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PMA2020 Data


Public access to PMA2020 datasets will be granted in a layered approach, on a case-by-case basis, upon written request. Approval will be granted by the program country's Principal Investigator(s) and/or PMA2020's coordinating center in Baltimore. Following protocols guided by the Institutional Review Boards for human subjects research at the Johns Hopkins Bloomberg School of Public Health and at country partner institutions, de-identified PMA2020 data will be made publicly available as a zipped file via email.

PMA2020 will review all submitted requests and grant access to indicated datasets, or contact users for additional information if needed, and will share electronic copies of the data files with relevant supporting documentation.
View currently available datasets >>>

Types of Datasets:

When available, users will be able to request two separate types of survey datasets for each country and round: (1) Household and Female; (2) Service Delivery Point.
 
1. Household and Female merged dataset composed of:
     
     Household data: each household selected into the survey will have a unique identifier, and each member of the selected household will constitute one record in the dataset. Data obtained at the household level include information from the household roster and basic information about the household, such as ownership of livestock and durable goods, a household wealth index, as well as characteristics of the dwelling unit, including wall, floor and roof material, water sources, and sanitation facilities.
     
     Individual Female data: data include individual records for each eligible female identified in the household roster of selected households.  Included are measures of education; marriage; fertility and fertility preferences; family planning access, choice, and use; quality of family planning services; exposure to family planning media messages, and water, sanitation, and hygiene related information. The family planning data collected are confined to those needed for FP2020 indicators.
 
2. Service Delivery Points (SDP) data (in countries and rounds where facility-based surveys are conducted):
     
     Each health service delivery point is classified as one record. Variables include information about the provision and quality of reproductive health services and products, integration of health services, as well as water and sanitation within the health service delivery point. All survey datasets provided will include both interviews completed and interviews attempted but not completed.  Geographic information provided is limited to the primary sampling unit and the largest regional identifier (region, state, county, etc.), allowing for national and sub-national estimates.
 
Data codebook: Users can download a standard PMA2020 data codebook by clicking the links to the codebooks on the left of this page. The codebook provides the wording of each question, type of question, variable label and option choices and coding.  The codebook will be adapted for each country and round of data collection, as certain questions may change by country and round of data collection.  
 

File Types:

Datasets will be provided in a zipped file in two formats, .csv and .dta (version 12 or higher).  Codebooks will be provided as an Excel document and questionnaires provided in .pdf format.
 

Terms of Use:

  1. Due to limited capacity to respond to individual requests, user support will not be provided.
  2. Analytic access to data is limited to the specific uses specified by individual(s) who are approved.
  3. Partnering institutions reserve the right to limit access to select indicators and/or complete datasets.
  4. Publications from PMA2020 data should include the following suggested citation:
Performance Monitoring and Accountability 2020 (PMA2020) Project, [the name of the relevant PMA2020 partner institution(s)]. [Survey year]. [Country]. Baltimore, MD: PMA2020, Bill & Melinda Gates Institute for Population and Reproductive Health, Johns Hopkins Bloomberg School of Public Health.
 
To request access to PMA2020 datasets, click here.