Private Sector Counts - Child Health

Explore the role of public and private sources of care

About the Data

The data used in this tool come from the Demographic and Health Surveys (DHS) program. For a detailed explanation of the indicators and surveys of the DHS program, go to

Private Sector Counts - Child Health uses the most recent (as of January 2020) DHS surveys from 24 countries. All USAID maternal and child survival priority countries are included with the exception of South Sudan, which does not have a DHS survey. A full list of countries and surveys used is included below.

The countries are divided into three regions: seven countries in Asia, six in West and Central Africa, and nine in East and Southern Africa. Haiti and Yemen are also included but do not fit into the three regional categories.

All DHS data used in the child health analysis are reported by mothers who were asked about illnesses each of their children under age five may have experienced in the two weeks before the interview. Mothers’ reports of these illnesses are categorized as described below. If their child had one or more illnesses, mothers were asked if they sought treatment or advice from any source for that illness. If they sought treatment or advice, mothers were asked where they went, categorized as described below.

Use the download icon at the bottom of each visualization to download a PDF of the visualization or an Excel file of the raw data.

Definition of Terms

Illness prevalence - The percentage of children under five who were sick in the two weeks preceding the survey, according to data reported by mothers. The prevalence for each individual illness shows the percentage of children who experienced that illness in the last two weeks, even if they also experienced another illness.

Specific definitions for each illness are noted below.

Diarrhea – A report of three or more watery stools within 24 hours.

Acute respiratory infection (ARI) – A reported cough with chest-related rapid or difficult breathing that is chest-related; a non-specific proxy for suspected pneumonia.

Fever - A reported fever, a non-specific proxy for malaria

One or more illnesses - Children who are sick with one illness may also be sick with another illness. Thus, the combined illness prevalence includes some co-morbidity and shows the prevalence of children who are sick with at least one of the three illnesses above.

This analysis focuses on diarrhea, ARI symptoms, and fever because diarrheal disease, pneumonia, and malaria are some of the most common causes of child mortality. Please note that DHS data do not report whether children recently had malaria or pneumonia because both of these illnesses must be confirmed in a laboratory. Instead, the DHS reports whether or not children had recent fever as a non-specific proxy for malaria or symptoms of ARI as a non-specific proxy for pneumonia.

Care-seeking level – The percentage of mothers with sick children in the past two weeks who reported seeking advice or treatment for their child’s illness from any source.

Care-seeking source – The sources where mothers reported seeking advice or treatment for their sick children. The sources are grouped into private sector, public sector, and other sources.

Private sector includes private clinics, hospitals, and doctors; nongovernmental and faith-based organizations; and pharmacies, shops, and markets.

Public sector includes government clinics, hospitals, health posts, and community health workers.

Other sources include traditional healers, friends, and family members.

This analysis shows where caregivers go for treatment, regardless of their level of access to different sources of care. It does not reflect where caregivers might choose to go if they had access to all sources of care.

Wealth quintiles – The analysis uses the wealth quintiles produced by the DHS. Wealth quintiles are constructed using an asset-based index of items owned by each household and are country-specific. For this reason, this analysis does not aggregate wealth-quintiles from the individual country-level into regional results.

Regional average estimates – All countries were weighted equally to produce regional averages.

Countries and surveys used for analysis

  1. Asia
    • Afghanistan 2015
    • Bangladesh 2014
    • India 2015-16
    • Indonesia 2017
    • Myanmar 2015-16
    • Nepal 2016
    • Pakistan 2017-18

  2. West and Central Africa
    • DRC, 2013-14
    • Ghana 2014
    • Liberia 2013
    • Mali 2018
    • Nigeria 2018
    • Senegal 2017

  3. East and Southern Africa
    • Ethiopia 2016
    • Kenya 2014
    • Madagascar 2009
    • Malawi 2015-16
    • Mozambique 2011
    • Rwanda 2015-16
    • Tanzania 2015-16
    • Uganda 2016
    • Zambia 2013-4

  4. Other
    • Haiti 2016-17
    • Yemen 2013