11 January, 2016 © Crown copyright

Case study two – Flooding in Nigeria, 20114

Flooding in Lagos, Nigeria during 2011

exposed varying levels of vulnerability for

women and girls based on income rates.

Those within the lower income regions of

Badia experienced significant water and

sanitation challenges. Those women and

girls in the high-income Victoria Island and

middle-income Ajah region experienced far

fewer restraints to recovering from the

floods. This provides a useful reminder that

even within gender disaggregated data,

there can be underlying impacts for smaller

groups within a section of society.

This highlights that gender is often, but not

always the key factor. The intersection

of other factors such as age, race,

socio-economic status, ethnicity, etc.

combine to result in differential impacts to

women and men.

ACKNOWLEDGEMENTS REFERENCES

The collection of data is a standard process in the immediate aftermath of a humanitarian

emergency. Identifying those within a community who need shelter, food, clothing and other

vital equipment is often the first action a responding organisation will undertake. Data collected

is then used to determine requirements within the community and provide supplies.

“Access to information is critical to successful disaster risk management. You

cannot manage what you cannot measure." -- Margareta Wahlström, Special Representative of the

Secretary-General for Disaster Risk Reduction 2008 - 20151

The impacts of disasters are not distributed equally within society. Disasters often affect some

members of a community more severely than others; therefore different sections of a society

require different types of assistance. Women and girls have been shown to be significantly more

affected in disasters than is the general population.

This poster explores key issues for women’s and girls’ disaster vulnerability and

highlight how disaggregated data collection and analysis can assist with mapping and

understanding whole community vulnerability, to enable a more effective humanitarian

response.

This poster has been developed with assistance from Public Health England,

Northumbria University and the Gender and Disaster Network.

Exploring the collection and analysis of disaggregated data

to help improve humanitarian response to women and girls after disaster

BACKGROUND

Gender disaggregated data is data that has been collected to enable it to be broken down by gender.

Disaggregated data can be collected using both qualitative and quantitative methodologies.

Whilst the process of collecting gender disaggregated data is a relatively simple – although often ignored – process, when applying other categories (such as age), socio-economic classification can become complex

The process of collecting disaggregated data has not been widely adopted despite many within the DRR community recognising and advocating its benefits. In fact, the Sendai Framework includes specific calls for data to be disaggregated by:

Case study one - Flooding in Pakistan, 20103

The flooding killed approximately 2000 people and directly affected more than 200 million.

Whilst these figures are harrowing enough, it has been shown that women and girls faced

disproportionately higher impacts than men and boys. Workloads for women and girls

increased with

many women

expected to carry

out traditional roles

as care-giver and

home-keeper but

also to assist with

traditionally

male-dominated

work including

providing

agricultural support

and assistance in

rebuilding damaged

property. These

issues were only discovered after exploring data collected using a disaggregated analysis.

This realisation was vital as no programmes initially covered women’s additional workload

and responsibilities or the subsequent health impacts.

Using the Sendai Framework, Science and Technology to Improve the Collection and Analysis of Disaggregated Data

Authors: Kevin Blanchard, DRR Dynamics & Gender

and Disaster Network (GDN)

Cheney Shreve Liu,

Laurie Campbell, Maureen Fordham,

Northumbria University and Gender and

Disaster Network (GDN)

INTRODUCTION

:19(g) – “…sex, age and disability, as well as on the easily accessible, up-to-date,

comprehensible, science-based, non-sensitive risk information, complemented by

traditional knowledge”2

However, initial data collected from the 2009-2011 Hyogo Framework for Action

Monitor, indicated that 62 out of 70 countries do not collect vulnerability and

capacity information disaggregated by gender

Gendered analyses examine (unequal) power relationships between men and women . Vulnerability analysis (VA) is a participatory process through which the risks, vulnerabilities and

capacities of people are analysed . Coupling gendered analyses with vulnerability analyses is a powerful mechanism for building resilience for both genders —making visible needs and

capacities but also inequalities, that must be addressed to enable resilience.

Women are frequently more adversely impacted by disasters in comparison to men, but not all women, and not all disasters. Due to their roles as caretakers, 55-60% of deaths during the

recent Ebola outbreaks in Liberia, Sierra Leone, and Guinea were female . In contrast, in the 1995 Chicago heat waves, it was poor, elderly, African American men who died in

disproportionately higher numbers than other groups . However, for heat waves in France during 2003, victims tended to be elderly, disabled, lower social class females. This data indicates

that culture, location and context matter. Disaggregated data analyses make these changes visible, enabling more effective humanitarian response.

Case Study Examples

1. UNISDR (2012) Disaster Statistics. Accessed 11/01/16 from https://www.unisdr.org/we/inform/disaster-statistics

2. UNISDR (2015) Sendai Framework for Disaster Risk Reduction 2015 – 2030. Accessed 09/01/16 from http://www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf

3. Drolet, J., Dominelli, L., Alston, M., Ersing, R., Mathbor, G., & Wu, H. (2015). Women rebuilding lives post-disaster: innovative community practices for building resilience and promoting sustainable

development. Gender & Development, 23(3), 433-448.

4. Ajibade, I., McBean, G., & Bezner-Kerr, R. (2013). Urban flooding in Lagos, Nigeria: Patterns of vulnerability and resilience among women. Global Environmental Change, 23(6), 1714-1725.

5. Image one - Adrees Latif/Reuters - http://www.nytimes.com/2010/08/01/world/asia/01pstan.html

6. Image two – UN Women

7. Image three - http://asiapacific.unwomen.org/en/news-and-events/stories/2015/06/the-gender-factor-in-nepal-s-reconstruction

8. Image four - https://openknowledge.worldbank.org/bitstream/handle/10986/17075/733710BRI0P1300idance0Note0080final.pdf?sequence=1&isAllowed=y

Image one

Image two

Image three Image four