03 Apr 2020

Data Should Drive COVID-19 Mitigation Strategies in Lower- and Middle-Income Countries

The current World Health Organization’s guidelines call for the public focus on handwashing, social distancing, communication with medical providers, and staying informed to help mitigate the spread of COVID-19. However, such guidance may be more aspirational than actionable for millions at risk of exposure to the virus in lower- and middle-income countries (LMICs) as revealed by recent Demographic and Health Surveys (DHS). DHS data from 2014 onward from more than 50 countries in Africa, Asia, and Latin America highlight the very different contexts for daily living in LMICs. These realities must be considered when developing country or context-specific strategies for reducing COVID-19 transmission.

Handwashing:

The basics required for handwashing (soap and water) are taken for granted by many but are not readily available for millions of people. In Burundi (2016-17 DHS), only 5% of households were observed to have soap and water for handwashing (among those where handwashing places were observed). Soap and water were present in fewer than 20% of households in Malawi, Ethiopia, Benin, and Mali (see chart). A location for handwashing with soap and water was found in fewer than half of households in 21 out of 36 recent surveys for which The DHS Program has this information.

Household Size and Sleeping Arrangements:

Messaging about social distancing in the current pandemic focuses on staying home and reducing contact with people. In LMICs, self-quarantining to individual households and nuclear families may not be a particularly useful concept.

Households in Sierra Leone, Tajikistan, Guinea, Pakistan, Afghanistan, and Senegal are the largest, with six or more members on average. The ability to distance from sick or vulnerable family members within the household is crucial, but in many households sleeping quarters are crowded. Households in Pakistan, Madagascar, Ethiopia, and Cambodia have the highest average of people per sleeping room, at three or more.

Household Age Structure:

A recent article in the Hindustan Times pointed out that multi-generational households in India might be a risk factor for coronavirus transmission to the elderly. The 2015-16 India National Family Health Survey (India’s DHS) reported that 4 in 10 Indian households are non-nuclear families, many of which are multi-generational. This type of family structure makes social distancing, especially for the elderly, very challenging. When younger children go to school, or working-age adults go to work, they return home to multi-generational families in which the elderly are particularly vulnerable to coronavirus. While the proportion of population age 65+ in DHS countries is not large, there are some key things to note, particularly within the context of multigenerational households. In recent surveys, on average, about 5% of the population is 65+, but in countries like India (6.6%) and Indonesia (6.2%), these seemingly small percentages correspond to many millions of people due to population size.

Explore these data in STATcompiler

The DHS Program’s STATcompiler allows users to create custom tables, charts, and maps from 1000s of indicators across 90 countries.

Just this week, the STATcompiler has been updated to include new indicators to help contextualize the COVID-19 crisis in DHS countries, and two “COVID19” tags have been added to help users identify these indicators. Explore data on handwashing, sanitation, household size, sleeping arrangements, access to media, spousal violence, and more. Other relevant DHS indicators on household age structure, access to internet and cell phones, and tobacco use will be added in the coming weeks.

COVID tags

Select indicators and explore two new COVID tags in STATcompiler.com.

Access to Information:

Health emergencies necessitate that urgent information be shared with the public in a timely manner. And yet large portions of the global population live without regular access to mass media. More than half of women age 15-49 in Liberia, Nigeria, Sierra Leone, Guinea, Benin, Timor-Leste, Niger, Malawi, Mozambique, the Democratic Republic of the Congo, Burundi, Papua New Guinea, Ethiopia, and Chad report that they do not have weekly access to information via radio, television, or newspaper.

In 30 out of 47 recent DHS surveys, at least 75% of households owned at least one mobile telephone. Still, ownership is lower in rural areas, and still uncommon in some countries; in Madagascar, for example, only one-third of households owned a mobile phone in 2016. Internet access, however, is very low across DHS countries. In Nigeria, only 16% of women and 35% of men age 15-49 used the internet in the past year (2018 NDHS). In Zambia, use was even lower, at 12% of women and 26% of men (2018 ZDHS).

Additional Considerations: Domestic Violence, Tobacco Use, and Access to Basic Health Services

And then there are potential secondary risk factors. How does cigarette smoking affect vulnerability? How will families cope with the stresses of a pandemic and the interpersonal conflicts exacerbated in quarantine settings? Will women and children continue to get the general health services they need, such as vaccinations, antenatal and delivery care, family planning, and nutritional support? These questions are important in all settings, but especially in those that are still in the process of building systems to support accessible, quality health care services. In Nigeria, for example, fewer than one-third of children age 12-23 months have received all 8 basic vaccinations, only about 40% of births are delivered in a health facility, and 19% of women have an unmet need for family planning.

Averaging across countries with data on spousal violence shows that 1 out of 4 women report physical, sexual, or emotional violence committed by their husband or partner within the last 12 months, and 36% report ever having faced such violence in their lifetime. These data suggest that social distancing may expose a significant proportion of already vulnerable women to a heightened risk of violence as women are forced to spend even more time with their abusers than usual and their access to sources of help is further limited by the pandemic.

There are countless other factors that are likely affecting COVID-19 transmission throughout the world. Urbanization, and slum environments in particular, are breeding grounds for contagion. In LMICs, millions of people migrate to city-centers for employment and are now migrating home to rural areas seeking safe-haven. These and myriad other factors can be explored in DHS datasets and final reports.

Conclusion:

Pandemics require data-driven decisions. While it is one unique virus that has spanned the globe, individual nations, communities, cultures, and families all face it within their own contexts. We can’t collect DHS household data during a pandemic. But we owe it to families in DHS countries to use the information already collected to better inform decisions to provide recommendations that resonate in their settings and to safeguard their already fragile health infrastructure.


17 Mar 2020

DHS Data Users: Ibrahima Gaye, Institute of Health and Development

Don’t read French? You can use the translate feature at the top of the page!

Si vous êtes intéressé à être présenté dans la série de blogs ‘DHS Data Users’, faites-le nous savoir ici en nous soumettant votre exemple d’utilisation des données du programme DHS.


Comment êtes-vous impliqué dans les enquêtes de The DHS Program ?

J’ai travaillé pendant trois années comme superviseur national du volet ménage des Enquêtes Démographiques et de Santé (EDS)-Continue au Sénégal. Durant cette expérience, en plus du suivi de la collecte, j’ai participé activement dans le traitement des données (éditions secondaires) et dans l’analyse des données. Lors de l’EDS-Continue, j’ai bénéficié de formations en matière de :

  • L’échantillonnage de l’EDS ;
  • Les procédures de traitement des données de l’EDS ;
  • Les méthodes dynamiques de formation pour adultes.

Cette dernière a changé ma façon d’animer les ateliers. En toute modestie, si aujourd’hui la qualité de mon enseignement ou d’animation est appréciée, c’est en grande partie grâce à la formation sur les méthodes dynamiques de formation pour adultes que j’ai suivi.

Et les ateliers de l’utilisation et de l’analyse de données des enquêtes de The DHS Program ?

En novembre 2019, The DHS Program m’a engagé pour animer un atelier, Tendances des Indicateurs du Paludisme au Bénin.

L’atelier portait sur l’analyse des tendances temporelles des indicateurs du paludisme au Bénin. La finalité était de contribuer à l’amélioration des capacités des 18 acteurs opérationnels de la mise en œuvre du programme paludisme par :

Discussion des intervalles de confiance. © ICF

Comment utilisez-vous les données des enquêtes de The DHS Program lors de votre travail actuel ?

Depuis 2018, je suis Data Manager de l’Evaluation prospective des programmes du Fonds Mondial (Tuberculose, VIH, Paludisme) où je suis chargé de la gestion et de l’analyse des données de l’évaluation.

Les données de l’EDS nous permettent de vérifier l’exactitude des données des programmes de santé mais aussi d’estimer les connaissances, attitudes et pratiques de la population sur les maladies telles que la tuberculose, le VIH ou encore le paludisme.

Quel est le problème de population ou de santé qui vous intéresse le plus, et pourquoi ?

Je suis particulièrement intéressé par la planification familiale. La plupart des décès maternels restent liés aux grossesses rapprochées, trop nombreuses, précoces ou tardives. C’est pourquoi la planification familiale constitue une méthode des plus efficaces et peu couteuse pour améliorer la santé des femmes et des enfants et lutter contre la mortalité maternelle et infantile.

En effet, en dépit des progrès réalisés dans le secteur de la santé au Sénégal, les taux de mortalité maternelle et infantile n’ont pas connu l’évolution espérée ces dix dernières années. Le pourcentage de décès de femmes liés à la grossesse est l’un des plus élevés de la sous-région (29%).  Par ailleurs, la mortalité infantile (42 décès pour 1 000 naissances vivantes, EDS-C 2017) reste au même niveau depuis quelques années et ce à cause, notamment, du nombre important de décès néonataux (28 décès pour 1 000 naissances vivantes, EDS-C 2017) qui représentent la moitié des décès infantiles.


Un rapport a été produit à partir des analyses des participants. Lisez le, Tendances des indicateurs du paludisme au Bénin : Résultats d’un atelier de l’utilisation des données des Enquêtes Démographiques et de Santé.


Écrit par : Ibrahima Gaye

Ingénieur statisticien de formation avec une spécialisation en informatique décisionnelle, Ibrahima GAYE est aussi titulaire d’un Master en management de projets et d’un Master en santé publique spécialité Méthode Quantitatives et Économétriques pour la Recherche en santé, pour lequel il a utilisé les données de l’EDS dans le cadre de son mémoire de Master en santé publique sur : « Analyse multiniveau de l’utilisation de la contraception au Sénégal ». Il est maintenant en train d’écrire sa thèse de Doctorat en santé publique : « Contribution du modèle Age-Période-Cohorte (APC) à l’étude de la prévalence contraceptive au Sénégal », pour lequel il utilisera également les données de l’EDS.


Featured image caption: © ICF

06 Mar 2020

International Women’s Day 2020: Measuring Gender-related Power

Five years since world leaders agreed to the Sustainable Development Goals (SDGs) to create a better world by 2030, this year’s theme for International Women’s Day, I am Generation Equality: Realizing Women’s Rights, challenges everyone to reflect on how a gender-equal world will be achieved. DHS data describe the status of women around the world. Over time, women have made gains in education, employment, health care, and family life. However, progress towards gender equality is halting and inconsistent.

In a gender-equal world, women and men will have equal power: the power within to know their right to equality, the power to create change, and the power with others. In a gender-equal world, other people’s power over women will be reduced, especially the most extreme expression of power over, gender-based violence (GBV).

DHS questionnaires already give insight into the types of power that women and men do and do not have. For instance, a composite scale of three DHS survey items is used to measure progress toward SDG Indicator 5.6.1: the proportion of women age 15-49 who make their own informed decisions regarding sexual relations, contraceptive use, and reproductive health care.

DHS data have been used to construct other composite scales, such as the Survey-based Women’s emPowERment (SWPER) index to measure women’s empowerment. The Population Council’s Gender and Power Metrics database includes several scales that use DHS data to measure gender, agency, power, and control.

The DHS Program has recently updated DHS-8 questionnaires and optional modules, including the Domestic Violence module, to fill gender-related data gaps and respond to emerging gender data needs. For instance, in several countries around the world, many people live together in unions that have not been officially registered. A registered marriage is related to a range of social protections and rights, such as divorce and inheritance, that are especially important for gender equality. New questions have been added to the Woman’s Questionnaire on marriage registration:

  • Did you have a marriage certificate for your last marriage?
  • Do you have a marriage certificate for this marriage?
  • Was this marriage ever registered with the civil authority?

Measuring gender-related power using DHS data highlights countries’ progress towards gender equality, especially in the areas of reproductive empowerment, male engagement, and reduction of GBV. Measuring power can also help program managers and policymakers understand how power manifests within couples, between service providers and clients, and how different interventions can cultivate positive expressions of power and mitigate harmful expressions of power over for a more equal world.

For International Women’s Day 2020, explore gender-related power measures in DHS surveys in an inventory and a presentation. You can also explore many common gender indicators using The DHS Program’s Gender mini tool.


Featured image caption: © Mary Long

25 Feb 2020

Inside The DHS Program: Q&A with Gisèle Dunia

Name: Gisèle Dunia

Position title: Senior Advisor for Capacity Strengthening

Languages spoken: French, English, Swahili, Lingala, and Haitian Creole

When did you start at The DHS Program? March 2019

Favorite DHS survey cover: I prefer it when we have an image that represents the country. For example, the report for the 2007 Democratic Republic of the Congo DHS had an okapi on the cover, and you find okapis only in DRC.

2007 DRC DHS Final Report

What is your role at The DHS Program? As the Senior Advisor for Capacity Strengthening, I oversee the implementation of strategies to strengthen host country individual and institutional capacity, working with different technical teams.

My work involves assessing survey implementing agencies’ capacity at the beginning and at the end of a survey and working on capacity strengthening activities to improve and sustain institutional capacity. Capacity strengthening activities are either survey-related or competency-based trainings. Our training opportunities are offered both online, on The DHS Program Learning Hub, and in-person during national and regional workshops.

Another way of strengthening capacity at the country level is by collaborating with consultants. The DHS Program has been using south-to-south consultants for several years. Consultants help build and reinforce capacity in host countries and across regions. Under DHS-8, we are designing a certification program for these consultants, streamlining processes to equip them with skills to better support survey implementation and dissemination.

What work are you most proud of? I have designed and facilitated several capacity strengthening activities in the past. In my work now at The DHS Program, I’m no longer in front of people facilitating trainings. I am mostly behind the scenes. I am very much involved in the design process, making sure that we have the right tools to facilitate engaging trainings. I am proud of the way I’ve been able to help technical teams design trainings, and I trust them to successfully run the show.

I am most proud of completely designing the DHS-8 Global Capacity Strengthening Strategy within my first six months at a program that has so many components as The DHS Program.

What’s your favorite trip to date? So far, my second trip is my favorite one. In December, I went to Madagascar to conduct a capacity assessment of the Institut National de la Statistique (INSTAT), the implementing agency for the forthcoming fifth Madagascar Demographic and Health Survey. While there I pilot-tested our updated Capacity Assessment Tools, which I used to assess INSTAT’s current capacity. Based on the results, I shared with INSTAT a list of capacity strengthening activities that I think would benefit them, like how they can restructure the way they work so that whatever capacity is built during the DHS survey process can be managed and shared throughout INSTAT to build long-term institutional capacity.

For more information about The DHS Program’s capacity strengthening approaches, visit our website.

Featured Image: © 2019 ICF

11 Feb 2020

Luminare: Geospatial Modeling for Locally Available Data

This blog post is part of Luminare, our blog series exploring innovative solutions to data collection, quality assurance, biomarker measurement, data use, and further analysis.


Demographic and Health Surveys (DHS) collect nationally representative data and data representative at the first subnational administrative level (ADMIN 1). The 2016 Ethiopia DHS was designed to produce representative estimates for nine regions and two administrative cities. The 2014 Kenya DHS produced estimates for eight regions (formerly provinces). In addition to national-level indicators, STATcompiler also presents subnational data, as shown in the map of childhood stunting at the ADMIN 1 level in Ethiopia and Kenya.

Childhood Stunting by Subnational Level, 2016 Ethiopia DHS & 2014 Kenya DHS

Click the map to explore childhood stunting using STATcompiler.

National and ADMIN 1 data help countries track their progress towards achieving the Sustainable Development Goals, for instance. However, as countries decentralize their health service delivery systems, local health officials increasingly need local data. In Ethiopia, nine regions are further divided into zones and special districts (ADMIN 2). In Kenya, eight regions are further divided into counties.

One option to get data representative at the ADMIN 2 level is to increase the survey sample size, requiring more time and more money. Another option is to produce spatially interpolated maps, which use Bayesian geospatial modeling techniques to predict indicator values at non-surveyed locations.

The DHS Program’s Geospatial team assembled data for 12 geospatial covariates, such as elevation, precipitation, and population density. These covariates are related to and can partially explain variation in health indicators of interest, allowing for more accurate predictions across the map.

Next, the Geospatial team imported georeferenced cluster data points from the 2016 Ethiopia DHS and 2014 Kenya DHS. (Did you know? You can download shapefiles or geodatabases of georeferenced data for most DHS surveys from the Spatial Data Repository.)

Using the geospatial covariates and survey data, the Geospatial team employed a new modeling approach–a stacked ensemble model–which combines multiple models. This increases predictive power and captures the potentially complex interactions and non-linear effects among the geospatial covariates. Three sub-models were fit to the health indicator data using the geospatial covariates as exploratory predictors. The prediction surfaces generated from the sub-models were then used in the final Bayesian geospatial model, producing 5 X 5 km pixel-level mean estimates of health indicators with associated uncertainty.

Childhood Stunting by 5 X 5 km Pixel, 2016 Ethiopia DHS & 2014 Kenya DHS

Modeled surface maps available from the Spatial Data Repository.

Pixel-level estimates were then used to calculate population-weighted averages to aggregate estimates to the ADMIN 2 level. For Ethiopia, this produced estimates of childhood stunting by zone, and in Kenya, estimates by county.

Childhood Stunting by ADMIN 2 level, 2016 Ethiopia DHS & 2014 Kenya DHS

Health system program managers in Ethiopia and Kenya can now use these zonal- and county-specific estimates to make decisions and manage locally administered health programs to address childhood stunting in their areas.

The DHS Program will continue exploring model-based geostatistics as a feasible, reliable, and cost-effective way to produce local data for local needs.

Read the full report, Interpolation of DHS Survey Data at Subnational Administrative Level 2.

Explore available spatially modeled map surfaces of DHS indicators on the Spatial Data Repository.

29 Jan 2020

Luminare: Insights from a Malaria Consultative Meeting in Malawi

This blog post is part of Luminare, our blog series exploring innovative solutions to data collection, quality assurance, biomarker measurement, data use, and further analysis.


The DHS Program clearly loves data, but what good is collecting data if it is not used, or used only in isolation? This was the motivation behind a Malaria Data Consultative Meeting implemented by The DHS Program and co-facilitated by Dr. Katherine Battle of the Malaria Atlas Project in Malawi in July 2019.

Routine health surveillance data are continuously collected at health facilities in Malawi and entered into District Health Information Software 2 (DHIS2), giving a robust picture of malaria control in Malawi. For instance, each year, approximately six million malaria cases account for 30% of all outpatient visits at health facilities, 34% of inpatient hospital admissions, and 2,967 malaria-related hospital deaths.

The quality and completeness of DHIS2 data vary by facility and only data on people who seek and receive care are included. By contrast, household surveys, such as Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS), are representative of the general population, with comparable data for trend analysis and multi-country comparisons.

At the consultative meeting, malaria data experts developed and presented case studies on indicators that were found in both data sources to check for external consistency and evaluate progress towards Malawi’s Malaria Strategic Plan (MSP) targets. For instance, effective malaria case management is a key component of the 2017–2022 MSP, with targets to test 95% of suspected malaria cases and treat 100% of confirmed cases by 2022.

The DHIS2 data above depicts suspected malaria cases in children under 5 that received a confirmatory test at a health facility. The household survey data above represents children under 5 who had a fever in the previous 2 weeks for whom advice or treatment was sought and who had blood taken from a finger or heel for diagnostic testing. See the table below for more information on these indicators.

 
Data sourceAvailable dataIndicatorNumeratorDenominator
DHIS22014–2018Percent of suspected malaria cases in children under 5 who received a confirmatory test at facility or village clinicNumber of suspected malaria cases in children under 5 who received a confirmatory testTotal number of suspected cases in children under 5 at facility or village clinic
Household survey data2014 Malawi MIS and 2017 Malawi MISPercent of children under 5 with fever in the previous 2 weeks for whom advice or treatment was sought and who had blood taken from a finger or heel for testingNumber of children under 5 with fever in the previous 2 weeks for whom advice or treatment was sought and who had blood taken from a finger or heel for testingTotal number of children under 5 with fever in the previous 2 weeks for whom advice or treatment was sought

Adapted from Table 2 in Malaria Journal report.

Both the DHIS2 and MIS data show improvement in confirmatory testing of suspected cases over time, although absolute values differ. Differences were attributed to recall bias among survey respondents. Because the study populations (denominators) of the two datasets are different, it is more meaningful to compare trends rather than absolute values.

As countries move towards malaria elimination it is essential that programs begin monitoring performance using multiple data sources. By using routine surveillance data and household survey data together, malaria data experts have a more complete, unbiased picture of malaria in Malawi.

A report of this Malaria Data Consultative Meeting was published in the Malaria Journal. You can read it here!

Explore Malawi household survey data for yourself using STATcompiler.




 

Featured image caption: Participants from the Malaria Data Consultative Meeting in Malawi. ©ICF

07 Jan 2020

Introducing DHS Program Analysis Briefs

Over the last 30 years, The DHS Program has published more than 500 analytical reports in collaboration with researchers and institutions around the world. These reports extend to a wide variety of topics covering population and health issues with the ultimate purpose to be used in policy formation, program planning, and monitoring and evaluation. However, many potential beneficiaries of DHS Program research findings are intimidated by these long, technical reports.

In order to expand the reach of DHS analyses to program managers, policymakers, and academic researchers, The DHS Program is pleased to announce a new user-friendly format of analysis reports. Analysis Briefs are two- to three-page user-friendly documents summarizing the methods, key findings, and any relevant action steps.

 

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.

These abbreviated, colorful briefs with graphics highlight major findings in a more accessible way that allow readers to use the findings for program or policy use in their respective country. If readers choose to dive into the full report, the brief still provides an orientation through the technical data in the full report. The graphics are presented in a simplified way to orient the information in a clear, visual display. Readers with limited time and attention are encouraged to review the accompanying briefs for a condensed summary of the full analysis report.

Briefs can be found on the full report publication summary page or by filtering by publication type ‘Analysis Briefs’ in The DHS Program publication search.

 
11 Dec 2019

Meeting Emerging Nutrition Data Needs in DHS-8

Nutrition is central to the health, well-being, and economic development of individuals, communities, and nations. Comprehensive and credible data are needed to capture the current state of nutrition and track the implementation of nutrition interventions. The DHS Program is a leading source of nutrition data in low and middle-income countries.

The DHS Program has standard Model Questionnaires, updated every 5 years, which form the basis for the data that are collected in each country. In 2019, we underwent a rigorous process to update the questionnaires for DHS-8. A total of 89 nutrition-related questions are now in the Woman’s Questionnaire, up from 54 questions in DHS-7.

The DHS-8 questionnaires meet several current and emerging nutrition data needs which can be used to track progress and inform national and global decisions on nutrition policies and programs. This week we are highlighting the new and revised nutrition questions in DHS-8.

These new and revised questions strengthen the nutrition portfolio in DHS surveys, filling major data gaps and enhancing countries’ ability to address malnutrition in all its forms.

Click the icon below to view the new nutrition information by topic:

Anthropometry Measurement
Nutrition Counseling
Food or Cash Assistance
Iron Supplementation
Minimum Dietary Diversity for Women
Unhealthy Foods for Children
Growth Monitoring
FIES

Click the life cycle below to view all nutrition data collected in DHS surveys:

When will updated nutrition data be available?

The DHS-8 Model Questionnaires will be ready for use in surveys with fieldwork starting in late 2020 with data released starting in late 2021. In the meantime, The DHS Program will:

  • Translate the questionnaires
  • Revise training manuals and materials
  • Develop an adaptation guide for questions which require country-specific adaptation, such as infant and young child feeding and minimum dietary diversity for women
  • Create data processing applications
  • Define indicators, design table templates, and draft report templates
  • Pilot select new questions, modules, and alternative approaches for entering data in CAPI

The status of DHS surveys can be found here.


Visit The DHS Program website and subscribe to The DHS Program Nutrition eNewsletter for more nutrition updates in The DHS Program. You can also join the Data for Nutrition Community of Practice as a free, online platform for more nutrition resources.

Featured Image: © 2017 Riccardo Gangale, USAID, Courtesy of Photoshare.

 
02 Dec 2019

16 Days of Activism against Gender-based Violence

The 16 Days of Activism against Gender-based Violence campaign is back in action for 2019 under the theme “Orange the World: Generation Equality Stands against Rape!” This year, The DHS Program is highlighting sexual and physical violence indicators, as well as help seeking behavior in Tajikistan, Pakistan, Nigeria, Benin, and Mali.

Click on a graph below to open the indicator in STATcompiler. Use STATcompiler to compare other domestic violence indicators across countries, and share your results on social media using #orangetheword and #generationeqaulity. You can even add additional background characteristics and view the data over time or by region. For more ways to use STATcompiler, watch our STATcompiler tutorials.

 

Still want to do more? Share these 16 days messages from UN Women’s social media toolkit. Additionally, try The DHS Program’s Gender mini tool to compare indicators of gender inequality, women’s empowerment, and gender norms all in one easy tool.

20 Nov 2019

From Participant to Facilitator: DHS Fellows from Myanmar and Egypt

The 2020 DHS Fellows Program is currently accepting applications from Bangladesh, Indonesia, Jordan, Maldives, Pakistan, Philippines, Tajikistan, Benin, Burkina Faso, Cameroon, Guinea, Mali, Rwanda, Senegal, and Zambia. Apply to join us for the DHS Fellows Program in 2020. The deadline to apply is November 24, 2019.

 

In this blog post, we interview two DHS Fellows who served as DHS Program workshop facilitators.

Dr. Kyaw Swa Mya is an Associate Professor and Head of Department of Biostatistics and Medical Demography at the University of Public Health, Yangon, Myanmar and Mr. Ehab Sakr is an assistant lecturer in the department of Demography and Bio-statistics at the Faculty of Graduate Studies for Statistical Research in Cairo University in Egypt. Both Fellows were both co-facilitators for the DHS Fellows Program (2019 and 2018, respectively) in addition to co-facilitating other DHS Program capacity strengthening workshops.

When was your first experience with the DHS Fellows Program?

KSM: In 2018, I was selected as part of a three-member team for the 2018 DHS Fellows Program from the University of Public Health, Yangon. We were the first Fellows from Myanmar where only one DHS survey has been conducted in 2015-2016. In Myanmar, most public health professionals, including myself, were not aware of DHS surveys.

ES: In January 2017, my colleagues and I were selected to be the first Egyptian team to participate in the 2017 DHS Fellows Program. I was eager for this opportunity because I used DHS data in my studies when I specialized in demography 17 years ago.

What was your experience as a DHS Fellows Program participant?

KSM: The Fellows Program provided many opportunities for the participants. First, we learned how DHS data was systematically collected and prepared for data users. Second, the Fellows Program improved our data management and analytical skills using STATA, as well as report writing skills. Third, as a requirement of the Fellows Program, we conducted capacity building activities at our University. These activities raised awareness among the Myanmar government and NGO public health professionals about using DHS data and DHS resources during planning, implementation, and evaluation of their health programs. We also disseminated the findings to stakeholders who impact policy implementation. Finally, we produced a DHS working paper that was published in the PLOS One journal.

ES: The Fellows Program was a great opportunity to enhance my knowledge about survey tools and improve my skills to use DHS data more efficiently and effectively. We were exposed to different cultures and academic trends from five other teams around the world. It’s also worth mentioning that implementing the capacity building project at our home university enriched my technical, teaching, and coaching skills. In two workshops facilitated by Dr. Wenjuan Wang and Dr. Shireen Assaf, we learned to use DHS data tools and techniques when analyzing DHS data. My teammates, Prof. Emeritus Mona Khalifa and Dr. Wafaa Hussein, and I wrote a DHS working paper titled “Changes in Contraceptive Use Dynamics in Egypt: Analysis of the 2008 and 2014 Demographic and Health Surveys.”

What was your experience as a facilitator?

KSM: The DHS Program gave me a second opportunity to participate in the DHS Fellows Program as a co-facilitator. I am thankful to The DHS Program for this opportunity. It was quite a challenging experience to be a co-facilitator. As a Fellow, I only needed to focus on my research topic, but as co-facilitator, I needed to learn all the research topics of participating countries. Moreover, I had to prepare lecture topics and this helped me become more familiar and confident with DHS methodology, analytical skills, and interpretation of the results.

ES: July 2019 was another great moment when I was asked to co-facilitate a workshop in Jordan on producing report tables using SPSS syntax at the Department of Statistics. It was a great experience communicating with lovely and skilled trainees, and we adapted to situations that forced us to customize the agenda of the workshop to suit the skills and knowledge of the trainees.

What impact has the DHS Fellows Program made on you?

KSM: The DHS Fellows Program changed my career, and DHS data has become a core part of my life. Since 2018, I published two journal articles and presented two oral presentations at the 10th and 11th International Conference on Public Health among Greater Mekong Sub-Regional Countries. One of my Masters in Public Health (MPH) students received a degree and I reviewed two master theses of two junior colleagues using DHS data and they achieved their master’s degree from foreign countries. I also received some emails from different countries asking for help with DHS coding and analysis challenges, and I helped them as far as I could. In addition, three of my MPH students prepared their proposals using DHS data this year. Myanmar is now realizing the data quality and accuracy of DHS indicators, so, not only academicians and students but also program managers and policymakers are using DHS indicators in relevant situations.

The DHS Fellow Program is one of the best and most effective programs that I have ever attended. I am grateful to USAID for providing financial and technical support to collect and disseminate quality data to monitor and evaluate population, health, and nutrition programs for developing countries.

ES: The DHS Fellows Program was life-changing and it gave me the opportunity to deepen my scientific and practical knowledge in an international, inspiring, creative, and diversified environment. Special thanks to USAID, The DHS Program team, and all the people I mentioned above. I learned a lot from them and hope to continue collaborating with them in the future.


Photo caption: Facilitators and participants from the 2018 DHS Fellows Data Analysis Workshop. ©ICF


Written by: Kyaw Swa Mya and Ehab Sakr

Dr. Kyaw Swa Mya is a Biostatistician. He is an Associate Professor and Head of the Department of Biostatistics and Medical Demography, University of Public Health, Yangon, Myanmar. He holds a master’s degree in Public Health in Biostatistics. He is a member of the Institutional Review Board of the University of Public Health, Yangon. He currently works as a module supervisor of Diploma in Research Methodology and Research Ethics program conducted in the University of Medicine (I). His research interests are maternal and child health, nutrition, and non-communicable diseases.

Mr. Ehab Sakr is an assistant lecturer in the department of Demography and Bio-statistics, Faculty of Graduate Studies for Statistical Research, Cairo University in Egypt. He holds a master’s degree in Statistics from the Faculty of Economics and Political Science. His thesis theme was related to the levels and trends of age at first marriage for women in Egypt. He taught and consulted on various topics related to population dynamics and development and is currently a Ph.D. student.

The information provided on this Web site is not official U.S. Government information and does not represent the views or positions of the U.S. Agency for International Development or the U.S. Government.

The DHS Program, ICF
530 Gaither Road, Suite 500, Rockville, MD 20850
Tel: +1 (301) 407-6500 • Fax: +1 (301) 407-6501
dhsprogram.com

Anthropometry measurement (height and weight) is a core component of DHS surveys that is used to generate indicators on nutritional status. The Biomarker Questionnaire now includes questions on clothing and hairstyle interference on measurements for both women and children for improved interpretation.