Country overview
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Reference mapping is one of the most fundamental maps and one of the most useful in any response. They provide context and orientation for any location. Reference maps can be simple country overview maps to detailed street level mapping with lots of detail.
The depiction of administrative boundaries, with p-coded (place code) labels where appropriate, is invariably highly important for multiple aspects of information management in support of humanitarian decision-making. This is because it encourages and enables situational data to be aggregated using a consistent framework, and so facilitates analysis. It is essential that administrative boundaries, with any associated p-codes, are standardised across institutions and agencies involved in the response.
Early on in a response it may only be possible to obtain level 0 (International) or level 1 (province, municipality) information, but the more detailed the boundaries, the more granular the analysis can be, so using level 2 (district/zone), level 3 (territory/city), or level 4 (village) becomes more important as a response evolves.
Strategic and operational.
Basemap.
The depiction of administrative boundaries, with p-coded labels where appropriate, is invariably highly important for multiple aspects of information management to support humanitarian decision-making. This is because it encourages and enables situational data to be aggregated using a consistent spatial framework, and so facilitates analysis.
Everyone.
The depiction of administrative boundaries, with p-coded labels where appropriate, is invariably highly important for multiple aspects of information management to support humanitarian decision-making. This is because it encourages and enables situational data to be aggregated using a consistent spatial framework, and so facilitates analysis.
Maps styles will vary according to the audience and intended use:
basic - black and white or grey scale map with just administrative boundaries: easy to photocopy, users can add their own information over the top.
advanced - full colour reference, office wall type map: users are likely to be planning operations with it and need as much detail as possible.
Create a gazetteer and lookup for settlements, particularly if there are many settlements. This will enable the user to find locations more quickly and efficiently, particularly when there are hundreds or thousands of locations.
Use data driven pages, or at the very least have this in mind.
Plan to produce three or more levels of maps: (1) country; (2) administrative level 1 map series; (3) administrative level 2 map series, each with increasing levels of detail if required.
Administrative boundaries and p-code maps should be used as a base for almost all products.
It is essential that administrative boundaries, with any associated p-codes, are standardised across in- stitutions and agencies involved in the response. The starting point will normally be the common opera- tional datasets. OCHA information management staff will normally have stewardship of these datasets, and should be consulted to ensure that the version used in mapping is consistent with that in use for data collection and other purposes.
Administrative Boundaries
Global Administrative Areas (GADM) - accurate global coverage of administration boundaries from level 0 to level 2. Can be downloaded in multiple GIS formats.
Global Administrative Unit Layers (GAUL) - global coverage of administrative boundaries. Each country varies in the number of administrative levels that are included, from level 0 to level 5.
Large Scale International Boundaries (LSIB) - accurate international boundary level data.
Second Administrative Level Boundaries (SALB) - highly accurate for the countries covered.
Place Codes (p-codes)
Common Operation Datasets (CODs) - accurate global coverage of administration boundaries from level 0 to level 2. Can be downloaded in multiple GIS formats.
Settlements
Humanitarian Response has a number of documents that further explain the concept of p-codes and how to create them.
These maps show the physical ‘lie of the land’, and include information such as elevation, rivers and lakes. They allow the user to begin to understand the accessibility of an area. Flat areas near rivers may be prone to flooding or storm surges if near to the coast. On the other hand, these may be identified as potential helicopter landing zones or locations for camps for displaced people. Knowing where the mountainous regions are and their influence on temperature and rainfall will help to inform decisions when planning for winter.
Strategic and operational.
Basemap.
These maps should be produced and distributed as early as possible in an emergency response. Those responders new to the affected area will need to get an overview of where everything is as soon as they can.
Everyone.
Topographic maps are useful for anyone planning IDP camps or other facilities where large open areas are required. Planners will want to understand whether areas are prone to flooding.
For pilots, understanding the topography is important as it may determine where they can fly, the route that they take and how they can take-off or land. They are particularly interested in the maximum height of major obstacles in the area, and peaks and valleys that can have an effect on weather conditions.
Use some form of digital elevation model or contours to show height, this is particularly key in mountainous areas where pilots will be flying.
Topographic maps can be used as base maps relating to floods, storm surges, telecommunications line of sight, or identification of potential IDP camp locations.
national mapping agencies
Google Earth
Perhaps one of the first maps that you may see in a response or if you are unfamiliar with a country. This map provides the simplest overview and orientation of a country, region or other geographical area providing an overview of the capital and other key cities, major roads and transport links and physical features such as rivers and lakes.
Strategic and operational.
Basemap.
These maps already exist but they can should be produced as early as possible. It should be a one off production, it can however be the basis for many other maps such as situational overview maps and many of the other thematic maps that can be produced.
Everyone.
For new responders coming into a country that is new to them or at least unfamiliar it helps orientate them and familiarise themselves with the overall lie of the land.
Keep the map simple and only include key features such as the following:
National capital
Other major cities
Key roads, airports and seaports
Significant rivers and lakes
Remember that this map can be used for many of the other maps so keep this in mind when you are designing. It is also an easy and useful map to add to a presentation slide for others to use or to add to a report to orientate the reader.
You can keep the map title really simple, for example,"Reference map of Sri Lanka" or "Reference map of Eastern Europe".
Population maps can be categorised into baseline population and affected population. Baseline population is the population of an area before the response and affected population is that after or as a result of the event.
Maps produced in response to extensive population displacements that may be internal, cross-border (refugees) or both. Such displacements may be driven by a natural or technological disaster, or by a complex emergency. Data to be mapped is most often generated through coordinated displacement tracking and field assessment activities, although may sometimes be derived from predictive and remote sensed methods.
Both.
Situational.
Displacement can occur at various times during an emergency and may recur and shift through returns and secondary displacements, particularly during protracted crises.
All responders, but particularly those working on assessment processes and response planning and coordination. Emergency shelter, protection and camp coordination and camp management cluster actors may be both key data providers and users of such mapping.
Displacement is a major driver of humanitarian needs and the profile of displaced people, including their movements and locations, is a key information need for response planning.
In complex emergencies, protection must be considered carefully before issuing any maps identifying groups who may be vulnerable.
The harmonisation of spatial structures (e.g. p-coded administration units) with situational datasets is crucial for the effective mapping of displaced people. This should be considered when designing profiling projects of IDPs.
Thought should be given to the most effective way to depict on maps the movement of groups, who may go through several different phases of displacement. Infographic methods may be most suitable.
Qualified and reliable data on groups of displaced people. This will usually be collected through a coordinated process such as an IDP profiling project and/or a displacement tracking matrix.
Best-available administration boundary and settlement datasets, matching the spatial tagging of the displacement data.
Data on the pre-emergency population is likely to be valuable in some cases.
International Organisation for Migration (IOM)
Displacement Tracking Matrix
United Nations High Commissioner for Refugees (UNHCR) - Asylum and Migration
This shows the population that has been affected by the emergency. The affected population is the key figure to be reported during a response, and will determine the type of response required. During the acute stages of an emergency these figures can be highly changeable and uncertain, but as the response continues the figures should stabilise and then hopefully decline. It is important to recognise the units of measurements used – i.e. individuals, families, households, etc., as these will determine the response. If family or household is used, then how many people make up a family? Likewise if household is used, how many people make up a household? The definition of ‘affected’ can be hard to define and will vary, but may include injured, displaced or those affected by the emergency and in need of some form of assistance (e.g. without shelter, food, water, etc).
Strategic and operational.
Situational.
As early as possible in the response, and should be updated routinely – particularly during the acute stages.
Everyone. Individual clusters and specialists will be interested in the affected numbers that relate to their specialist expertise (e.g. the water, sanitation and hygiene (WASH) cluster will be interested in the number of people without safe drinking water, the shelter cluster in the number of people with damaged or destroyed houses).
The affected population figure will determine the type of response required, and is also one of the triggers for a response in the first place.
Try to use individual people as the unit of measurement rather than households or families, as this will remove any uncertainty around how many make up a family or household.
Use round figures – you can’t have a fraction of a person.
National and local government
Ministry of Health
Local Emergency Management Agency (LEMA)
Office for the Coordination of Humanitarian Affairs (OCHA)
Humanitarian clusters
Humanitarian Data Exchange
is a clean simple dataset that is perfect to use for these maps. You may wish to supplement it with data from or where there might be more accurate data or administration boundaries that are being used by the humanitarian community.
This report brings together learning from a review of both humanitarian and academic literature and also gender focused interviews with stakeholders from a range of humanitarian organisations. It aims to highlight the importance of taking gender into account in data collection and analysis and the opportunities this presents for better humanitarian decision making. It also explores the challenges and barriers to this effectively happening in practice and seeks to identify ways in which MapAction can contribute to better consideration of gender and collection of sex and age disaggregated data (SADD).
Before beginning the report it is important to define some key differences between sex, gender and gender identity.
"Sex" refers to the biological attributes of a person (Sphere handbook, 2018).
"Gender" refers to the socially constructed differences between women and men throughout their life cycle. (Sphere handbook, 2018).
"Gender identity" is a person’s "deeply felt, internal and individual experience of gender, which may or may not correspond to the person’s physiology or designated sex at birth" (WHO, 2021).
While the focus of this research is more broadly on gender, significant emphasis is placed on reference to the relevance of sex and age disaggregated data (SADD). It is important to recognise that there are multiple factors that influence an individual’s needs and vulnerabilities. Here the focus is mainly on gender (or sex) and because of the frequent reference to SADD also considers age to some extent. We acknowledge other characteristics such as disability, ethnicity, religion and sexual orientation also impact an individual’s vulnerability, but these are beyond the scope of this study.
Sometimes known as a common operational picture, these maps aim to provide a snapshot or overview of the emergency at that moment in time. They will typically include a mixture of thematic information, possibly including physical impacts, hazards, numbers of affected people or response actions. In the early stages of an emergency, responders require a visualisation of the disaster zone that enables them to acquire a general spatial understanding of the operating environment. In many cases, newly-arrived actors may have no prior knowledge of the operating geography.
Operational.
Situational.
From the start of the emergency, although initially there may be very limited information available. During the early stages of the emergency maps might be updated twice daily, but are more likely to be daily transitioning to every other day, weekly or when there is a significant change in the situation.
Everyone.
Organisations - Governments (National or Local), UN, Clusters, NGOs, Donors and others;
Roles - Rescuers, Programme Managers and funders
In the early stages of an emergency responders require a visualisation of the disaster zone, which enables them to acquire a general spatial understanding of the operating environment. In many cases, newly- arrived actors may have no prior knowledge of the operating geography. Maps will be used to plan and execute initial life-saving responses, and to understand the dimensions and constraints of humanitarian assistance. These initial maps will often be used to plan damage and needs assessments.
The creation and dissemination of clear, simple maps conveying what is known about the emergency should be a priority from the earliest stages of a new disaster.
Base maps should show administration boundaries at an appropriate level, and relevant topographic data layers.
Situational data is initially likely to be fragmentary and anecdotal: textual annotations may be the best way to map this.
Be aware of the risk of wrong interpretation of ‘no data’ to mean ‘no impact’.
Annotate maps clearly as being subject to regular updates, and request data to be submitted e.g. 'this map needs your help!’.
Government reports
OCHA situation reports
Rapid assessments
Assessments registry (for data in where assessments have already been done)
Stakeholder interviews were undertaken in November and December 2022 by Alistair Wilkie and Gemma Davies with participants representing: REACH/IMPACT, ACAPS, HOTOSM, iMMAP, CDEMA, OCHA FISS, OCHA Bangkok office, Save the Children, Care International, FDCO.
The key themes emerging from the interviews are summarised in the section below:
Considering gender needs to be more than a tick box exercise. In order to mainstream gender, it is important to ensure that the concerns and experiences of women and men (and other vulnerable groups) are considered at all levels of project design and implementation. Gender needs to be considered from the initial stages of project design (regardless of the type of project) and should influence who you are talking to, who you do and don’t have access to, and the questions you will then ask. Successful consideration of gender requires a small investment by a lot of people. While there is much that could be done in an ideal world, with unlimited resource, there is still value in starting simply working on the things you can easily consider and adjust will a little though, such as recording the gender of the key informant interviewed. Proper consideration of vulnerability needs to extend beyond just sex and age in order to fully understand the affected population.
Important distinctions were drawn that it is much easier to define sex than gender and, in some cases, collecting data on gender identity is discouraged for features of data sensitivity. There is also an incorrect tendency to view gender analysis being only about women and girls, sometimes neglecting the specific needs of or impacts on men.
There is much agreement and policy around the collection of SADD where possible, however, practice tends to vary. Even where there are the best of intentions collecting data on gender can be very difficult in some settings, for example southern Afghanistan or Yemen where female assessors must have a male escort with them at all times. However, in many counties with only little effort and thought it should be possible to collect this effectively from the very beginning. Once collected, analysis of primary or secondary data ideally requires a diverse analysis team, men and women of different cultures, in order to avoid unintended bias. For collection of SADD to be effective there needs to be thought as to why it is being collected and what analysis it will inform.
A clear example of why it is important to consider gender was given in the case of the Sri Lanka Tsunami. When this hit lots of women were at home at the time and were killed. Initial assumptions in camps were that single female headed households would be more common, however, on this occasion there were more men, who had been left leading households for the first time and needed to taught how to cook, not just provided with food. The response needed to be changed to reflect different gender situation and cultural context. Other examples of where considering gender was relevant included:
A waste mapping project in Somalia that initially struggled to get relevant information until they gained access to interviewing local women who were responsible for most of the waste collection.
An otherwise great survey on maternal child health in Tanzania forgot to record the gender of the respondents, which affected the understanding of the results.
The lack of gender consideration in quarantine facilities meaning a single female headed family may be sharing a room with single men.
There was wide agreement that gender should be considered at all stages of the response cycle, but also importantly, that if it was not taken into consideration the pre-disaster phase there would be little chance of meaningfully considering it when the disaster struck, and also that if SADD is not considered from the start it is difficult to bring it into the research design later. Detailed information on population dynamics is particularly useful to obtain before a disaster hits. There is variation in the likelihood of SADD being collected depending on the type of disaster. While SADD is always important for understanding the situation and avoiding the need for repeat assessments, this is more likely to take place in more stable emergencies or camp setting and more likely to be missed during early stages of a sudden onset disaster. Often teams doing damage assessment have very little focus on gender, particularly if you have all male teams setting in at the last minute to do assessment. It is often too late at that point to influence consideration of gender during data collection. Typically, SADD is better considered during large scale Multi-Sector Needs Assessment (MSNA) and more likely missed during rapid needs assessment.
There is often a disconnect between those collecting the data and the reasons for collecting it. If people do not understand what will be done with the data, and they are busy they may not collect it. Therefore, with limited resources on the ground, it often gets skipped. Collection of SADD can be challenging especially when there are no women on the assessment team and the views of women not accounted for either because access to women in the community is therefore or restricted, or they are just not thought about. SADD can sometimes end up treated as a box ticking exercise with a disconnect between what is requested by decision makers and what is happening on the ground with limited resources. Cost often limits being able to have 2 enumerators (1 male and 1 female). At sudden onset SADD can often be viewed as something that can wait until later, but that means that you may have to go back to communities later when collection was not complete at the start.
When disaggregated data exists (e.g. census data) it is often aggregated before being released and is therefore of more limited use, the same can happen with results from data published in reports, where aggregated results are published and disaggregated raw data not shared. Data consistency is also a limiting factor such as inconsistent age categories If those advocating for SADD don't understand the analysis aspect when they ask for it, the survey can fail to capture the appropriate data for in-depth findings. When SADD is collected is not then necessarily analysed, or not analysed well. There is a need for training so that people collecting data have the knowledge on what to collect and that they or others know how to analyse it. There are cultural challenges in contexts where it is more difficult to collect data from women, often with a requirement to speak to the (usually male) head of the household. The key challenges can be summarised as:
Lack of understanding on the importance of SADD for analysis and decision making by those on the ground collecting the data
Cost limitations and lack of available enumerators
Poor follow through in terms of analysis and use of the data
Cultural context and limitations on access to all groups
Lack of appropriate training for assessment design, data collection and analysis
A consistent message throughout the literature and interviews undertaken was that gender analysis and collection of SADD is important, but is often missed for a variety of reasons. There often appears to be a disconnect between those who understand the value of gender data and analysis and wish to use this in decision making and those collecting data on the ground, who do not always understand its value and relevance and perceive it as an additional burden. Sometimes very real practical and resource limitations add to difficulty in including gender in assessments, especially when trying to implement this at the point of rapid needs assessments in the aftermath of a sudden onset disaster.
A clear message that emerged during the interviews in particular, was that if no thought as been given to gender analysis or SADD during the preparedness phase, then it is unlikely to considered properly or collected in the first couple of weeks after onset of a crisis. This in turn limits its adoption and effectiveness at later stages of the response. It is therefore key where possible to collect SADD on baseline population and needs, an understanding of the gender context, and establish connections with a relevant range of groups on the ground who may be able to assist with access to gendered data during an emergency. Gender is typically better considered in protracted crisis, then in the aftermath of a sudden onset event. Even when collected SADD is not useful if it is not clearly analysed and presented in a way that is useful for humanitarian decision making.
There appears to be a training gap ranging from field assessors through to decision makers, with more actors needing awareness and understanding before a crisis hits. Greater training and understanding is needed around: the gender context in specific situations; appropriate wording of questions to capture gender relevant information; the influence of the gender of the enumerator and informant on data obtained; how to analyse and interpret data in a way that help inform decision making and programming.
The message clearly coming through from stakeholders interviewed is that of ‘every little helps’. If everyone works together to raise awareness of gender and the importance of disaggregated data it will eventually become more integrated into thinking at all stages of a response.
ACAPS (2016) - Meeting information needs? A review of ten years of multisector coordinated needs assessment reports accessed 29/11/2022
Benelli P, Mazurana D & Walker P (2012) - Using sex and age disaggregated data to improve humanitarian response in emergencies, Gender & Development, 20:2, 219-232, DOI: 10.1080/13552074.2012.687219
DARA (2011) - [Addressing the gender challenge](https://daraint.org/wp-content/uploads/2012/03/HRI_2011_Addressing_the_gender_challenge1.pdf accessed 13/09/2022
Data2x (2022) - Data2x
Doss, C & Kieran, C (2013) - Standards for collecting sex-disaggregated data for gender analysis: A guide for CGAIR researchers accessed 13/09/2022
Eklund L, Tellier S (2012) - Gender and international crisis response: do we have the data, and does it matter? Disasters. 36(4): 589-608. DOI: 10.1111/j.1467-7717.2012.01276.x.
FCDO (2018) - UK National Action Plan on Women, Peace and Security 2018-2022: Guidance Note Implementing Strategic Outcome 4: Humanitarian Response](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/959786/UK_NAP_Guidance_on_Strategic_Outcome_4-Humanitarian_Response.pdf) -- Hoare J, Smyth I & Sweetman C (2012) - Introduction: post-disaster humanitarian work, Gender & Development, 20:2, 205-217, DOI: 10.1080/13552074.2012.698914
IASC (2018) - The gender handbook for humanitarian action accessed 13/09/2022
Mazurana D & Proctor K (2015) - Gender analyses. In The Routledge Companion to Humanitarian Action (chapter 4) Eds: MacGinty R, Peterson J. ISBN 9780415844420 2015
Mazurana D, Benelli P, Walker P (2013) - How sex- and age-disaggregated data and gender and generational analyses can improve humanitarian response. Disasters. Suppl 1:S68-82. DOI: 10.1111/disa.12013. PMID: 23905768.
Mazurana et al (2011) - Sex and Age Matter: Improving Humanitarian Response in Emergencies” Feinstein International Center, Tufts University
Pezzulo, C., Hornby, G., Sorichetta, A. et al. (2017) - Sub-national mapping of population pyramids and dependency ratios in Africa and Asia. Sci Data 4, 170089 -- IDA (2015) - Gender Equality in Humanitarian Assistance
Streets J, Binder A & Foran S (2013) - Gender-Age Marker Toolkit.
Tatem, A., Garcia, A., Snow, R., Noor, A., Gaughan, A., Gilbert, M., & Linard, C. (2016) - Millennium development health metrics: where do Africa's children and women of childbearing age live? Population Health Metrics, 11(1), 11.
World Health Organisation (WHO) (2014) - Gender, Climate Change and Health.
The interagency standing committee (IASC) 2018 Gender handbook for humanitarian action contains a lot of detailed considerations for using gender analysis, with much cluster specific breakdown
Oxfam (2013) - (Oxfam minimum standards for gender in emergencies](https://www.oxfamwash.org/communities/gender/ml-oxfam-gender-emergencies-minimum-standards-291113-en.pdf)
A literature review on mapping gender
Shows the population for the area of interest before the emergency. It may show absolute population numbers per district, or population densities.
Strategic and operational.
Baseline.
As early as possible in the emergency, possibly during the pre-deployment stage, subject to availability of data.
Everyone.
The spatial distribution of the baseline population of the disaster-affected area is of high importance in understanding the potential impact of the disaster. By cross-analysing physical impact indicators (even just a list of affected districts) with population figures, first attempts can be made to create a humanitarian profile for the emergency. Visualising the distribution of the population is often also important to create understanding of the complex spatial dimensions of a response, such as access constraints and numbers of people living in different livelihood zones (e.g. upland versus lowland farming).
Initial maps showing relative population density should be produced using whatever data is available, but with the source clearly marked.
Symbolising population density is ideal for visual interpretation, however labelling with absolute numbers can add value for users.
While total population figures may be used on the map, it can be useful to add other graphics with generalised data to the map sheet, e.g. a pyramid chart to show age and gender breakdown.
National Census
Census data from the national statistics office should provide the most accurate picture of the population and include further demographics such as age, gender, number of those in school, etc.
Other sources
It should be established whether this data matches the administrative boundaries dataset in use (which may be inconsistent due to boundary changes since the last census).
Common Operational Datasets (CODs)
Humanitarian Data Exchange (HDX)
Gridded population estimates
These datasets may be useful where locally-derived population figures are not available, or cannot be reconciled to administrative boundaries.
GRUMP, WorldPop, LandScan datasets, may be useful where locally-derived population figures are not available, or cannot be reconciled to administrative boundaries.
Useful in all elements of your work.
These products are useful at any point during a response regardless of a hazard or vulnerability and are often the basis for the rest of the products.
These products show established and planned humanitarian coordination and logistics locations, and sometimes their designated areas of responsibility. Coordination centres and hubs depicted may include those established by national authorities, UN agencies, humanitarian clusters or other coordination bodies such as NGOs.
Normally operational, as it provides information about the coordination centres responsible for all areas.
Situational.
As early as possible after confirmation by OCHA or the organisation coordinating the emergency response. If there have been long-term programmes in the country, there may already be some of this infrastructure in place.
Everyone at operational level, as they should first contact the focal point at the main coordination hub in order to understand the situation of the humanitarian coordination.
Humanitarian infrastructure maps may be used to inform decisions about the evolution of coherent coordination architecture for the emergency: for example by encouraging the co-location of coordination centres between sectors/clusters. Maps may also have the beneficial effect of stimulating the involvement of humanitarian actors in the coordination process, by communicating the locations of coordination centres and other hubs.
The map is usually updated several times during the emergency, so a simple MXD, ready to be re-loaded with more information, should be prioritised.
Create and maintain a point shapefile for all reported humanitarian infrastructure, to avoid inflexible one-off annotations of maps.
Check with coordination actors for authoritative and consistent terminology for coordination centres and use this to label maps accurately, as this can often otherwise be a source of confusion.
The information is typically provided by OCHA or another coordinating body. Close liaison is required to ensure that planned and actual changes are reflected in map updates.
Include locations of coordination hubs (OSOCCs, BoO etc.), distribution points, warehouses, etc.
There are many types of situational maps and these will be largely described in other sections of this guide. There however two types of situational maps - situation overview and who-what-where (3w) - that can be used to describe the overall response, as well has being the basis for thematic variations.
Globally natural disasters kill more women than men and often at a younger age (WHO 2014). Gender and age both matter in terms of who dies, are injured and whose lives are impacted in what ways during and after the crisis (Mazurana and Proctor 2015). UN Women (2022) report that global research has shown that women and children are 14 times more likely than men to be injured or die as a result of a disaster. It is important to understand who was most impacted by a crisis in terms of age and gender and the long-term impact that this may have on a society.
Even in natural disasters impacts are not even between men and women (Mazurana et al 2013; Hoare et al 2012). At the sudden onset of a disaster, impacts may differ due to the geographic distribution of the population at the time the disaster hits (Mazurana et al 2013). Beyond the immediate onset of the disaster, impacts also differ. Men, boys, women and girls may all experience the same phenomena during conflict or natural disaster, however, how they experience it differs as they have different physiology, are targeted and experience harm differently, they suffer different social, economic and livelihood impacts, have different roles in family and community, different livelihoods and access to cash, assets etc all of which impact their survival and recovery. In war for example, men are more likely to be killed in direct combat, but women more likely to be impacted and die from the wider impacts on limited food, water, hygiene etc. Men are more likely to be prioritised for food within household when it is scarce, but physiologically women are more susceptible to mineral and vitamin deficiency. Due to reproductive and caring roles they are also more vulnerable to lack of health care services (Mazurana and Proctor 2015). Mazurana et al (2011) report overwhelming evidence that a person’s sex and age lead to significant differences in accessing essential lifesaving services when experiencing natural disasters or armed conflict. Humanitarian situations also potentially expose people to different gender or age specific risks such as sexual and gender-based violence, forced recruitment and sexual exploitation and abuse, which need to be addressed (Streets, J et al 2013). Women also face increased risk of sexual and gender-based violence, as well as unequal assistance to needs such as shelter and food, increased workloads and a loss of economic opportunities (UN Women 2022). Existing power inequalities between men and women are also often exacerbated during a crisis (SIDA 2015).
It is important to avoid viewing gender as just about women as this creates its own bias (Hoare et al 2012). Due to historic and current marginalisation of women in many societies, gender analysis can sometimes be skewed towards privileging women and girls in the application of theory and analysis. This, however, limits the understanding of the relationship between men and women, which is a key component of understanding gender relations (Doss and Kieran 2013). Men and boys also have their own gender specific needs and failing to consider these has negative consequences (DARA 2011). While it is women and girls whose gender roles most commonly lead to constraints, men and boys are also influenced by expectations of masculinity (Sphere 2018). We therefore need to take care to ensure we consider, women, men, boys and girls (Mazurana and Proctor 2015).
Gender is socially constructed as a result of cultural, political and social practices that define different roles for women, men, girls and boys. (IASC 2018) Because gender relations are socially constructed, rather than natural they are not the same in every society, but taught, learned and absorbed, varying between and within cultures (Hoare et al 2012, IASC 2018). Understanding the cultural context, you are working in is therefore vital to properly collecting and interpreting sex-age disaggregated data (SADD) for programming decisions (Mazurana et al 2013). Care needs to be taken to ensure that programmes avoid stereotypes about gender division of labour, which may promote inequality. Done right, proper consideration of gender in programming should lead to reductions in equality (Hoare et al 2012). Age is also important to consider as gender roles change throughout the life cycle (Eklund and Tellier 2012). Unequal societal expectations and social norms can prevent women’s and girls’ voices from being heard and their needs being deprioritised as a result (FCDO 2018).
Examples from the response to the large earthquake in Pakistan in 2005 highlight the importance of understanding this cultural context. Understanding that most of the communities actively practices purdah meant that from the start facilities like separated toilet and bathing blocks were rapidly designed. However, during the same emergency response, a lack of understanding of the fear of honour killings meant that when rescue teams arrived in the Northern Rocky Highlands in Pakistan, even critically injured women refused to board the helicopters. While mostly Pakistani nationals, the all-male rescue teams did not realise that some communities practiced honour killings and that women risked being killed if they boarded a male staffed helicopter on their own. (Streets et al 2013).
The following section highlights some of the key questions ((taken from Street et al (2013) Gender-Age Marker toolkit) which should be considered when considering gender and age in humanitarian action. These acknowledge the need to understand the underlying cultural context and capacities of the population affected.
What roles do women, girls, boys, men and older people traditionally play and who controls resources in the household and the society? Do any gender or age groups in the society face discrimination – including in their ability to access humanitarian assistance – and are particularly vulnerable?
How does the crisis or emergency affect different gender and age groups and their roles in different ways?
What capacities do different population groups have for coping with, responding to, recovering from and preparing for future crises?
What specific needs do women, girls, boys and men of different ages have for assistance and protection?
Are there any specifically vulnerable groups or groups with particular needs that should be targeted for certain types of assistance? If the action intends to target only one or a few specific gender and age groups, what other groups might need to be involved as well and what would be the consequences of not involving them (e.g. tensions, stigmatisation, failure of objectives, etc.)?
Having already identified that men, women, boys and girls have different needs both before and during a crisis, that disasters impact groups differently and that inequalities exist pre-crisis the figure above stresses the importance of integrating gender equality into humanitarian response. Effectively humanitarian action cannot, however, be achieved without understanding the specific needs, priorities and capacities of all gender and age groups (IASC 2018). Integrating gender and age into humanitarian programming makes assistance more effective because it: better addresses specific needs of different groups of people; ensures equitable access to goods and services provided; improves targeting of assistance to the most vulnerable; better protects different individuals from negative consequences created by the crisis and reduces harm; empowers a representative range of people to be involved in the design and implementation of humanitarian action, making assistance more effective (Streets et al 2013).
Gender mainstreaming during a response is central to impartial humanitarian action. It means that the impact of policies and programmes on both genders should be considered at all stages of the programme cycle including planning, implementation and evaluation (FCDO 2018, ISAC 2018).
Having a gender programme from the start:
Considers how the crisis, policies and programmes may impact people differently according to their age and gender (FCDO 2018);
Provides a more accurate understanding of the situation;
Enables needs and priorities of the population to be met in a more targeted way, based on how women, girls, boys and men have been affected by the crisis;
Ensures that all people affected by a crisis are recognised and that all their varied needs and vulnerabilities are accounted for; and
Facilitates design of a more appropriate and effective responses. (IASC 2018).
The following section below provides a selection of case studies which highlight why consideration of age and gender matter for humanitarian programming.
During the cholera outbreak in Haiti in 2011 SADD revealed that more men were dying and fewer men were attending clinics than women. This led to the discovery that men needed more education on the symptoms and highlighted where men had been hiding their symptoms because they confused them with HIV, which had associated stigma. (Streets et al 2013).
There have been cases recorded (e.g. Eritrea) where a disproportionate number of male adolescents were acutely affected by undernutrition. These were demobilised fighters, separated from their families, and who were affected because they did not know how to prepare food (Streets et al 2013, Mazurana et al 2011). Understanding malnutrition by age and gender helps to highlight this group and understanding of the context helps to understand the reasons for the problem, thus enabling solutions to be developed.
In Pakistan 2009 a review of WFP food ration recipients identified 95% of registered men were collecting rations, but only 55% of women. This triggered further investigation that led to understanding the access constraints affecting women (Mazurana et al 2011).
In the Darfur region of Sudan it emerged that there was a clear link between collection of firewood and risk of rape. Earlier identification of the need for IDPs to collect firewood combined with the use of sexual violence as a weapon of war against civilian populations by the belligerents, should have led to earlier responses from humanitarians to put measure in place to reduce the requirement for firewood collection or put in place safer means for its collection (Mazurana et al 2011).
WASH service provision in Niger women were trained in good hygiene as it was understood that they were responsible for this within the home, however, the programme was initially unsuccessful as men were excluded from this education process, yet they controlled the resources and were not willing to invest in the water storage containers and soap needed. Only when hygiene promotion was extended to the men was there is a change in practices that reduced diarrhoea significantly. (Streets et al 2013)
It is not just after a disaster occurs that gender analysis matters, it is also important in anticipatory action. Integrating protection, gender and inclusion considerations into anticipatory action interventions is a crucial step in tackling the intersecting vulnerabilities that affect the delivery of humanitarian assistance. It also helps to ensure that any assistance provided does not exacerbate these vulnerabilities. These three factors should be considered at all the stages of the anticipatory action process, as they not only affect the type of assistance provided and where it happens, but also the target beneficiaries and modalities of early warning and delivery mechanisms (Karki 2022).
Sex- and age-disaggregated data (SADD) are an valuable part of gender and age analysis. They move analysis on to an in-depth understanding of the affected community’s sex and age profile and of the people accessing humanitarian services, leading to a more effective response and making individual gender and age related need more visible (Streets et al 2013). SADD also highlights how people are affected differently depending on their age and gender (UNDRR 2021). Disaggregated data is key for example when modelling differences in development, mortality and disease risk, allowing for more targeting of specific at risk groups (Eklund and Tellier 2012, Tatem et al 2013). Disaggregated data is vital for understanding vulnerabilities, needs and barriers to access during a humanitarian response (FCDO 2018).
Disaggregated data needs collecting at all stages of a crisis, before being analysed and interpreted accounting for context, then being used to effectively inform programming (Mazurana and Proctor 2015). Collecting SADD is important right from the start of Phase I of a response when baselines, tools and indicators are agreed. Early adoption of SADD is not only important for making data and findings stronger and more useful in early planning of programmes, but also increases the likelihood that SADD will be considered properly in later stages of the response (Mazurana et al 2011). While collection of SADD is improving there is still a lot of improvement to be seen.
While much guidance promotes use of SADD and gender analysis, its adoption is limited
While guidance tends to require collection of SADD and most people agree it is useful, in reality it is not collected or not collected well (Mazurana et al 2013; Benelli et al 2012). It is sometimes the case that SADD is collected at a local level, but when not available for all areas fails to be aggregated and reported (Eklund and Tellier 2012). Eklund and Tellier (2012) found that most articles mentioning male and female affected differently did not actual have any quantitative SADD behind them and instead were relying on qualitative data. While much of the literature debating the use of SADD was written around 2012, more recent articles and reports imply that the same challenges largely remain and that SADD is extremely limited and largely missing, especially in phase 1 of an emergency (ACAPS 2022, ACAPS 2016, data2x 2022, UNDRR 2021, WHO 2021).
Mazurana et al (2011) criticise the humanitarian system for not being evidence driven, suggesting that cluster leads (at least in 2011) did not show a strong interest in SADD and therefore it was not collected in the field. Because gender is not seen as a priority gender data are often lacking or of poor quality (WHO 2021). Governments often fail to prioritise SADD due to missing or inadequate policies (UNDRR 2021). Pezzulo et al (2017) identify that even basic demographic data often fails to be disaggregated below admin 1, despite the fact that there are large subnational heterogeneities within countries. There needs to be a better understanding of why gender and age matters and how it contributes to programming (Mazurana et al 2011). Other reasons cited for lack of collection of SADD included SADD being missing from disaster management templates (UNDRR 2021) and a lack of trained female enumerators within communities (ACAPS 2022).
There is a reported lack of understanding and expertise with regard to analysing, interpreting and using SADD (UN Women 2016, Mazurana et al 2013) and there is little point in collecting the data if it is not then used and analysed (Mazurana et al 2011). SADD can be complex to interpret and better formatting and presentation are needed to improve take up for programming decisions (Mazurana et al 2011). Where SADD is collected there are reports of inconsistent collection (FCDO 2018, Mazurana et al 2011), inconsistent data management (UNDRR 2021), and inconsistent analysis and use (ACAPS 2022, Mazurana et al 2011). There are also challenges associated with data sharing, with a lack of coordination and data quality concerns (UNDRR 2021). Data collected locally are also sometimes not shared or aggregated at a national level in a way that looses the SADD which was collected (UNDRR 2021)
It is commonly argued that “paying attention to gender issues may not be timely or practical on the ground”, i.e. the so called “tyranny of the urgent”. Evidence shows though, that considering the differences in needs according to sex and age is crucial for effective relief and lifesaving assistance. It will inform needs assessments and engage and empower beneficiaries.”
SIDA 2015
There is little dispute that there is value in accounting for gender and age during data collection, analysis and subsequent programming, yet still much potential to be expanded on in terms of putting regular collection, analysis and use of SADD and gender analysis into practice in a way that positively impacts programming.
Demonstrating and training on the benefits of SADD look to be key to ensuring effective adoption and use into the future.
CAGIR (2013) summarise some of the key considerations for gender analysis as:
collect info about men and women
collect info from men and women
make data collection context specific
budget for additional cost of collecting SADD
work with a gender expert early in the process to refine questions and methods
ensure confidentiality especially around sensitive topics
These show who (which agencies), are doing what (in terms of relief operations) and where they are operating, and are also known as 3W. As a response continues this can evolve into a 4W: who, what, where and when (time).
Normally strategic, though occasionally operational (e.g. urban search and rescue). Largely dependent on the scale and level of aggregation within the data.
Situational.
Operational 3W maps might be required during user search and rescue phases. Strategic 3W maps will be required as the clusters and overall coordination mechanisms ramp up. 3W mapping is usually intended as a tool to help decision-makers track and allocate resources, filling gaps and avoiding over-resourcing. It’s an essential planning tool in most emergencies.
Organisations - Governments (National or Local), UN, Clusters, NGOs, Donors and others;
Roles - Programme Managers and funders
The most commonly invoked rationale for 3W mapping is to identify gaps and overlaps in the relief effort and provoke the reallocation of aid as appropriate. A much more detailed discussion of the purpose of 3W mapping (from OCHA’s perspective) can be found here: OCHA 3W - Its Purpose Target Audience Scope and Products - V1 - May 2013. Note that cross-cluster 3W data is normally limited to recording ‘operational presence’ of agencies but is NOT expected to serve as a tool for monitoring volumes of assistance delivered.
Produce two versions that compliment each other and serve the audience:
Humanitarian presence - this is an overview map with a count of organisations or activities per administrative unit - See Liberia: Ebola Outbreak - 3W Humanitarian Presence (as at 5 Sep 2014)
Cluster specific - detailed mapping of cluster activities per administrative unit. See - Philippines Typhoon Haiyan (Yolanda): 3W - WASH (as of 03-Dec-2013). Large 3W datasets can be mapped using Data Driven Pages (ESRI) or QGIS Atlas.
Standardised 3W data formats are normally agreed by an information management working group at national level, with OCHA advising and providing templates. Compilation of 3W data is then normally done through clusters, and contributed to a master 3W matrix which may be online (e.g. a Google spreadsheet) at predetermined intervals: e.g. two ‘3W deadlines’ each week.
Good quality administrative boundaries and p-codes are required. These must be in agreement with coordinating body for the data to join, so use of the common operational and fundamental operational datasets is recommended.
Key to understanding the movement of both people and aid, transport maps are vital for responders in logistical roles. Knowing the location of airports and seaports is important as these will often act as distribution hubs, as well as receiving and storing aid. Roads will often be damaged during a disaster, so knowing what the conditions are like, combined with understanding the road network, helps to identify the accessibility of a settlement or location. Transport maps can help to understand disease transmission and/ or the movement of people.
Strategic and operational.
Basemap.
These transport maps can form the basis of many logistics maps, and so should be produced and distributed as early as possible.
Everyone, however anyone involved with logistics or assessments will be particularly interested.
Knowing how to get to locations is vital in needs assessments and the distribution of aid, therefore knowing the location of transport links is important. In scenarios that involve the migration of people, knowing the locations of these arteries helps to show where people might move to and from.
Maps being provided for logisticians should include road conditions such as surface type and width. Weight limits and widths of bridges are also important, as this determines the type of vehicles that can be used.
General
Logistics Cluster Geonode - includes airports, border crossings, bridges, roads, rail and seaports.
Natural Earth Data - basic transport infrastructure at a global level.
OpenStreetMap - general transport infrastructure at a global scale, and increasingly good detail at a local scale. Data is continuously updated.
Airports
Roads
Seaports
The ability to communicate with populations affected by disasters and emergencies effectively is key to understanding their needs. It is also important for communicating with the affected population about what is being done.
Strategic.
Baseline.
Where many languages are used and communicating with affected community about the response is important than as soon as the data can be obtained.
Anyone who is interacting with the local community, including assessment enumerators and broadcasters (usually community radio) across the operational area. The emergency telecommunications cluster will be interested as these maps may help to inform the best positioning of new infrastructure. Baseline products will typically be for international responders who are unfamiliar with the country or area. Most maps will be indicative of the language or languages spoken in the area rather than absolute, particularly when there is an element of migration.
For those communicating and interacting directly with the local community who need to know what language to communicate in. It may also lay bare a need to recruit local translators for an organisation or programme.
Language borders are likely to be fairly fuzzy as people may speak a mixture of languages. Where possible, also show some form of population or built up area data to give some context to the extents.
Language data e.g. Ethnologue
National census
Administration boundaries and settlements
Communication infrastructure
The CDAC Network
Infrastructure maps can be split into the country infrastructure (e.g. transport, electrical, telecommunications, hospitals, etc) and humanitarian infrastructure (e.g. humanitarian hubs, warehouses, coordination centres). In many responses the infrastructure of a country is likely to be damaged or under further stressed and will need supporting for the long term recovery.
These products show basic structures and organisational facilities within a country or affected area. Transport networks are key to represent, but also other facilities such as education, hospitals, fire stations, police, power structures, banks, etc. Many infrastructure products will become basemap or baseline products that can be used for assessments on which situational data will be overlayed.
Normally operational as it provides information about the coordination centres responsible for every area.
Basemap, baseline and situational.
If preparedness work has been done then the basemap and baseline products may already exist, although there may be some initial updating to be done. During the early stages of the emergency damage assessments will be carried out, and the status of infrastructure will be reported and may be updated frequently.
During any rescue phase, search and rescue workers. Emergency medical teams will be working with the national government to understand the capacity of hospitals, etc, so that they can be supported from the emergency phase onwards. Responders will be interested in their specialist vulnerability, e.g. those looking at education will be interested in the status and conditions of schools; logisticians in the capacity of roads, airports and seaports; and emergency telecommunications specialists in power supplies, or radio and mobile phone masts.
Damaged infrastructure has an effect on the population hit by the emergency, and will inhibit any response. Having an understanding of the status and capacity of buildings is important for any responder to provide the best support that they can give.
For pilots, understanding the topography is important as it may determine where they can fly, the route that they take and how they can take-off or land. They are particularly interested in the maximum height of major obstacles in the area, and peaks and valleys that can have an effect on weather conditions.
Products showing specific infrastructure themes will be important to those looking at specific vulnerabilities, and so it is important that there are individual products. Things should not however be looked at in isolation, and having some generalised products showing key infrastructure such as the main hospitals, government buildings and schools can be useful for everyone.
Buildings including hospitals, schools, government buildings, areas of industry, power, etc.
Transport networks - roads, rail, airports, seaports.
Baseline population.
Reference
Population
Situational awareness
Infrastructure
Situation overview
Humanitarian presence
Baseline population
Affected population
Gender
Languages
Population displacement
Critical infrastructure
Humanitarian infrastructure
