27 Apr

The Vaccination Landscape: Changes and Challenges

What was the last vaccination you received? The one before that? When did you receive them?  Where was the vaccine administered – your arm? Your thigh? The right or the left? For most of us, this is not easy information to remember. And yet it’s what we ask many women to recall for their children in DHS interviews.

A child in Lhoksemawe, Aceh, Indonesia, receives a vaccine injection.

© 2012 Armin Hari/INSIST, Courtesy of Photoshare

Since 1984, The DHS Program has collected data on vaccinations in over 80 countries.  During this time, the vaccination landscape has changed dramatically. Initially, BCG, DPT (Diphtheria; Pertussis, or whooping cough; and Tetanus), Polio, and Measles were the only childhood vaccines most countries administered. These data were collected only from vaccination cards.

As time went on, our methodology expanded to include data collection from mother’s recall to clarify incomplete vaccination cards. In cases where there is no vaccination card, mothers are asked whether or not her child received each type of vaccine and the number of doses.

Today, the number of vaccines standardly administered is much higher. This is good news — it means millions more lives saved — but it introduces data collection challenges.

The vaccination data collected in a standard DHS questionnaire are far more elaborate than any time in our history: BCG remains; for Polio a birth dose is added; DPT is now combined into a pentavalent vaccine with Hepatitis B and Haemophilus influenza type B (Hib); 3 doses of a pneumococcal vaccine and 3 doses of a rotavirus vaccine are now included; and the measles vaccine has been replaced with a measles combination vaccine. For countries that are transitioning between vaccination schedules or have more complicated schedules, the landscape becomes more challenging to navigate.

Data collection is relatively straightforward when a child has an up-to-date and complete vaccination card.  But in many cases, changing vaccine schedules and inconsistent record-keeping render the cards incomplete or unclear. Worse, vaccination cards are often missing or otherwise unavailable.

Indeed, a recent study revealed that in 4 of the 10 countries with the largest birth cohorts that had carried out either a DHS or MICS survey in 2010-2013, less than 50% of children had home-based vaccination records.

A happy mother shows her child's vaccination card in New Delhi, India.

© 2012 Bhupendra/MCHIP, Courtesy of Photoshare

When a vaccination card is unavailable, it is the mother who is expected to fill in the gaps.  But a mother’s recall is not 100% reliable. Keeping track of vaccines for multiple children and for combination vaccines is challenging enough, but even more so if the mother isn’t present for every vaccination event.

Knowing whether newer and existing vaccines are reaching their target population and doing so on schedule is valuable information to many. What can be done to maintain and even improve data quality when the complexity of the data needs on vaccine coverage continue to grow?

The DHS Program, in collaboration with the World Health Organization (WHO), United Nations Children’s Fund (UNICEF) and other experts in the field, are pursuing several options. One involves visiting health facilities to compare the information collected during the interview to the vaccination information recorded at the health facility.

This process has been used previously in Central Asian countries and in Albania, where facility-based documentation is strong. It is now being pilot-tested in Ethiopia; however, the method of record-keeping varies by location and includes instances where records are kept based on the date of visit and not based on the child’s name or date of birth. Country-specific challenges such as these require additional flexibility and coordination between survey implementers, Ministries of Health, and health facilities.

There is unlikely a one-size-fits-all solution to the challenge of accurately measuring vaccination coverage.  But from the perspective of global health, this is a good problem to have.  More children worldwide are being protected from a host of illnesses.  We are proud to be sharing data to help track progress towards closing the gap as our implementing partners reach more children with a larger variety of vaccines.

20 Apr

From the Field: 2014-15 Uganda Malaria Indicator Survey (UMIS) Team

From left to right: Patrick, Aziza, Irene N., Doreen, Persis, Irene B. with Uganda Bureau of Statistics (UBOS) survey vehicle

During fieldwork for a household survey, survey teams visit households that are selected to represent an entire country. Respondents to the survey are as diverse as the country and live within mountains, valleys, deep in forests, and busy urban centers. These respondents allow survey teams into their homes to answer questions about themselves, their families, and their lives. While I consider myself lucky to have the opportunity to meet and talk to so many people during survey fieldwork, there are certainly many challenges.

For the fieldwork phase of the 2014-15 Uganda Malaria Indicator Survey (UMIS), I spent a day with Patrick, Aziza, Irene N., Doreen, and Persis as they conducted interviews and tested children under 5 for anemia and malaria. Despite the challenges and even some homesickness, the team worked hard to collect data important to Uganda while enjoying the chance to travel throughout their country, make friends, treat children for malaria, and engage with different communities.

Patrick, Lab Technician

“When you test a person’s child and actually find he has malaria, at the end of the day you give them treatment and the guardians are usually grateful. You feel like you’ve helped out.”


 

AzizaAziza, Interviewer

“It has been hectic. It hasn’t been easy. But at the end of the day we get data, even when you are very tired!”

“I’ve gotten the chance to educate women in the village… This is a way we connect with people in the village.”

 

Irene-NIrene N., Interviewer

“Most times, we wake up at 6 so we can be on the road by 7 after breakfast. Then, we get in the field by 8, so each interviewer does 5 to 7 households and then test about 16 children in a day.”

 

Doreen, Nurse/Interviewer

“We realized that malaria is still a major problem. People are suffering. Young children under five are really suffering from malaria and also anemia.”

“It has actually given us an opportunity to appreciate and learn more about our communities, because you would not have ever imagined that malaria really exists and is killing so many people until you are there, testing and seeing positive rapid diagnostic tests (RDTs).”

Persis, Supervisor

“My motto is, ‘I don’t give up’ … when it comes to work I do it with all my heart. I don’t compromise work, I am really mindful of the quality at the end of the day.”

“I really wanted to work on the malaria survey because health is the first and foremost priority… I believe our work is good.”

The 2014-15 Uganda Malaria Indicator Survey (UMIS) was released on November 6th, 2015, and is the 2nd UMIS as part of The DHS Program. Fieldwork took place from early December 2014 to late January 2015. There were 17 teams for field data collection; each field team included 1 field supervisor, 3 interviewers (1 of whom was a nurse), 2 health technicians, and 1 driver. A total of 5,345 households were interviewed. The 2014-15 UMIS was implemented by the Uganda Bureau of Statistics (UBOS) and the National Malaria Control Programme (NMCP) of the Uganda Ministry of Health.

13 Apr

How Many Demographers Does It Take to Make a Great Visualization?

How much time do you budget to create a data visualization?  The best visualizations, though they appear to be simple and clear, are often the result of dozens of attempts.

Demographers spend countless hours crunching data and preparing journal submissions, but not all take full advantage of data visualization, either in their exploratory analysis, or in communication of their findings.  Last month, data visualization enthusiasts met at the Population Reference Bureau for a hands-on workshop as part of the Population Association of America (PAA) Conference.  The 4 hour interactive workshop featured presentations from DC-based data viz expert Jon Schwabish, Dr. Tim Riffe, demographer at the Max Planck Institute for Demographic Research (MPIDR), Jonas Schoeley (MPIDR), and Dr. Audrey Dorelien of the Minnesota Population Center.  While each presenter had a unique focus, a common theme was clear:  your first draft visualization should never be your final visualization.  This lesson was put into practice as participants shared works-in-progress, received constructive feedback, and prepared “makeovers”.


Clara Burgert and I have been working on a visualization project for over a year.  The original was published last summer but we’ve been reworking it for a journal submission. Our colleagues at the data viz workshop provided constructive feedback, and we have made yet another round of changes. Some of the many stages of our chart “makeover” are presented below.

SAR12

Clara’s recently published analysis looks at 27 countries and 6 child health indicators. The goals of our visualization were to compare countries across these 6 indicators and to illustrate the inequity within countries, by highlighting the worst and best performing sub-national regions. While some countries have a very high measles vaccination prevalence, such as Tanzania, there are regions in Tanzania that are performing very poorly. Meanwhile, other countries have moderately good vaccination rates with very little variation among regions (like Rwanda). Our first real attempt at a publishable graphic looked like this:

indicators for journal

One of the challenges with this first graphic was that it didn’t use color very well. Clara needed to use color to distinguish between the 6 indicators in other places in the report, so we wanted to integrate that color scheme here for consistency. Simultaneously we realized that we could also simplify our use of color in this first draft: while we had originally plotted the red circle as the lowest region, the reader doesn’t need that color to know that that plot is the lowest- it’s obvious based on the axis and the left-to-right understanding of a numerical timeline. So we tried this:

indicators for journal with color coding

This color scheme worked better to unify the other graphics in the report, and we were feeling pretty good about it. But we still had a few concerns and questions:

  • Was it okay to have the axis for the stunting indicator and under-five mortality the same size as the others even though they aren’t at the same scale?
  • Was it okay that we were sorting lowest to highest, instead of ordering countries in a consistent way?
  • How should we handle ordering of the data when for 4 of our indicators, a high data value is “good”, like vaccination coverage, while for 2 of our indicators, a high data value is bad, like mortality?
  • Were there any formatting tweaks we could make to improve readability?

It was this version that was shared at the PAA data visualization workshop. Through the feedback of experts and colleagues, we made some final decisions:

  1. Change the axis of the stunting indicator to go to 100% so that it is consistent with the other percentages in the graphic. Some suggested that we move stunting and under-five mortality to a separate page to visually remind readers that the interpretation of these indicators is different (i.e., high values are bad). Ultimately, we decided that the layout of the 6 indicators was better for us in terms of publication, but agree that this is a trade-off and may confuse some less technical audiences.
  2. We decided to keep our sorting from low to high, as the main audience for this paper is looking at general trends, not for data for a specific country. However, reports by The DHS Program often have many audiences, and with that in mind, we created an additional graphic (not shown) that summarizes each of the indicators by country so that a stakeholder in Ghana can see his or her relevant data in one view, without searching for Ghana in each of the above graphics.
  3. Jon Schwabish had some quick and practical suggestions for making this graphic easier to read. His critique that it felt “heavy” resonated with us as the creators. He suggested thinning out the lines and substituting the big “X” marking the national average with a smaller circle.

6 indicators for journal April 4

There is a science to data visualization, but there is also a lot of subjectivity. Many solutions can be found only through trial and error. Often it takes time, several new sets of eyes, and dozens of drafts to settle on the best possible visualization for your data. While this is a big investment, there is growing evidence that it’s worth it. We are competing for just 1 or 2 minutes of our audience’s attention in a world filled with data and information. We hope to create a few visualizations that are worth stopping to explore.

 

07 Apr

Measuring health care: The Service Provision Assessment Survey

http://dhsprogram.com/publications/publication-SPA22-SPA-Final-Reports.cfm

When DHS and other population-based surveys indicate potential problems with a country’s health care systems, such questions are raised:

“Are certain services available in health facilities?”
“What is the quality of those services?”
“Are there factors at the service delivery level that could be contributing to the problems?”

The Service Provision Assessment (or SPA) survey attempts to bridge this gap while fulfilling the need to monitor health systems strengthening in surveyed countries.

Let’s say a national strategy is initiated to address a growing obesity problem and its associated issues, diabetes and hypertension. A component of the strategy may focus on improving a country’s health facilities by increasing the number that have diabetes services available.

2014-15 Tanzania SPA Key Findings

2014-15 Tanzania SPA Key Findings

It may also strengthen readiness of those facilities to provide quality services – more staff who are up-to-date on trainings for provision of diabetes services, more equipment (such as blood pressure apparatuses, adult weighing scales, and height boards), improved diagnostic capacity (the ability to conduct blood glucose and urine protein tests), and increased availability of medicines to manage diabetes. These are all indicators a SPA survey provides.

The improvements in service availability and readiness may lead to early identification of risk factors, early diagnosis and initiation of management, and, perhaps, a gradual decline in unmanaged diabetes.

2014-15 Tanzania SPA Key Findings video series
The SPA survey is designed to collect information from a sample of functioning health facilities in a country on the availability of services, readiness of facilities to provide health services in many areas, and measures of quality of care. Four different questionnaires are used to collect data at the facility, provider, and client levels. Survey data collection is done by teams of health workers.

If the DHS is a snapshot of a population’s health, the SPA is a snapshot of the service environment and those who provide and receive services, which drives population health. Though it can be challenging to directly link health facility data with population data, the SPA is useful in providing support and context to the DHS.

The first SPA surveys took place in Guatemala, Kenya, and Bangladesh in the late 1990’s, and continue to be implemented today. To date, 22 SPA surveys have been conducted, the latest being the 2014 Bangladesh Health Facilities Survey and 2014-15 Tanzania SPA. Ongoing surveys include the 2015 Nepal SPA and Senegal Continuous SPA. Be the first to know when those will be available (along with all other surveys) by signing up for email alerts, or by following us on Facebook and Twitter

30 Mar

Model Datasets to the Rescue

Have you ever wanted to start immediately working on a DHS dataset, but didn’t have a research topic? Or didn’t want to take the time to register for access? Well, The DHS Program now has the cure for all your data analysis woes!

The DHS Program has created model datasets so users can become familiar with datasets without having to register for access. These datasets have been created strictly for practice and do not represent any country’s actual data. Model datasets are based on the DHS 6 Questionnaire and Recode. They include data on all standard survey characteristics, as well as data on domestic violence, female genital cutting, adult and maternal mortality, and child labor.

You might be thinking, how can I use these datasets? Model datasets can be used for many different purposes, including:

  • Replicating standard final report tables
  • Practicing calculating complex indicators
  • Teaching statistical concepts and procedures

Team members from Nigeria participating in the 2016 Regional DHS/MIS Malaria Analysis Workshop

Recently, the model datasets were used in the 2016 Regional DHS/MIS Malaria Analysis Workshops in Uganda and Senegal. Since participants attending the workshop came from different countries with different DHS/MIS datasets, the curriculum and workshop exercises were standardized using the model datasets. After going through the model dataset examples, participants then worked with their country’s specific data to match numbers in the final report. This was a great way for facilitators to make sure everyone was mastering the skill before participants worked on their own country’s data.

Model datasets have already had a starring role in our sampling and weighting tutorial videos. Future videos will also feature the model datasets, allowing users to follow along with the examples in the tutorial with their own statistical program.

Visit the Model Datasets page on The DHS Program website for more information. Users can pick and choose which data files to download, as well as download the full set of final report tables and sampling errors to check their work. Again, unlike datasets for specific surveys, users do not need to register in order to gain access.

If you have recently used the model datasets we want to hear from you! Comment below or email modeldatasets@dhsprogram.com to share your experiences with the model datasets or how you plan on using them in the future. You can also post questions about the model datasets on the User Forum.

22 Mar

A Closer Look at Unmet Need in Ghana

View from Elmina Castle in Cape Coast Ghana. © Cameron Taylor/ICF International

For over 30 years, data from DHS surveys have been widely used to assess use of family planning, and monitor family planning programs around the world. DHS data are the gold standard for quality, but nuanced information related to fertility intentions and family planning use is often challenging to collect in a large-scale quantitative survey. Information from in-depth interviews with DHS respondents can help us understand and interpret survey results.

QRS20DHS recently published a follow-up study to the 2014 Ghana Demographic and Health Survey (GDHS). The study reflects an evolving model of qualitative and mixed-methods research within The DHS Program: projects linked to the DHS survey process itself, rather than fielded separately. At the heart of the study was the opportunity to speak with a sub-sample of DHS respondents a few weeks after their DHS interview, which gives us some insight on data quality and reliability when we re-ask a few of the same questions.

But the real purpose of the study was to help us make sense of quantitative data. What does it mean when women say that they want to delay or space their births but that they are not using family planning? Programmatically, there is an important distinction between women who may be classified as having an unmet need for family planning versus women who are willing and ready to contracept. The reasons why a country with a relatively strong family planning program such as Ghana would have one of the continent’s highest levels of unmet need are not something we can always understand very well through the existing questions asked in large-scale surveys. A small number of systematically planned in-depth interviews can help us understand the individual narratives behind survey answers that give rise to the classification of unmet need.

Approximate locations of the final 13 clusters selected for the follow up study. Cluster locations have been randomly displaced to ensure respondent confidentiality.

Approximate locations of the final 13 clusters selected for the follow up study. Cluster locations have been randomly displaced to ensure respondent confidentiality.

Following up with DHS survey respondents was ethically and logistically complicated. We had to first get women’s consent during the initial interview for re-contact, use a computer program to select eligible women, and then try to re-identify women using an approximate address, structure number, name of head of household, and relationship to head of household. Once we approached original respondents we then had to start the process of obtaining consent and scheduling an interview anew. Fieldwork was conducted by the Institute of Statistical, Social, and Economic Research (ISSER) at the University of Ghana, Legon. Ghana Statistical Services, which implemented the GDHS, helped ISSER interviewers re-locate original households and randomly audited the follow-up interviews for data quality.

We re-asked some of the same questions posed by the GDHS and then inquired about any discrepancies. Did the respondent think that there was an error in transcription, or had her circumstances changed in the interim period between surveys?

Perceived cost and access barriers to contraception among follow-up respondents who were not using a modern method of family planning.

Perceived cost and access barriers to contraception among follow-up respondents who were not using a modern method of family planning.

Key findings from the study include: women seem to underreport traditional method use, intentional abstinence as a method of family planning is not well-captured by our surveys, husbands and partners have both a positive and a negative influence on use, women are most concerned about menstrual irregularities caused by hormonal methods, and opposition to modern methods among non-users is stronger than apparent from survey data.

You can download the full study, “Understanding Unmet Need in Ghana: Results from a Follow-up Study to the 2014 Ghana Demographic and Health Survey” from The DHS Program website.

08 Mar

On International Women’s Day: A Pledge for Accountability

International Women’s Day, March 8, never fails to give me pause: while it provides a time and space to celebrate women’s achievements and evaluate progress toward attaining gender equality, it also makes me wonder when we – all of humanity – will no longer need to set aside a special day to focus attention on fully half of humanity. It is disappointing that despite the nearly half century since the publication of Ester Boserup’s 1970 game changing Women’s Role in Economic Development which documented women’s critical and largely ignored role in agriculture, we are still only “pledging for parity” and are nowhere near achieving it.  Boserup’s work showed that in many economies women did half or more of agricultural work while also contributing significantly to trade.

Spousal Violence and HIV: Exploring the linkages in five sub-Saharan African countries

For me, Boserup’s work has special meaning. Not only did her insights change the way I looked at women’s role in development, but also because 22 years ago it indirectly gave rise to my very first job in the United States. In 1993, I joined DHS as its first and only Women-in-Development Analyst. The job title sounds archaic now, but back then the change from a focus on women’s roles in development to the role of gender in providing the context and constraints for women’s full participation in development was just beginning. By the end of the 1990s, the shift from WID to GAD (Gender and Development) was complete and my title eventually reflected this change.

…for us at The DHS Program, the 2016 International Women’s Day call of ‘Pledge for Parity’ translates into a pledge to continue providing the highest quality data and analysis to hold the world accountable for the continuing gap in the achievement of gender equality.

Women's Lives and Challenges: Equality and Empowerment since 2000

As the newly minted DHS WID analyst, I was asked to develop a module of survey questions that could be included in a DHS and would provide information on gender relations in the household and the context of women’s lives. At that time, almost 10 years after the DHS project was initiated, the DHS woman’s questionnaire, designed primarily to measure key demographic and health indicators, had almost no information on women’s status. The only information related to women’s status was education, age at first marriage, and employment. Thus in developing a women’s status module, I had a pretty clean slate to work with. The module that was finally developed and piloted as part of the 1995 Egypt DHS covered many aspects of women’s status including household decision making, dowry payments, attitudes towards women’s roles and spousal violence, ownership and control of assets, freedom of movement, financial autonomy, and exposure to violence. Though never fielded again in its initial form, the module became the basis of DHS’s ongoing contributions to understanding the role of gender and women’s empowerment in the achievement of demographic and health goals.

Men and Contraception: Trends in Attitudes and Use

Today The DHS Program continues its 20+ year tradition of providing reliable and consistent data on women’s roles in the household, violence against women, and female genital cutting. The power of these data comes not only from the information they provide on women’s lives, but also from the fact that these data are collected alongside demographic, health and nutrition data for the same women. This holistic approach enables The DHS Program to go beyond just providing gender indicators to the world, to providing in-depth analyses that help highlight women’s contributions, constraints and gender inequities in the context of demographic change, health, and social and economic development. Thus for us at The DHS Program, the 2016 International Women’s Day call of “Pledge for Parity” translates into a pledge to continue providing the highest quality data and analysis to hold the world accountable for the continuing gap in the achievement of gender equality.

 

23 Feb

High Demand for New India NFHS-4 Data

 

Fact sheets with survey results for the first 15 of the States and Union Territories from the 2015-16 National Family Health Survey (NFHS-4) were recently released to much fanfare and a veritable feeding frenzy among the media. The keen interest in the survey results materialized even without a formal dissemination event. The thirst for the results may have been stimulated by how:

  • it has been 10 years since the previous NFHS survey,
  • the results were made available even before the second-phase fieldwork started,
  • the NFHS surveys are considered to be highly reliable, and
  • the fact sheets contain a wide variety of key population, health, and nutrition indicators (114 in all), broken down by urban and rural areas and shown in comparison with the 2005-06 NFHS-3 results when possible.
© Fred Arnold/ICF International

© Fred Arnold/ICF International

The excitement accompanying the release of the NFHS-4 results was a far cry from what I remember happened at the time of the release of the 1992-93 NFHS-1 survey national report. Of course, the key stakeholders who were knowledgeable about NFHS-1 showed up at the dissemination event in large numbers, but it was difficult to generate a great deal of interest among the media, since they were less familiar with the survey or the importance of its results.

The proliferation of news articles and conversations on social media surrounding the results of the NFHS-4 fact sheets are examples of the interest in getting survey results out quickly.  Tweets from a variety of users, tagged with #NFHS4, shared links to the fact sheets, complete tables from each fact sheet, and trends in the data.


The first fact sheets for NFHS-4 are now available from the NFHS-4 coordinating agency, the International Institute for Population Sciences and from The DHS Program, and there is a link to the fact sheets from the website of the Government of India’s Ministry of Health and Family Welfare. Overall, 250 district-level fact sheets have also been released for the same states, each containing 93 indicators.

Working on a survey with a sample size of more than 572,000 households, with more than 6,000 field staff, 16 survey field agencies, millions of biomarkers tests, and questionnaires in 18 languages is certainly challenging, but finally being able to see the survey results in the hands of key stakeholders who are in a position to help improve the lives of India’s population makes it all worthwhile. Stay tuned for more results as the second phase of fieldwork has just begun.

For more information, read the Ministry of Health and Family Welfare’s press release.

04 Feb

Celebrating 12 Years of Service with The DHS Program

Laurie Liskin with the 2014 Kenya DHS team.
From left to right: M.G. Obudho, Michael Musyoka, Sara Head, Laurie Liskin, John K. Bore, Andrew Imbwaga, A.A. Awes (back), Christine Mbuli, Rebecca Kiptui, James Munguti (back)

After 12 years with The DHS Program, 58 trips to 17 countries, and almost 40 years in international development, I’ve decided to slow down.  As of January 2016, I will retire from full time work and explore the pleasures of retirement.

What to make of the past 12 years?  First, I marvel at how the field of dissemination has changed since I joined DHS in 2003.  So much of what is standard now—eLearning, tweets, infographics, data apps, and desktop video production, either did not exist a decade ago or was just beginning.  The field of dissemination and personal communication has exploded.  We can see the growth everywhere.  In Kenya, for example, only 13% of households had any kind of telephone in 2003.  Just 11 years later, in 2014, 86% of households have a mobile phone, many of them smart phones. Facebook is ubiquitous.   Access to information has never been easier.

Second, I am profoundly grateful for the chance to work with the dedicated team here at The DHS Program.  All of our staff—the diligent data processors, the incredibly creative dissemination team, talented researchers, capacity strengthening experts, the overworked survey managers, and of course, our stalwart program managers—are committed to ensuring that DHS, SPA, and MIS surveys are the highest quality possible.

Third, I cherish the opportunities I have had to collaborate with our country partners. After multiple trips to Tanzania, Bangladesh, and Kenya, in particular, I am lucky to have worked with survey specialists, communication experts, staff from USAID cooperating agencies, and our partners at USAID missions.  The work has been challenging, exciting, occasionally very frustrating, but most of all, lots of fun.

Best of all, the program welcomes a terrific new Senior Advisor for Communication. Erica Nybro has worked with The DHS Program since 2004 and has pioneered new products and activities including the DHS User Forum, the Mobile App, and training in data visualization.  I look forward to seeing her lead dissemination at The DHS Program in exciting new directions.

So, I bid farewell to my colleagues and friends in Rockville and around the world.  Thanks to all for a wonderful 12 years with The DHS Program.

20 Jan

Spotlight on New Staff: Allie Reese

Name: Allie Reese

Position title:  Social Media Specialist

Languages spoken: Sadly I only speak English fluently. But I can convey as much (or confidently say “hello”) in a few different languages:

Halo! Nggak bisa berbicara Bahasa Indonesia, tapi bisa mengerti.
Hola! Yo hablo Inglés, pero sé un poquito de español.
こんにちは! わたし は にほんご が はなせません。
!أهلا وسهلا

When not working, favorite place to visit:  I’d love a reason to travel and visit Indonesia! I have family there, I miss the food…

Favorite type of cuisine: It’s impossible to pick one single cuisine. Right now I’m craving fish and chips.

Last good book you read: “The Life-Changing Magic of Tidying Up: The Japanese Art of Decluttering and Organizing” by Marie Kondo. (Just don’t look at my desk.)

Where would we find you on a Saturday?  In bed asleep. If the weather is right I might be taking a long walk somewhere, looking for a good place to eat fish and chips.

FR275First time you worked with DHS survey data: Unwittingly while I was an undergraduate, writing a research paper on maternal mortality in Indonesia; I completed it just before the 2012 Indonesia DHS release.

What is on your desk (or bulletin board/wall) right now? I have a toy snake, some toy spiders I’ve kept from Halloween, and a miniature cat who sits on top of my monitor.

2014 Kenya DHSWhat is your favorite survey final report cover? Right now my favorite is the recent 2014 Kenya DHS.

Favorite chapter or indicator, and why?  Fertility and family planning, both telling and meaningful beyond being indicators of development.

What’s your favorite way to access The DHS Program’s data? I like reading hard copies of reports, but ultimately it’s through STATcompiler.

What population or health issue are you most passionate about?  Why? Women and girls, simply because women make up half of the world’s population and need to be treated like so.

What are you most looking forward to about your new position?  Engaging with our users via our social media platforms, especially Facebook and Twitter!

What has been your biggest surprise so far?  How much I learn each day – every time I feel like I’ve “got” something, there’s a caveat or several in there.

What do you look forward to bringing to The DHS Program (job-related or not!)? Dry wit, maybe some baked goods.

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.

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