Sadd report draft_2008-dec-10

Inter-Agency Standing CommitteeGender Sub-Working Group

Sex and Age Disaggregated Data in Humanitarian ActionSADD Project

Draft Report

December 10, 2008Prepared by The Canadian Society for International Health

Team Leader: Janet Hatcher Roberts Consultants: Lorna Bailie, Madzouka Kokolo

DRAFT IASC Sex and Age Disaggregated Data in Humanitarian Action

Table of Contents

Table of Contents 2

Acknowledgments 4

Executive Summary 5

Goals of the Study and Methodology 8

Scope and Objectives of Study 8

SADD Activities 9

Caveats 10

Cluster Approach: Impact on Information Management 11

Levels of Information Reporting 13

Data Needs Correspond with Emergency Phase 14

Primary and Secondary Data Sources 17

Data “fit for use” 18

Country Specific Review of Data and Information 19

Iraq 19

Myanmar 22

Uganda 23

Detailed Findings 27

I. Gender awareness, understanding, and knowledge transfer requires constant reinforcement at all levels to ensure the consistent collection of age- and sex-disaggregated data. 27

II. Age information is slanted towards children – what about older persons? 28

III. Strengthening information management is an important step towards the improved collection of age- and sex-disaggregated data. 30

IV. Having the right data at the right time is critical in emergency settings. 33

V. Age- and sex-disaggregated data collection and analysis must be grounded in statistical methodologies that follow standard procedures 35

December 10, 2008 Page | 2


VI. Information about age and sex information is not being analyzed and used to its full potential 37

Recommendations 38

Roadmap to Implementing Recommendations 42

Appendices (found in separate document) 43

Appendix I. List of individuals interviewed as part of SADD project 43

Appendix II. SADD compliance indicator for Work plans, Guidelines and Tools 43

Appendix III. Inventory of data and information referenced for Iraq 43

Appendix IV. Inventory of data and information referenced for Myanmar 43

Appendix V. Inventory of data and information referenced for Uganda 43

Appendix V. Cluster specific report 43

Bibliography 43



Acknowledgments

The Sex and Age Disaggregated Data Project Team (SADD), managed out of the Canadian Society for International Health, would like to thank the overwhelming number of individuals and organizations that supported the Project and contributed to this evaluation. SADD met with representatives from the Global Clusters, OCHA, as well as other agencies. Thanks so much for your time and patience in helping us get the right information.

Special thanks to Dr. Henia Dakkak, co-chair of the IASC Gender Sub Working Group. Other key informants contacted include Ms. Kate Burns, Senior Policy Officer, Gender Equity Policy Development Studies Branch, UNOCHA; Brendan McDonald, Manager Field Information Services Unit, OCHA, and Samson Bongsuiru Lamlenn, Technical Advisor, Data in Crisis Situations, Humanitarian Response Branch UNFPA. These individuals provided much needed advice and guidance on the project.

The SADD Project Team was comprised of Janet Hatcher-Roberts, Executive Director, CSIH; Madzouka Kokolo, Consultant, Administration and Logistic Support; and Lorna Bailie, Consultant, Statistics and Information. Thanks also to Dr. Nenette Motus, IOM; Ms Elizabeth Pender, UNFPA; and Ms. Siobhán Foran, ex-GenCap Gender Advisor, for providing insights from their on–the-ground perspective.



Executive SummaryThe Canadian Society for International Health (CSIH) was contracted through the United Nations Population Fund (UNFPA), on behalf of the IASC Sub-Working Group on Gender and Humanitarian Action, to conduct a desk audit of Global Clusters’ use of age- and sex- disaggregated data to support humanitarian actions during emergency situations. Sex and Age Disaggregated Data in Humanitarian Action (SADD) was the official title of the project, which was steered by the IASC Sub-Working Group on Gender, co-chaired by Dr. Henia Dakkak, UNFPA, and Claudia Garcia Moreno, WHO.

SADD originated from concerns that sex- and age-disaggregated data have not been used to their full potential to inform humanitarian interventions. In the best interest of all beneficiaries, including women, children, and older persons, those facing vulnerable situations or having unique needs must be accurately documented. Leaving information gaps related to sex and/or age could restrict or hamper critical decision-making during humanitarian response to emergency situations.

“Taking gender issues into consideration in planning and implementing emergency responses is not only a question of protecting the human rights of the persons affected. It is also a means to make emergency aid more effective”. (Dr. Henia Dakkak)

The Canadian Society for International Health (CSIH) is a national, non-profit, non-governmental organization committed to the promotion of global health and development. Its mission is to lead in mobilizing knowledge and resources to facilitate innovation and excellence in global health, both in Canada and internationally. CSIH was funded by the UNFPA to undertake the SADD Project.

Six important findings were identified during the SADD research and are summarized in the following paragraphs.

I. Gender awareness, understanding, and knowledge transfer requires constant reinforcement at all levels to ensure the consistent collection of age- and sex-disaggregated data.



There exists a broad understanding and acceptance of the importance of collecting age- and sex-disaggregated data to appropriately inform decision-making. This is very evident at the global cluster level, but is less clear at the country and regional levels. The data collection tools used depend largely on the preferences of the country team. The importance of age- and sex-disaggregated data is not well reinforced at the higher levels and there is often a lack of statistical expertise within the teams to transform data into meaningful information. Knowledge transfer from the global level to the country level therefore needs to be strengthened.

II. Age information is slanted towards children – what about older persons?

There needs to be a harmonized definition of children, and priority given to information about older persons.

The cluster program objectives determine the extent to which age-disaggregated data are compiled. There is no harmonized definition as to what age range constitutes a “child”, but most programs at least distinguish children’s needs from those of adults. Data is not usually disaggregated by single years of age, and age groupings are often not comprehensive. This limits the data’s usefulness across programs.

Data to support the needs of older persons is not a priority. According to Susan Erb, Age Specialist, Policy and Program Advisor, UNHCR, the Protection Cluster has just started developing guidelines for assessments of older persons -- but they remain vague. For instance, in practice, data is not disaggregated by age beyond 49 years of age. This is a problem, particularly because 99% of older persons in humanitarian situations are child caregivers, and many are economic contributors to the family.

III. Strengthening information management is an important step towards the improved collection of age- and sex-disaggregated data.

The consensus of cluster representatives is that while there has been a great deal of technical advancement around information management, the cluster approach has not kept up. More work is needed to harmonize concepts, influence data collection standards, and strengthen data interpretation skills. The extent of the affected countries’ data holdings and statistical expertise determines the breadth and depth of the data made available. Collaboration among humanitarian players goes a long way towards improving information. Although the SADD mandate was limited to evaluating the use



of age- and sex-disaggregated data, broader information management issues are a contributing factor to the minimal level of age- and sex-disaggregated data being collected and appropriately analyzed for decision-making. IV. Having the right data at the right time is critical in emergency settings.

At each stage of an emergency, it is important to put relevant, reliable data into the hands of those who need it. The level of disaggregation required depends on the phase of humanitarian relief and the nature of the intervention. However, collecting data for data’s sake is not acceptable. Rather, having reliable, relevant, and timely information can be achieved through strategic planning and advanced thinking to identify the questions that need answers and what data is required to answer those questions.

Initial assessments call for baseline numbers of affected populations to establish the magnitude of funding required. During an initial response, decision-makers may not recognize the need for details about the sex/age structure of the population. It is also not practical to administer a detailed age- and sex-focused questionnaire in every situation. However, having age- and sex-disaggregated data is often crucial for focused relief delivery over the longer term.

As the emergency unfolds, program specific information is required to identify priorities and assess the impact of the interventions. As such, advanced thinking of information needs and how information will be used to inform program decisions must take place prior to data collection. In parallel, data collection methodologies can then be developed that are practical, feasible, and address the identified information needs.

V. Age- and sex-disaggregated data collection and analysis must be grounded in statistical methodologies that follow standard procedures

This desk audit clearly found that during the early phases of initial assessments, data collection exercises do not collect disaggregate data on age and sex. This must be distinguished from the issue of being able to collect the data. The challenges of early emergency settings, combined with political and security issues, can complicate and delay data collection.



However, there is no evidence to suggest that such issues should prevent the collection of age- and sex-disaggregated data.

The breadth and depth of data collected increase as the emergency setting stabilizes—but this is not standard across all programs or emergencies. There are a variety of data collection tools being used with little or no harmonization of methodologies, strategies, or conceptualization.

VI. Information about age and sex is not being used to its full potential.

Even when data are collected, there is often a weak link between the data analysis and interpretation. Aggregated data is often the most practical to use because disaggregated data requires specialized knowledge and expertise for its interpretation. For example, age- and sex-disaggregated data interpretation requires the expertise of gender specialists and statisticians. These skills are not readily found in the field of humanitarian actors. It takes time and skilled resources to collect and interpret findings to support program decision-making.

Goals of the Study and Methodology

Scope and Objectives of StudyIn December 2005, the Inter Agency Standing Committee (IASC) designated global cluster leads for eleven sectors or areas of activity to strengthen field responses to emergency humanitarian relief. At the global level, the aim of the cluster approach is to strengthen system-wide preparedness and technical capacity by ensuring that there is predictable leadership and accountability.

In 2006, the IASC Principals converted the IASC Gender Task Force into the Sub-working Group on Gender and Humanitarian Action and agreed to support the integration of gender as a crosscutting issue into the Cluster Approach.

In 2008, the Canadian Society for International Health (CSIH) was contracted through the United Nations Population Fund (UNFPA), on behalf of the IASC Sub-working Group on Gender and Humanitarian Action, to conduct a desk



audit of Global Clusters’ use of age- and sex-disaggregated data to support humanitarian actions during emergency situations.

The main focus of the audit, entitled SADD (Sex- and Age-Disaggregated Data in Humanitarian Action), was to determine how sex- and age-disaggregated data are being used in support of humanitarian actions during emergency situations.

Using an existing range of assessment activities undertaken during the sudden onset or protracted complex emergencies or natural disasters, the objectives of this study were to:

1. Analyze the obstacles and gaps in the collection, analysis, reporting, and use of sex- and age-disaggregated data in emergencies; and

2. Identify how these obstacles and gaps could be addressed.

SADD ActivitiesThe project’s terms of reference evolved around four specific activities as the means to compile and analyze relevant details and information.

1. Consultative meetings

The project was officially launched the first week of August through meetings in New York held with Dr. Henia Dakkak, co chair of the IASC /Gender Sub Working Group and other key stakeholders.

2. Interviews with Cluster and Agency Experts

Face-to-face meetings were held with representatives from seven of the eleven clusters. Most of the meetings took place in New York and Geneva. Contacts included cluster leads, information managers, and gender specialists. Representatives of the Agriculture, Education, Emergency Telecommunications, and Logistics Clusters were not interviewed. In addition to interviews with Clusters representatives, meetings were also held with other agencies and on-the-ground experts. (Refer to Appendix I for the list of contacts interviewed).

3. Review of data collection and data management tools, including gender specific guidelines



The Clusters and other agencies have all developed guidelines and training for data collection and analysis. Some of the tools are cross-cutting while others target a specific program or special population group. Documents relevant to the collection and use of age- and sex-disaggregated data were compiled from interview sources as well as the Internet. A list of relevant documents is found is Appendix II.

4. Review of data and information used in recent emergency operations

Data, reports, analysis, and collection tools specific to the 2008 Myanmar Tropical Cyclone, the 2006 conflict in Uganda, and the 2006 conflict in Iraq were examined to determine when and how age- and sex-disaggregated data were collected and used. These three events enabled the project team to explore both ongoing emergencies and sudden onset emergencies, and were good examples of effective cluster group approaches to humanitarian interventions. Country-specific findings are discussed later in this document.

CaveatsThe SADD project addressed on-going as well as sudden onset emergency situations, wherein the cluster approach was used to coordinate humanitarian interventions.

The review of age- and sex-disaggregated data addressed only two of the broader set of gender initiatives: 1) collecting data about the differences between women’s and men’s experiences, and 2) using the information to guide programs.

Building the inventory of relevant reports, guidelines, and data was restricted to documents found on the internet and/or referenced by the persons interviewed. For privacy and confidentiality concerns, it was not realistic to find micro-level data on the internet. However, questions specific to age and sex found in the data collection tools did indicate the existence of micro-level data. At the same time, there was very little reference to country-specific data on the internet.

Conducting emergency site visits was not part of the mandate of this phase of the project. A few country representatives were interviewed and three country sites were reviewed. Further work is required to discern how information is being collected and used at the country/local level and how this varies across countries.



Representatives of seven of the eleven Clusters were interviewed. Representatives of the Agriculture, Emergency Telecommunications, and Logistics Clusters were not included in the study.

Cluster Approach: Impact on Information ManagementThe Cluster Approach, initiated in 2006, is being used to coordinate responses to emergencies in many but not all countries. According to the IASC Task Team on the Cluster Approach, as of May 2008, fifteen of twenty-six countries with humanitarian coordinators were formally implementing the cluster approach.

The SADD team members conducted face-to-face interviews with seven clusters. The discussions focused on their intended and actual use of sex-and age-disaggregated data for decision-making, and the issues faced in collecting and using these data. The eleven global clusters (sectors) and lead agency are identified below.

Area of Activity Sector or Global Cluster Lead

Technical areas:

1. Nutrition UNICEF

2. Health WHO

3. Water/Sanitation UNICEF

4. Emergency Shelter UNHCR, IFRC

5. Education UNICEF

6. Agriculture FAO

Cross-cutting areas:

7. Camp Co-ord. /Management UNHCR, IOM

8. Protection: UNHCR/OHCHR/UNICEF

9. Early Recovery UNDP

Common service areas:

10. Logistics WFP

11. Emergency Telecommunications OCHA/UNICEF/WFP



At the onset of an emergency, the Humanitarian Coordinator, in close consultation with the Humanitarian Country Team, is responsible for securing the appropriate sectoral groups based on a preliminary needs assessment.

Information management takes place on two levels.1 Intra-cluster coordination is the responsibility of the cluster leads; the Clusters identify the data that they need to support their program objectives, and typically carry out qualitative and quantitative studies to generate that information. The second information management level is the inter-cluster level, for which responsibility is assigned to the UN Office for the Coordination of Humanitarian Affairs (OCHA). OCHA supports information management through Humanitarian Information Centers (HIC), and provides guidance on the use of information tools. OCHA has created an operational 3W database (who-where-when) that holds information about the humanitarian activity. The database includes the number of beneficiaries but no characteristics about them. OCHA is also mandated to establish an Information Working Group at the country level, in order to coordinate information management activities and to support the various clusters and sectors.

The governments of the affected countries and local agencies play an important role in providing relevant information. Census of populations, country-specific health surveys, and ongoing mainstream data collection can be used to provide essential baseline information. The International Federation of Red Cross (IFRC), WHO, UNICEF, and other agencies also provide valuable local data collection expertise that is used for program-specific evaluations and surveys.

The most recent Cluster Approach Evaluation found that the cluster approach has increased demands for information management. “In reality by increasing and improving information flows, clusters have actually reinforced the need for stronger inter-cluster information management and overall situation analysis…” (Dr. A. Stoddard, 2007).

With the cluster approach, there are many actors involved in identifying and addressing the complex information needs. However, the development of a system to collect, analyze, store, and share information has not progressed as required. There is duplication of effort in data collection and little harmonization of concepts and questionnaires. There is no central depository

1 Operational Guidance on Responsibilities of Cluster Sector/Leads



to facilitate data sharing. There is also a lack of technical skills to support questionnaire design, data collection, and analysis. Although the SADD project mandate was limited to evaluating age- and sex-disaggregated data, the broader information management issues must be considered as both an opportunity and impediment towards finding solutions for improved age- and sex-disaggregated data.

Levels of Information ReportingThere are three levels for information reporting during emergency relief. The levels are:

1) Global-level information supports system-wide preparedness, capacity building, and leadership. Information is summarized at a very high level.

2) Affected countries require specific details to ensure a coherent effective response. The levels of disaggregation describe the regions and people located in these regions.

3) Regional-level expands further on affected site details, including micro data specific to households and communities as well as contextual information on culture, ethnicity, religion etc.

Data Needs Correspond with Emergency PhaseIn addition to the reporting levels, information needs evolve throughout the phases of a humanitarian emergency response. Data collection is an iterative process that begins with existing baseline information from secondary sources. As the emergency unfolds and information needs become more defined, there are opportunities to increase the breadth and depth of information provided through targeted data collection. For the purposes of this study, four different information needs associated with the phases of response were established.

1. Pre-crisis and contingency planning information (baseline data)

2. Initial cross-sectoral investigation (including Flash Appeal 1-2 days and then revised 5-10 days)

3. Rapid inter sectoral assessments (3-5 weeks)

4. In depth cluster/agency specific assessments (8 weeks and beyond)



At the onset of an emergency, there is an urgency to get as much information as possible. However the challenges found in emergency settings do not create ideal data collection situations. In the case of a protracted complex emergency, there is more time and opportunity to collect data and to analyze the information. Collecting relevant data at the most appropriate time using the most appropriate methodology is very important.

Sometimes information needs are not properly thought through. Asking for detailed age- and sex-disaggregated data early on in a crisis situation may not be reasonable or practical. There is a saturation point for information and it takes specific skills to accurately interpret and use data.

The OCHA Assessment and Classification of Emergencies Project (ACE), led by Alexis Hoskins, is developing a common framework for needs assessment2. ACE produced an inventory of the variety of different assessment tools being utilized at the different phases of an emergency, and makes the distinction between rapid assessments and in depth assessments. The ACE findings point to the lack of harmonization across clusters in both concepts and data collection tools. ACE conceptualized needs assessments according to emergency timelines.

2 OCHA Assessment and Classification of emergencies (ACE) Project. Mapping of Key Emergency Needs Assessments and Analysis Initiatives, Consultation Draft, November 2008.



Along the same theme, the Global Protection Cluster Working Group prepared a document entitled Guidance on Profiling Internally Displaced Persons (see below). The document is an excellent reference on appropriate data collection methodologies depending on the emergency phase.





The SADD project review and assessment assumed that requirements for age- and sex-disaggregated data become more detailed through the phases of an emergency. It also assumed that there is a core set of information needs that are common across clusters. A final assumption was that clusters have information needs that are unique to their program objectives. The SADD project evaluation framework considered data uses, along with appropriate collection methodology, resources, and time constraints.

Primary and Secondary Data SourcesImportant to the SADD project was the distinction between primary data sources (survey data collected and used for the intended purpose) and secondary data (collected for other purposes such as administrative records, census of populations). Secondary sources are used for contingency planning as well as the very early appeals.

The Inter-agency Contingency Planning Guidelines assists Humanitarian Country Teams to prepare for potential emergencies. The document urges country teams to develop projections of humanitarian needs using existing baseline data. The guidelines also encourage countries to prepare strategies for initial assessments, including agreements on specific rapid assessment tools and discussions about how cluster information would be collated and shared with others. The guidelines do not explicitly mention the need for age- and sex-disaggregated data.

OCHA supports information needs for the pre-planning and initial stages of an emergency through the use of country-specific secondary data sources such as population census, health surveys, and administrative records.

As an emergency progresses, clusters and agencies conduct surveys and focus group studies to obtain detailed information relevant to their program needs. The primary sources of information (key informant and household surveys and focus group studies) were of particular relevance to the SADD project because sex- and age-disaggregated data could be included as part of these studies. This is not the case with secondary sources, where the data has already been collected for an intended purpose, which may or may not have required age- and sex-specific data. The second issue with secondary data is gaining access: the data are owned by those mandated to collect the



information and gaining access to micro data may contravene requirements to keep data private and confidential.

Data “fit for use”A sample of the information tools, guidelines, and data from clusters - as well as from three specific emergencies (Myanmar, Uganda, Iraq) - were compiled and evaluated in terms of “fit for use”. Rather than having data for data’s sake, the “fit for use” looks at the use or functionality of data. The “use” is determined by the emergency phase as well as the nature of the program response.

The “fit for use” methodology is taken from data quality management principles used by Statistics Canada and other information experts 3. Although there are variations to the elements of data quality, they typically include relevance, accuracy, timeliness, accessibility, interpretability, and coherence. The quality elements are overlapping and interrelated, so there is no single measure of accuracy.

Achieving an acceptable level of “fit for use” is the result of managing and balancing priorities such as cost, time, and the conditions and circumstances under which data are collected and used. The SADD project did not call for a data quality evaluation as such. However, the “fit for use” model was adapted and used as a basis for discussing data needs and uses with the various stakeholders, and more importantly, understanding the limitations and realities in collecting and using these data.

Country Specific Review of Data and Information

Iraq

BackgroundOngoing violence in Iraq has created difficulties for aid delivery and is preventing millions of people from accessing essential services. Recent UN estimates indicate that four million Iraqis are in urgent need of food

3 Statistics Canada Quality Guidelines, Fourth edition, October 2003



assistance and only 40 percent of the Iraqi population has reliable access to safe drinking water. One-third of the population is cut off from essential health care and necessary medication. Between 4 and 9 percent of children under the age of five are suffering from acute malnutrition. The civilian death toll remains high, with an estimated 151,000 violent deaths occurring between March 2003 and June 20064. The SADD project team identified Iraq as an example of an ongoing emergency managed through a remote control strategy.

The Cluster Approach has not been formally activated in Iraq, although interagency workshops on the cluster approach have taken place. Recent country-level reforms have adapted and implemented working methods to facilitate the incorporation of major elements of the approach.

Although Iraq is not officially using the cluster-based approach, there has been a similar humanitarian structure in place for several years, in the form of Sector Outcome Teams (SOTs). This structure corresponds more or less to the standard sectors defined through the humanitarian reform. Three SOTs stood out as being proactive in gender matters - Protection, Education, and Health/Nutrition.

Collaboration between agencies and the local government has helped to improve the overall situation related to information management. The original HIC (Humanitarian Information Centre) for Iraq was handed over to the Iraqi Central Organization for Statistics and Information Technology (COSIT) in 2004. The HIC products and services that supported humanitarian coordination were transferred to UN Assistance Mission for Iraq (UNAMI). The Central Organization of Statistics and Information Technology (COSIT)5 and the equivalent office in Iraqi Kurdistan (KRSO) are the two main Iraqi governmental structures managing population data.

The Inter-agency Information and Analysis Unit (IAU) is composed of analysts from different participating UN agencies and NGOs in Iraq. The IAU was formed in early 2008 to improve the effectiveness of the humanitarian and development response through the strategic use of information. A GenCap Gender Advisor has been deployed to the IAU to ensure that a gender perspective and analysis is included in all of the Unit’s work.

4 UN General Assembly Economic and Social Council – Strengthening of the coordination of emergency humanitarian assistance of the UN: Report of the Secretary General June 9, 20085 Website: http://cosit.gov.iq/english/index.php


http://cosit.gov.iq/english/index.php


Data sources reviewed The data collection tools reviewed include: UNICEF Multiple Indicator Cluster Survey (2006), IRAQ Family Health Survey (WHO), and the Iraq Living Conditions Survey (2004). In addition, UNHCR has completed many assessments of displaced persons using similar tools.

COSIT and the Ministry of Planning and Development Cooperation collaborate with other agencies to collect and use data in support of humanitarian interventions. However, there is some concern that data collected by local authorities were not always made available to the agencies. See Appendix III for list of documents referenced.

Ms. Siobhán Foran was the GenCap Gender Advisor appointed to UNAMI and then OCHA between February and August 2008. Gaps in sex- and age-disaggregated data have been identified and presented in three different reports prepared by Ms. Foran. Although she indicated that reporting is getting much better, there is still a long way to go. Time restrictions for the SADD project did not allow for communications with other agents involved in Iraq, namely Mr. David Shearer (Humanitarian Coordinator), Francine Pickup (OCHA officer), and Deborah Clifton (current GenCap Advisor).

Key Findings A review of recent data collection and needs assessment for Iraq found that they do include age and sex content. Most of the data collection used household questionnaires.

According to Ms. Foran, UNICEF consistently uses sex- and age-data for targeted interventions. UNICEF collected sex- and age-disaggregated data on primary school children and used those data to improve access to education for all kids. For this, they looked into stratified data on the use of sanitation. Observed imbalances between the sexes were considered in the development of targeted programs. However, WHO missed opportunities to use sex- and age data that had already been collected. For example, their analysis of inoculation data is not very useful for gender-specific interventions. Some of the other findings from the interview with Ms. Foran included the following:

Age-disaggregated data for older persons are commonly neglected but widows (young or old) represent a particular issue.



There is an absence of sex-disaggregated information in most of the project sheets in terms of analysis of needs and in the proposed activities’ expected outcomes and indicators.

While there are references to the collection of data related to gender-based violence (GBV) in health facilities, there is no mention of the development and use of protocols for the ethical research, documenting, and monitoring of GBV or of standard operating procedures for the care of survivors of GBV.

Quality and consistency and timeliness of data pose serious challenges.

IssuesThe political and cultural context in Iraq presents particular challenges for data collection efforts. The surveys being conducted are usually household-level surveys with the head of the household reporting on behalf of the other household members. According to the Iraq Family Health Survey Report 2006/07, more than 95% of the households are headed by males. The Family Survey has a separate questionnaire for a sample of adults in the household as well as a women- and child-focused questionnaire. It is difficult in general to approach and/or interview women alone (especially for a male officer).

Myanmar

BackgroundCyclone Nargis struck Myanmar on May 2 and 3rd, 2008, with winds up to 200 kph, sweeping through the Ayeyarwady (Irrawaddy) delta region and the country’s main city and former capital, Yangon (Rangoon). The area was declared a State Disaster and has a total population of 24 million.

The Office of the Resident/Humanitarian Coordinator supported the coordination efforts led by the Ministry of Social Welfare Relief and Resettlement, mainly through a response coordination team (RCT) and the Myanmar Information Management Unit (MIMU). MIMU is supported by a Humanitarian Information Centre (HIC). In addition, given the number of affected areas, coordination mechanisms were needed at the local level where the response was being conducted. The long-term information management capacity was strengthened in part through the establishment of the Myanmar information website: myanmar.humanitarianinfo.org



Data Sources Reviewed Reports and survey tools were gathered using both the internet site specific for Myanmar as well as discussions with individuals working on site. A list of the documents reviewed is found in Appendix IV.

Key FindingsOnly minimum baseline data was available . The most recent Population Census was conducted 1984; it was therefore problematic getting accurate estimates of the affected populations. Several initial assessments were conducted at same time, which created confusion and conflicting estimates. The Government of Myanmar restricted access to specific regions and all data collection activities had to have government clearance. According to document sources reviewed by the SADD project team, no sex- or age-data were included in the initial response phase reports. However, age- and sex data were reported during the rapid inter-agency assessment phase.

The Nutrition and Health Clusters had the most age- and sex-disaggregated data early on. The Mid-Arm Circumference Rapid Assessment of May 17 collected data by age and sex for each township. The Food Security and Water Sanitation Rapid Assessments conducted qualitative studies that included women participants as well as men; unfortunately, the assessment findings were not reported by sex. The Health Cluster Bi-weekly Situation Report contained some descriptive information referencing women receiving care, but provided no detailed data.

In-depth cluster assessments began with minimal age- and sex-disaggregated data being collected at the household and community levels. The Village Tract Assessment Tool and the Food and Nutrition Survey are good examples of more recent survey collection tools collecting detailed age- and sex-disaggregated data. The special report Women’s Livelihood Findings for Assistance- Labutta Twp. sourced focus group results and surveys with municipal representatives.Protection, Nutrition and Shelter Clusters provided the most concrete examples of age and sex being reported on and used for decision-making.

IssuesThe biggest issue identified early on was the restriction imposed by the government on access to specific areas. A second issue was the degree of the devastation and the difficulties faced in collecting data under these circumstances.



Uganda

BackgroundUganda is beginning its recovery from over two decades of war, a period which has seen more than one million people displaced from their homes, and many more lives and livelihoods disrupted or destroyed. It is also a country facing increasing risk of disaster, with areas prone to lawlessness and under-development.

Uganda, together with Liberia and DRC, was chosen as a pilot country for the cluster approach, and clusters were rolled out there in early 2006. Clusters are active across the Acholi-Land and the Lango and Teso sub-regions of Uganda, supported by national clusters in Kampala. The humanitarian clusters in Uganda support communities in crisis by providing emergency life-saving assistance, basic services, and protection for vulnerable populations.

Four UN agencies – FAO, UNICEF, WFP and WHO – have received nearly US$ 5 million from the United Nations Central Emergency Response Fund (CERF) to scale up urgent activities in Karamoja, where food and nutritional security remain a source of grave concern.

By May 2008, the prospective failure of a third consecutive harvest led partners to conclude that “the deteriorating situation in Karamoja is fast approaching a worst-case food security scenario”. As of September 2008, 707,000 persons (70% of the five districts’ population) were receiving food assistance. WFP predicts the situation will continue to deteriorate in Karamoja, with early indications that the population targeted for food distribution may rise to approximately 900,000 (80% of the region’s total population) by the end of the year. Further aspects of vulnerability can be seen in the migration of the rural destitute to peri-urban areas within southern Karamoja and to urban centers such as Kampala, Iganga, Jinja and Mbale.

Data Sources ReviewedThere have been several reports and collection tools used over the years. It was not feasible to review all of them as part of this desk audit and so a



sample of the most recent was selected. The list of documents reviewed is found in Appendix V.

Key FindingsAlthough there was less information pertaining to the kinds of data being collected than were found in the Myanmar review, many of the Clusters Reports indicated targeted program interventions that address children and women’s issues.

The Health and Nutrition Clusters are very active in monitoring malnutrition as well as the normal ongoing monitoring of chronic illness of children. Acute Malnutrition (GAM) rates in both Moroto and Nakapiripirit districts are approaching 16%. By June 2008, active screening of all children in the selected communities in Moroto District, using MUAC 1 and weight-for-height found measures, found that 740 of 6,489 children screened were identified as severely malnourished. While not statistically valid, the extremely high levels of severe malnutrition indicated a rapidly deteriorating nutritional situation in the region and the need for immediate action.

Child health in Karamoja is threatened by high levels of malaria and pneumonia amongst children under 5. The child mortality rate (almost 30%) is higher than the national average. According to UNICEF, some 90,000 children under 5 have not been immunized, while bed-net coverage in Karamoja households is only 3.4%.The Education Cluster’s objectives are to ensure equitable access to quality education for marginalized groups and children in emergency areas. The extent to which data are used to monitor and inform these initiatives is not clear.

The Protection Cluster has been very active in establishing and/or refining protection for older persons as well as for children. There have been initiatives to raise staff awareness on older person’s protection issues. The District Child Protection Monthly Tracking and Activity Report is used to monitor the prevalence of protection cases. This tool does report by sex and has some indicators specific to children.



The Protection Cluster has also created Child Friendly Participatory Assessment Tools, which provide helpful ways to gather assessment information from children. While there seems to be an intention to address the needs, risks, and priorities of both girls and boys, and there is an intent that boys and girls will map out a plan of action, there is no instruction or intent on the analysis of the experiences and discussion which disaggregates by age and sex. It would seem that there would be significant and relevant information discerned from this approach and it may be that such analysis occurs but it is not explicit in the tool kit.

The Gender Based Violence (GBV) Preparedness Plan for Uganda sets out goals to deliver a set of minimum interventions to prevent and respond to sexual violence that are in line with the IASC Guidelines for Gender-Based Violence Interventions in Humanitarian Settings. There is also a GBV Monthly Reporting Form to support agencies working in service provision. The GBV monthly reports disaggregate by age on some indicators but do not distinguish sex in the data collection form.

A 2007 Mortality and Morbidity Survey, supported by the Medair Uganda European Commission Humanitarian Aid, was conducted in Agago County, Pader District, of Northern Uganda. The survey produced age- and sex-disaggregated baseline data that has been valuable for planning, programming, and rapid assessments. The survey was a retrospective approach to the measurement of mortality and morbidity in 11 IDP camps (6 of which were satellite camps or resettlement sites). The mean recall period was 225 days from 1st January to 21st September 2007. A systematic random sampling method was applied in selecting the households and data was collected using a structured questionnaire.

An in-country assessment of the cluster approach conducted in 2006 included gender-based violence as part of work plans, but no other mention was made of gender specific activities. There was no specific mention on the success of gender or age as cross cutting themes within clusters.

IssuesAs with the other country-specific reviews, it was difficult to determine the extent to which age- and sex-disaggregated data were being collected at the local level.



A Help Age International 2007 Project that explored current humanitarian policies and practices responding to the needs of the older person, made some interesting observations about data collection objectives in Uganda: “Cluster agendas appear to be more reactive than proactive, preferring to look at what is easily measurable and achievable in the short term, without necessarily properly understanding underlying issues and longer-term solutions and impact”(Tom Okello, 2007).

According to this study, the needs of the older population were not considered until it was realized that they represented a huge proportion of the displaced persons. In other words, inventories of displaced people were either not collecting or using basic demographic information such as age to inform program planning.

Uganda was one of the first countries to adopt the cluster approach. An in-country assessment completed very early on suggests difficulties in implementing this new approach. Unfortunately, the assessment did not mention how data and information were being used.

Detailed Findings

I. Gender awareness, understanding, and knowledge transfer requires constant reinforcement at all levels to ensure the consistent collection of age- and sex-disaggregated data.

Awareness and acceptance of the importance of age- and sex data in informing decisions is very evident within the global clusters. Regular collection and use of age- and sex-disaggregated data is less prevalent at the country and regional level.

Dr. Nanette Motus, an IOM Regional Migration Health Manager, provided insightful feedback based on her experiences in Myanmar. According to Dr. Motus, ground teams are frequently changing and so co-coordinators must be consciously aware and promote the need for age- and sex data. During the first month of emergencies, there are usually expected ‘challenges’ as agencies begin to prepare and coordinate relief activities. Data first collected usually includes information focused on saving lives and meeting shelter needs. However, Dr. Motus reinforced the importance of early detection of



vulnerable groups – including women, children, the elderly, those with mental/physical special needs, and others.

The data collection tools of choice depend on the country and what local data collectors are used to using. In Myanmar, as in most emergencies, there were many aid relief workers waiting on standby at the Central Humanitarian Relief site. This would provide a good opportunity to reinforce field training on gender issues as well as improve collaboration and the sharing of data.

Technical working group meetings are held regularly during a crisis. One thing that worked well in Myanmar was having those who had gone into the situations come back and report to others about their findings. For example, individuals from the Protection Cluster working in the field reported back to the Technical Working Group about the issues they observed regarding gender-based violence.

Agencies’ emphasis on women’s empowerment rather than on gender equality, combined with cultural sensitivities in the Iraq context, made it difficult to emphasize the need for age- and sex-disaggregated data collection. When not appropriately understood, men can feel threatened, neglected, marginalized, or even demonized by such initiatives.

Interpreting age- and sex-disaggregated data to inform programs about gender dynamics is weak. Informed decision-making requires the combined talents of program expertise and statistical information specialists. Program experts, using the gender dynamic lens, identify information needs and relevance of the findings. Information specialists advise on the best methods to collect and analyze the data. Together they make sense of what the information means in terms of interventions. This combined expertise is rarely found in humanitarian country teams.

II. Age information is slanted towards children – what about older persons?

The objectives specific to each program determine the age range used to compile data related to children. There are, however, no harmonized definitions as to what ages constitute a “child”, even though most programs distinguish children’s needs from those of adults. The starting point for many indicators is the “number of children” affected.



The age categories collected and used vary according to the specific cluster needs. In the case of the Health Cluster, the initial morbidity and mortality assessments collect data by “age less than 5 and greater than 5”. The Nutrition Cluster focuses on children between 6 and 59 months. The Protection Cluster is most concerned about children aged less than 1 year and people under age 18 when living alone without parents.

Apart from agency/cluster program definitions, there are legal definitions to consider as well. For example, the Myanmar Child Law defines a child as a person who has attained aged 16 years. A youth is between the ages of 16 and 18. Early reporting for Myanmar did not use this legal definition, although some of the post-Nargis data collection did make the distinction. Collecting data by single years of age is not feasible in most settings; however, collecting data by narrow age groups that span all ages would allow clusters to derive their specific age categories.

Cluster program interventions are targeted towards helping vulnerable populations such as children. Therefore, most data collection asks about children in the household and communities. In contrast, data describing the situation for older persons is not so readily collected and used.

Data specific to the elderly are not as prevelent as they are for children. Susan Erb, Age Specialist, Policy and Program Advisor, UNHCR, described the Protection Cluster has just getting started in developing guidelines for assessments of older persons --and they still are vague. In practice, data is not collected for individuals beyond 49 years of age.. This is a problem, particularly because 99% of older persons in humanitarian situations are child caregivers. Many older people are economic contributors to their households and families either through paid or unpaid work. Assessments on economic well being should not be restricted to certain age groups, but should be more inclusive to ensure a comprehensive evaluation regardless of age.

The physical vulnerability of older persons is also a concern. Susan Erb suggested that assessments are inconsistent and data have little to no impact on the interventions. One of her examples was a situation where a large proportion of the households were headed by older women, and yet the program distributed 25 pound bags of rice. It was problematic for the older women to carry heavy sacs of rice to their camps.



III.Strengthening information management is an important step towards the improved collection of age- and sex-disaggregated data.

There is no consistent standard collection of age- and sex-disaggregated data that crosses clusters-- yet gender is recognized by all as a cross cutting issue. There have been attempts to develop tools suitable for a group of clusters such as WASH, Health and Nutrition; however none have been fully endorsed. The difficulties of establishing data collection and analysis best practices stem from the much larger problem around information management.

With the Cluster approach, there are many actors involved in identifying and addressing critical and often complex levels of information needs. In general, the system to collect, analyze, store, and share data and information has not progressed as required. The consensus from those interviewed is that data management throughout the cluster approach is a significant concern. Mr. Atle Solberg from the Protection Cluster Lead suggested that there has been a great deal of technical advancements around information management, but the cluster approach has not kept up. For example, there is no central repository or inventory of data. Data analysis expertise required to make sense of the data is weak-- especially at the country level. The questions needing answers are not thought through sufficiently to guide the identification of what data needs to be collected. Rather, data collection is often done in isolation of knowing how to apply the information for good decision-making.

Often clusters and organizations function in a stove pipe, repeating data collection that might have already taken place. Improved overall situation analysis could help draw attention to cross-cutting issues and a more standardized data collection system could help programs in different sectors identify problems affecting specific groups. (Dr. A. Stoddard, 2007). For example, water access information specific to women could be beneficial for those providing nutrition programmes and protection.

Lynette Larson, Author of Strengthening Humanitarian Information Management: A status Report, suggests that “...information managers can better support clusters/sectors in their needs assessments, rapid or otherwise, by providing guidance on survey design, technical advice on data processing and management, and technical support for production of



derivative outputs for general distribution” (Larson, Lynnette, United Nations Office for Coordination of Humanitarian Affairs, June 2007). The Information Officers found in countries typically provide excellent support in data management and computer technical expertise. However, they are not statistical experts. Statistical experts would ensure improved data quality through recommending appropriate data collection tools and sampling methodologies. The quality of the information being used for critical decision making is of upmost importance. There were few details presented as to the quality of the data being used.

The cluster approach was initiated in 2005. Therefore information-based decision making is still a relatively new concept in humanitarian assistance, and represents a fairly significant cultural change for humanitarian actors (Larson, Lynnette, United Nations Office for Coordination of Humanitarian Affairs, June 2007). The implications of this statement is that not all clusters have developed standards to address the cross-cutting issues such as gender.

Other examples indicating a lack of coordination and expertise include the OCHA Analysis of May 17 that attempted to confirm the size of the affected population in Myanmar. The report references the problem of reconciling data because five different rapid assessment forms were in use.6

One excellent example of collaboration on information gathering is the Tripartite Core Group that included UN agencies, ASEAN and Government of Myanmar. In Myanmar, a two pronged assessment following the cyclone was conducted, organized by the Tripartite Core Group (UN agencies, ASEAN and Government of Myanmar). The damage and loss assessment led by World Bank and Asian Development Bank provided a macro level assessment. The Village Track Assessment (VTA), with the participation of several cluster groups/agencies, worked together with local government and achieved further cooperation. The VTA collected household-level age- and sex-disaggregated data. This tool continues to be modified and used for post evaluation studies.

A more recent version of the VTA is a much improved tool as far as collecting detailed age- and sex-disaggregated data. Although the collection universe remains at the household level, the questionnaire includes a household member roster to report specific details for each person. These include age,

6 (B. McDonald, OCHA, May 17, 2008)



sex, education, economic activity etc. The new version of VTA collects retrospective information to determine the effectiveness of the interventions and unmet needs. Other clusters and agencies such as UNFPA, UNICEF, IOM, WHO were also doing ongoing collection and most were collecting age- and sex-disaggregated data.

The Myanmar Cluster Approach Evaluation recognizes the success of the Myanmar Information Management Unit. Among other things, this Unit developed inter-cluster planning tools and launched a Website as a central depository for information. This helped to prioritize townships and determine key indicators for monitoring progress. Nine out of the thirty key indicators has some reference to age or sex information.

UNHCR is in the process of developing tools for cluster reports at the country level. Tools such as ProGres and IDP profiling guidelines all promote the collection of age and sex data. UNHCR conducts annual registries of populations of interest in 50 countries. The Annual Statistics Report on the Populations of Interest contains demographic data by country, including age and sex.

The recent proposal to establish an IASC Task Force on Information Management has the potential to improve data collection and analytic expertise for all concepts, including age and sex. This IASC Task Force proposes to recognize information management as an academic discipline. Adopting scientifically sound data collection and analysis tools will go a long way to improving data quality. A second recommendation of the IASC Task Force on Information Management is to identify and promote a minimum set of information for each Cluster to facilitate data sharing across clusters. Identifying common information needs across data sets would improve coordination of data collection (OCHA, October 2008). The Gender Sub Working Group needs representation on the IASC Task Force on Information Management to endorse and facilitate the use of data disaggregated by age and sex in decision making.

IV. Having the right data at the right time is critical in emergency settings.

At each stage of an emergency, it is important to put relevant, reliable data into the hands of those who need it. Useful information can only be



achieved through strategic planning and advanced thinking about the questions that need answers and the data needed to provide those answers. According to many of the clusters consulted, the SADD project was pertinent from a problem-solving point of view - to show how data inputs can impact the effectiveness of interventions for beneficiaries. Data needs are specific to the phase and nature of a humanitarian intervention.

Initial assessments use baseline data to estimate the size of the affected population and to establish the magnitude of required funding. As an emergency unfolds, program-specific information is required to identify priorities and assess impact of the interventions. Typically flash appeals do not report age and sex. The flash appeal is intended to summarize the situation and launch the funding appeal. However, many of the persons interviewed spoke to the need for age and sex data in advance, even at the early appeal stage, to better plan for the next step.

According to the 2007 Cluster Approach Evaluation, the most common source of frustration concerned the lack of baseline data - especially disaggregated by sub-region and for the affected localities

In Myanmar for example, the last census was taken in 1984. These data would not be helpful in estimating affected populations from a 2008 earthquake. Regular health surveys are another source, but frequency of collection and data quality is very much dependent on the country. Available indicators for national surveys (MICS, DHS) are only valid at the level of the larger regions and cannot apply to specific localities affected by the crisis and the affected population

Elizabeth Pender, Gender Advisor, Office of the Humanitarian Coordination Myanmar, reports that a lack of sex- and age baseline data for Ponja proved to be a real weakness. The data gaps impacted Child Protection and Women’s Protection Stand Alone programming. According to Ms. Pender, data would have been particularly relevant in the immediate aftermath, specifically in regards to increasing availability of women’s protection funding. Ms. Pender indicated that although data gaps still exist some six months after, a lot of efforts are taking place to remedy that situation.

Dr. Bruce Cogill, Nutrition Cluster Coordinator, reinforced the need for baseline data. According to Dr. Cogill, there should be national or representative surveys or demographic and health surveys conducted on a



regular basis, before emergencies happen. He pointed out that during an emergency there is no interest in testing statistical hypotheses on program efficacy or effectiveness. The information priorities are “who is affected by what, where, and why”. This proposed solution largely depends on the affected country and its ability to fund and conduct regular surveys.

Ms Moran stressed the need to overcome the familiar “mantra” about “being too busy” to consider sex and age at initial stages of humanitarian crises. She felt that the inconsistent data collected and reported in early phases of crises could hinder the effectiveness of interventions subsequently implemented. According to Ms. Moran…”if critical data are collected too late into a crisis, the damage done can sometimes only be observed, as the opportunity to act on it has been missed”.

The SADD project team found that age and sex data is either nonexistent or not being used in the early stages of decision-making. OCHA reviewed the commonly used indicators in both CAP and FLASH appeals during 2008. Commonly used indicators - those indicators found more than 30% of the time - did not include any age- or sex-specific data. The indicators found less than 30% of the time included infant mortality, mortality rates by sex, number of children orphaned, percentage of women and children displaced, percentage of children with moderate malnutrition.

Reliable and accurate data collection requires a combination of program expertise --knowing what information is relevant-- and statistical technical skills --knowing how best and when to collect and compile data. The Health Cluster Guide- Draft for Field Consultants identifies a common information gap where Health Information Systems are inappropriate to the phase of response. The example sited was use of sentinel site surveillance rather than a population-based data in the early recovery phase.

Some of the assessment tools being proposed are too voluminous and impractical to administer--at least early on in the crisis settings. According to Dr. Motus, in Myanmar for IOM, it was suggested at first to use an inter agency rapid assessment tool 32 pages in length. The team responded that this was not feasible because the tool had to be translated into local languages and staff needed to be trained on how to use it. This would have taken time to do so and proved to be extremely difficult especially in the first few days of the emergency.



Both the Flash Appeal and Consolidate Appeal for Myanmar did not contain age and sex data. However as time progressed, age and sex data were collected. Dr. Motus reported that less than one month into the emergency (May 15-16), WHO asked specifically for the reports to include an age breakdown more expansive than the standard less than or greater than 5 years which is collected as part of their formal reporting template. IOM eventually included sex breakdown into its work.

The inter-sectoral cluster assessments usually reference aggregate age and sex data. The Myanmar data collection tools reviewed illustrates that as time passes and the emergency setting stabilizes, more in-depth targeted data collection for age and sex took place (see Appendix IV).

V. Age- and sex-disaggregated data collection and analysis must be grounded in statistical methodologies that follow standard procedures

The SADD project team found that data collections carried out early in an emergency setting generally do not include age- and sex-disaggregated data. The breadth and depth of collected age and sex data increases as the emergency setting stabilizes. There are no standard data collection tools being used for any of the assessments, and yet information needs for age and sex are common to most programs. The data collection tools of choice depend on the country and what local data collectors are used to using. Many different assessment tools are being used with little or no harmonization of concepts.

The political and security context specific to each country can impact data collection--however there was no evidence found to suggest it prevents the collection of age and sex detailed data. This desk audit clearly found that the early phases of initial assessments do not include age and sex—which must be distinguished from the issues of being able to collect it.

The frustration of not having or being able to access baseline information at the onset was clear. The breadth and depth of available data is country-specific, but further work seems necessary to at least develop an inventory of what has already been collected.

Data collection takes place at the community, household, and individual levels. Many of interventions are aimed at the household level (e.g. shelter, material assistance), and therefore this is the data collection universe most



often used. When data collection is at the household or community level, age and sex data are proxy reported. Proxy reporting means that the information is reported by the person answering the questionnaire on behalf of the household or community. The quality of data resulting from proxy reporting is not as reliable as self–reported data. The degree of data accuracy depends on the most knowledgeable person’s ability and willingness to provide information on behalf of others in the household or community. This can result in major biases of the reported information. Data collected at the household or community level is already an aggregation. One cannot derive individual information and it is difficult to verify the details.

Data collected at the individual level yields much better quality than household level reporting; however it is more time consuming and costly. In emergency situations, most individual data collections reflect coverage of individuals receiving programme assistance. This is not representative of the community population as a whole and excludes those needing assistance but not receiving it. .

VI. Information about age and sex information is not being analyzed and used to its full potential

There is a lack of statistical expertise combined with program knowledge to transform data into meaningful contextual information. Without fully understanding the importance and uses of the information, data collection becomes an operational exercise with no clear objective in mind. Aggregate data is often the most practical to use because interpreting micro data requires a knowledge and expertise that is not broadly held.

The lack of time and expertise to effectively use data was reiterated in the country-specific reviews for Myanmar and Iraq.

The study “Mission Report Gender Outcomes & Reflections – Aceh” completed by Linda Pennells, reports the following: “Many humanitarian actors allowed too-long gaps between rapid assessments, which gathered initial sex-disaggregated information, and the deeper analysis of social and gender issues needed to inform recovery programming.” According to Ms Pennells, the impact is that interveners jump into programming without having identified the gender dynamics.



Sharing of data across clusters and programs is problematic. According to one IOM agent involved in several crisis situations, there is often no baseline data made available to the first responding agents -- but it does exist. For example, in Myanmar, 10 million people benefit from medical programs but this administrative data was not leveraged as valuable baseline information.

The SADD project originated from concerns that information gaps on recipient’s sex and age could restrict or hamper critical decision-making during humanitarian response to emergency situations. Women and children are often more vulnerable in emergency settings and therefore their unique needs must be accurately identified and documented. Some examples of where better age and sex data could have or did make a difference are documented below.

The IOM staff in Myanmar requested a more detailed age breakdown than greater and less than five years. At first the medical teams were only monitoring the acute emergency or reportable conditions. However as IOM medical teams continued their service, other age related chronic conditions were being reported, such as hypertension. It would have been very informative to track the rates of hypertension by age groups to see who was most affected.

An observed but not documented situation in Myanmar concerned the demand for Depo Provera injections rather than relying on oral contraceptive or condoms. This was a need not quantified through any data collection.

There is a lack of scientific evidence as to the extent of the violence against women in Iraq.

A health clinic in Pakistan found that few women patients were accessing services. This was because most of the health care professionals were men.

Combined data for boys and girls on growth rates can negatively affect the provision of appropriate treatment. The Nutrition Cluster has recommended standards specific to sex. Often in rapid assessments, data are combined for boys and girls to facilitate work in field (source Dr. B. Cogill Nutrition Cluster Coordinator).



Recommendations1. Gender awareness training and knowledge transfer should be

targeted at all levels and be ongoing throughout emergency settings.

The cross cutting work of gender awareness through training and information must seize opportunities outside of emergency settings to reinforce best practices. 1.1. Gender technical experts need to be involved in the emergency operations to influence what data are collected and how they are used. There is a requirement to identify people on the ground, not directly involved in the day-to-day challenges, to be reminding, encouraging, and explaining the importance of age and sex issues.

1.2. Train coordinators, including Cluster leads, HIC staff, Humanitarian Agency coordinators in the field, UNCT, HC/RCs, disaster management team coordinators, etc., to consciously be aware of the need for age and sex data. The training should ideally be done before an emergency, and can be integrated into disaster risk management and planning.

1.3. Use the Central Humanitarian Relief Site where possible as an opportunity to reinforce field training on gender issues. This setting is conducive to improve collaboration and sharing of data and information.

1.4. Flyers or quick information sheets are suggested as a means for knowledge transfer to reach people on the ground.

1.5. Encourage information sharing through the technical working group meetings held regularly during the crisis. For example, observers in the field could report back to the Technical Working Group about the issues they saw related to gender-based violence and other issues.

1.6. Reinforce the need to establish reporting indicators specific to programs as identified by the IASC Gender Handbook in Humanitarian Action.



2. Information Management needs to be strengthened across clusters.

The Gender Sub Working Group can leverage opportunities within existing initiatives to harmonize collection and analysis of age and sex data and establish this as standard procedure.

2.1. The Assessment and Classification of Emergencies Project (ACE), being led by OCHA has created an inventory of assessment information needs. The Gender Sub Working Group must ensure gender specialists are working with the ACE project to a) improve the understanding and awareness on how the needs for age and sex data span clusters and b) work towards an assessment tool box that would standardize the collection and use of age- and sex-disaggregated data.

2.2. The Guidance on Profiling Internally Displace Persons is an excellent resource that promotes data collection best practice. The recommendations are appropriate for any population and should be adopted in the gender awareness and training efforts.

2.3. The recent proposal to establish an IASC Task Force on Information Management has the potential to improve data collection and analytic expertise across programs. The Gender Sub Working Group needs to ensure gender experts are well represented on the IASC Task Force and that the Terms of Reference endorse findings ways to improve the use of age- and sex-disaggregated data in program decision-making.

3. Harmonize the definition of children and collect data by comprehensive age categories.

3.1. Concepts and definitions for age-defined groups such as children, youth, older persons need to be harmonized. A review of program specific definitions and recommendations for harmonization should be done.

3.2. For information to be of use across clusters, age data should be collected by single years of age or narrow categories, so that programs can derive the age groups specific to their needs.

4. Prioritize and sensitize the importance of information about the older person.



4.1. The work of Age Specialists in UNHCR should be supported to transform intelligence about the role and importance of the older person.

5. Ground age and sex data collection and analysis in statistically sound survey methodologies that become standard procedure

5.1. Inconsistent data collected and reported in early phases of crises can hinder the effectiveness of interventions subsequently implemented. Therefore cluster response at the very beginning should be encouraged to collect age- and sex-disaggregated data.

5.2. Although data collection is difficult to achieve given the challenges faced during the early phases of a crisis, greater collaboration and data sharing across clusters could facilitate the activity. WHO quickly establishes surveillance and is often the first organization collecting data. Its data collectors are usually trained in health surveillance.

5.3. Sensitive data concerning individual needs should be collected directly from the person when possible, as opposed to being proxy reported. Although time and costs are major impediments to conducting face-to-face surveys, sampling individuals within a household for a follow up set of directed questions is one way to ensure data is collected directly for women and children. Qualitative studies are another affordable approach to ensure information is being gathered directly from women.

5.4. The Global Clusters in Geneva should take a leadership role in i) advocating field staff to collect age and sex data; ii) establishing a short list of information needs common across clusters; and iii) harmonizing efforts for gathering and using data that correspond with the emergency phase and the best time to collect. One information tool is utopia -- a coordination of data collection and analysis efforts is more realistic.

6. The importance and uses of age and sex data to inform gender issues must be further reinforced so that data collection becomes a clear objective rather than an operational exercise.

6.1. Country information teams need to be strengthened to include both statistical and program expertise. This combination of skills will help to improve the relevance and reliability of the information, and ensure it is accurately interpreted and used in decision making.



6.2. Examples are needed to illustrate both the implications and successes of informed decisions.

Roadmap to Implementing RecommendationsThe recommendations cover a wide range of activities and target a broad audience that spans the global, agency, and country-level establishments. Some of the recommendations are easily implemented while others require additional resources and long term investment. This next section brings together a list of immediate action items that could help guide the IASC Sub-working Group on Gender through the next steps. It will be very important for the Gender sub-Working Group to integrate these findings and recommendations with many of the other related projects being conducted out of the UN. The timing of the first four actions is a priority as they require integration with other activities that are currently underway.

1. Prioritize SADD results in terms of integrating with the tools currently being developed by clusters to ensure gender is being included.

2. Further explore the opportunities in working with the newly formed IASC Task Force on Information Management. The proposal addresses many of the issues highlighted in the SADD study. The Sub-working Group on Gender is encouraged to become an active participant providing the much needed support on gender expertise.

3. The ACE Project is another opportunity for the Sub-working Group on Gender to influence the development of age and sex data collection as standard practice.

4. The findings and recommendations from SADD project with respect to collecting and using age- and sex-disaggregated data should be reviewed by the E-Learning Project. The relevant aspects can be integrated into the learning tools.

5. The recently appointed GenCap advisor for the global level will be working with clusters on building awareness. This can be an opportunity to reinforce the use of appropriate collection tools that include age and sex breakdown.



6. Identify gender experts to review the SADD findings with each cluster, and together identify the relevant recommendations and determine how to fit them into future work plans.

7. Work with Agencies and Clusters to determine how to enhance field expertise and build the capacity to full fill the gaps identified in this review. Once the requirements have been quantified, the next step would be to build the business case to secure additional resources.

Appendices (found in separate document)

Appendix I. List of individuals interviewed as part of SADD project

Appendix II. SADD compliance indicator for Work plans, Guidelines and Tools

Appendix III. Inventory of data and information referenced for Iraq

Appendix IV. Inventory of data and information referenced for Myanmar

Appendix V. Inventory of data and information referenced for Uganda

Appendix V. Cluster specific report

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