Washington, DC. http://hdl.handle.net/10986/23448.
Bowen, T, Del Ninno, C, Andrews, C, Coll-Black, S, Gentilini, U, Johnson, K, Kawasoe, Y, Kryeziu, A, Maher, B, and Williams, A.
2020. Adaptive Social Protection Building Resilience to Shocks. World Bank: Washington, DC. http://hdl.handle.net/10986/33785.
Christian, P, Kandpal, E, Palaniswamy, N, and Rao, V. 2019. “Safety Nets and Natural Disaster Mitigation: Evidence from
Cyclone Phailin in Odisha.” Climatic Change, 153(1–2): 141–164. https://doi.org/10.1007/s10584-018-02364-8.
de Janvry, A, Finan, F, Sadoulet, E, and Vakis, R. 2006. “Can Conditional Cash Transfer Programs Serve as Safety Nets in
Keeping Children at School and from Working when Exposed to Shocks?” Journal of Development Economics, 79(2): 349–373.
https://doi.org/10.1016/j.jdeveco.2006.01.013.
Demirgüç-Kunt, A, Klapper, L, Singer, D, Ansar, S, and Hess, J. 2018. The Global Findex Database 2017: Measuring Financial
Inclusion and the Fintech Revolution. World Bank: Washington, DC. https://globalndex.worldbank.org/.
Jones, N, Tafari, Y, and Woldehanna, T. 2010. Gendered Risks, Poverty and Vulnerability in Ethiopia: To What Extent is the
Productive Safety Net Programme (PSNP) Making a Difference? https://www.odi.org/sites/odi.org.uk/les/odi-assets/
publications-opinion-les/6250.pdf.
Monchuk, V. 2014. Reducing Poverty and Investing in People: The New Role of Safety Nets in Africa Human Development. http://
hdl.handle.net/10986/16256.
NDMA. 2015. Hunger Safety Net Programme—Evaluation of HSNP Phase 2: Inception Report.
Ovadiya, M and Costella, C. 2013. Building Resilience to Disaster and Climate Change through Social Protection. http://hdl.
handle.net/10986/16492.
Pelham, L, Clay, E, and Braunholz, T. 2011. Natural Disasters: What is the Role for Social Safety Net? Social Protection and Labor
Discussion Paper, 1102. https://doi.org/10.1596/27374.
Ulrichs, M and Slater, R. 2016. How Can Social Protection Build Resilience? BRACED Knowledge Manager.
World Bank. 2010. Implementation, Completion and Results Report on Grant to the Federal Republic of Ethiopia for a Productive
Safety Nets APL II Project in Support of the Second Phase of the Productive Safety Net Program. World Bank: Washington, DC
http://documents1.worldbank.org/curated/pt/525401468024639387/text/ICR16760P098091e0only1910BOX358365B.txt.
———. 2014. Social Safety Nets and Gender. Bardesi, E and Garcia, G (eds.).
———. 2015a. The Voluntary Guidelines and the World Bank: Increasing Women’s Access to Land, Approaches that Work. Good
Practices Brief No. 1. World Bank: Washington, DC. http://pubdocs.worldbank.org/en/265941444250962923/WB-Good-
Practices-Brief-FINAL.pdf.
———. 2015b. Gender Strategy (FY16–23): Gender Equality, Poverty Reduction, and Inclusive Growth. World Bank: Washington,
DC. http://hdl.handle.net/10986/23425.
———. 2018. Sahel Adaptive Social Protection Program. World Bank: Washington, DC.
Endnotes
1. There is limited evidence that female quotas are needed to assure female participation.
2. Authors’ calculation based on (Monchuk 2014).
58 • Gender Dimensions of Disaster Risk and Resilience
SECTION 5
Next steps
The strategy for mitigating differential disaster outcomes based on gender and improving
results for all populations is to identify gender gaps that drive differential outcomes for men and
women, and to identify policy actions to address or overcome those gender gaps. To enhance
this agenda, governments and international organizations must enable the application of this
strategy; this work can be organized around both analytical and operational priorities.
From an analytical perspective, there are challenges in identifying gender gaps, driven by
a lack of both data and understanding of the channels through which gender dynamics can
inuence disaster impacts. By consolidating research and organizing it around a conceptual
framework, this report contributes towards a better overall understanding of these channels.
But it has also exposed important knowledge and data gaps.
Results in the report are primarily based on a set of case studies. One way to strengthen
the evidence base in this area is to leverage global or regional data to scale up country- or
subnational-level studies. For example, global historic disaster data could be leveraged to
assess differential impacts of disasters on the long-term health consequences or educational
attainment of boys and girls, following the methodology of country studies, such as Datar et
al. (2013).
Some areas of interest for disaster risk management practitioners are understudied. For
example, there is an important knowledge gap around how women and men receive, process,
digest and respond to early warnings about disasters to build preparedness and understand
discrepancies. Emerging new data and technologies are enabling new research that can help
close important knowledge gaps. For example, the increasingly available mobility data from
mobile phones provides an opportunity to understand evacuation behaviors, which can be
linked to gender-based differences in access to shelters.
With good data, it is possible to develop an understanding of how disaster losses and
postdisaster support are shared within a household, but collecting good data is both costly
and time-consuming. An increasing body of research estimates resource allocation within
households by combining household decision-making models with household survey data
(Bargain, Lacroix, and Tiberti 2018; Brown, Ravallion, and van de Walle 2019; Cherchye et al.
2017; Bargain, Lacroix, and Tiberti 2014). Such methods could prove useful in understanding
the role intrahousehold power dynamics plays in driving differentiated disasters outcomes for
members of the same family. They could also be used to assess whether disasters can inuence
power relations inside the household.
The COVID-19 crisis has resulted in new challenges for development, including disaster risk
management. Even as the public health and economic consequences of the pandemic continue
to unfold, emerging research suggests that men and women are not affected equally (Cuesta
and Pico 2020; Walsh et al. forthcoming). The pandemic has also complicated data collection,
requiring innovative gender impact assessments that combine shorter phone surveys with
pre-COVID-19 data sets, as used by GFDRR in its emerging analytical work.
Next Steps • 59
Finally, enabling rigorous impact evaluations of policies and interventions in disaster risk
management would help guide policy action and design while closing important knowledge
gaps. Impact evaluations provide essential information on how an intervention affects different
population groups, including women and children. Disaster risk management lags other sectors
in undertaking rigorous impact evaluations, limiting innovation and insights into which policies
and delivery methods best serve marginalized groups.
From an operational perspective, World Bank teams, governments and other relevant in-country
actors need guidance on how to conduct gender gap assessments in disaster risk management.
While this report can inform the design of gender gap assessments by providing a useful conceptual
framework, literature and data sources, it cannot replace the need for local assessments. Agreeing
a common framework will help achieve consistency in disaster risk management gender gap
assessments—both in non-disaster and postdisaster times—would be an excellent starting point.
Three forthcoming or recently published regional reports on gender, social inclusion and
disaster risk management will support the World Bank operational agenda:
» Krylova et al. (forthcoming): a desk review comparing gender-responsive disaster
preparedness and recovery efforts in the nine Caribbean countries
» Limani et al. (forthcoming): covering 11 countries in Europe and Central Asia key, the
report identies gender gaps and opportunities for strengthening gender through
disaster risk management operations in the region
» World Bank (2021): focusing on social inclusion more broadly, the report covers ve
projects in ve South Asian countries and pilots a set of project-specic Inclusive
Resilience Action Plans, which identify practical entry points to enhance social inclusion
for World Bank-nanced disaster risk management projects.
Project teams and governments can use resources such as these to identify relevant gender
gaps and understand how gender dynamics inuence outcomes of natural disasters.
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The Global Facility for Disaster Reduction and Recovery (GFDRR) is a global partnership that helps
developing countries better understand and reduce their vulnerabilities to natural hazards and adapt
to climate change. Working with over 400 local, national, regional, and international partners, GFDRR
provides grant nancing, technical assistance, training and knowledge sharing activities to mainstream
disaster and climate risk management in policies and strategies. Managed by the World Bank, GFDRR is
supported by 34 countries and 9 international organizations.
www.gfdrr.org
