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Gender and age inequality of disaster risk

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Authors: Sarah Brown, Mirianna Budimir, Sujana Upadhyay Crawford, Rebecca Clements, and Alison Sneddon

EXECUTIVE SUMMARY

Context, objective and methodology

Women, children and youth are often recognised to be among the most vulnerable to natural hazards.

To understand disaster risk better, and tackle it effectively and in a gender- and age responsive manner, it is important to delve into the complexities and inequalities in a given location, the differences within and between broad categories of women, men, boys and girls, taking a context specific and intersectional approach.

This study explored the connection between gender and age inequality and disaster risk, examining evidence at a global level, and in three case study countries (Nepal, Malawi, and Dominica).

The study reviewed existing literature and datasets, assessing evidence of differential impact. The study examined three in depth case studies, considering evidence of differential impact in earthquake (2015) in Nepal, flood (2015), cyclone (2019) and drought in Malawi, and hurricane (2017) in Dominica. The country case studies considered context specific evidence of differential impact in areas including mortality, healthcare, WASH, livelihoods, education, housing and migration.

Through literature review and targeted Key Informant Interviews, we identified groups facing marginalisation in each case study context e.g. widows in Nepal, transgender women in Malawi, or children with albinism in Malawi. We listened to the experiences of individuals who are rarely considered in policy or programming; who are often overlooked or sidelined in Post Disaster Needs Assessments or preparedness plans.

Key Findings

The literature review highlighted incidences where inequality has driven significant differential impacts for women and girls. It also highlighted situations where people of other genders were worse affected. Examples of differential impact are context and event specific, often driven by differential exposure and context specific inequalities.

The data review found huge gaps in disaggregated quantitative data at a global level, with a near total absence of sex and age disaggregated impact data in global disaster impact databases, and in global analyses of differential impact. A review of the DesInventar database revealed that only 11 out of 85 countries disaggregated by sex for mortality, and out of those 11 only 0.65% of recorded deaths were disaggregated.

In all of our case study contexts and events disaggregated disaster impact data was limited.

The available data highlighted the diverse ways in which women, children and other marginalized groups can be differentially impacted by disasters over the short, medium and long term. These areas of differential impact varied from one country and event to the next – unsurprising as differential impact is often driven by context specific inequalities.

The country case studies also highlighted the way in which data gaps actively contributed to and reinforced exclusion. Data gaps excluding marginalized groups were apparent in all data sets, including at census level, meaning marginalized groups were often invisible in analysis, policy and practice.

Lessons Learnt

Analysis based on disaggregated quantitative impact data alone is insufficient to meaningfully understand and take action to reduce differential impact.

In order to get well-rounded insight into differential impact we found it useful to combine three existing types of data:

1) Disaggregated quantitative disaster impact data (potentially including census data on the demographics of the population in an affected area e.g. number of single women headed households).

2) Qualitative insights into differential impact from surveys or Focus Group Discussions in the area, sometimes focused on specific groups e.g. children.

3) Context specific data on inequalities.

The combination of these three data types enabled a broad understanding of areas of differential impact. The available data provided insights into differential vulnerability at scale and between women and men, old and young.

However, this data tended to treat groups as homogenous, focusing on singular identities (children as a uniform group for example), not capturing the ways in which women or children with multiple vulnerabilities or areas of marginalisation are differentially impacted.

There were minority, vulnerable or marginalized groups who were not appearing, or only mentioned in passing, amidst the mainstream data.

Missing Voices approach

To add nuance to the analysis and gain insights into the experience of those facing additional areas of marginalisation, we undertook what we are calling ‘Missing Voices’ interviews.

The ‘Missing Voices’ methodology, which requires approaches of building trust, listening, and working in partnership with intermediary organizations, provided a rich intersectional and context-specific perspective on the impacts of disasters on marginalized groups.

Five themes emerged strongly in the missing voices interviews:

  • Entrenched discrimination impacted vulnerability pre and post disaster.

  • Multiple areas of marginalisation exacerbated and multiplied vulnerability pre and post event.

  • Marginalized groups face heightened vulnerability to gender based violence, and additional barriers to getting support.

  • Exclusion of marginalised groups from datasets reinforces and perpetuates exclusion from DRR, response and recovery.

  • Minority groups reported feeling invisible, unnoticed, misunderstood and un-prioritised post disaster and in efforts to reduce disaster risk.

Recommendations

In order to reduce gender and age inequalities in disaster, we need a better understanding of differential impact, which needs to be underpinned by gender and age inequality informed data. This shift will require

  • Strengthened systems for sex and age disaggregated quantitative data.

  • Going beyond disaggregated quantitative data, to include qualitative and inequality focused data.

  • Proactive efforts to seek out other key sources of data that amplify the voices of marginalized populations.

  • Proactive efforts to identify, build trust, engage with, and listen to the experiences of those most at risk of being left behind.

  • Mechanisms to enable these marginalized experiences to inform gender and age-responsive DRR actions.

Inequality Informed Data

This study proposes a 6 Step Approach to understanding differential impact. This involves the combination of different data sources, including disaggregated quantitative disaster impact data, census data, qualitative studies of the hazard event, and contextual information on underlying inequalities, supplemented with perspectives drawn from key informants and from proactively listening to the experience, priorities and needs of ‘missing voices’.

This 6-step approach should produce a deeper, richer understanding of differential risk, underpinned by better, more inclusive data.

Better data can help ensure DRR efforts do not exacerbate existing inequalities and vulnerabilities. It can provide an intersectional understanding of disaster risk, enabling a shift from gender and age inequality unaware action on disaster risk, to a transformative approach. It can provide a foundation for action to reduce differential impact, ensuring no one is left behind.

281 natural hazard-related disasters occurred in 2018, affecting 61.7 million people, with 10,373 lives lost (CRED EM-DAT). Women, children and youth are recognised to be among the most vulnerable to natural hazards, conflict and other shocks.

Over 250 million children currently live in areas affected by disasters, armed conflict and high levels of violence, and it is estimated half of the world’s poor children live in fragile situations. (UNICEF, 2018)

While women’s, children’s and youth’s heightened vulnerability in disasters is linked to their lower socioeconomic status, including gender and age specific barriers to resilience, little statistical evidence has been generated on the topic. This is largely due to a lack of sex and age disaggregated data.

“Disasters don’t discriminate, but people do… disasters reinforce, perpetuate and increase gender inequality, making bad situations worse for women.” (UNISDR, UNDP and IUCN, 2009)

One 2007 statistical analysis on the outcomes of natural disasters in 141 countries found that women were more likely to die, and die younger, than men in disasters (Neumayer and Plümper, 2007).

Climate change and environmental degradation are further compounding the vulnerability of these three population groups, and extreme weather events increase the number of emergencies and humanitarian crises.