Tulane University School of Public Health; University of Kinshasa School of Public Health and The Bill & Melinda Gates Institute for Population and Reproductive Health at The Johns Hopkins Bloomberg School of Public Health; and Jhpiego. Performance Monitoring for Action (PMA) GPS Dataset, PMA2020/DRC-GPS. 2020. DRC and Baltimore, Maryland, USA. https://doi.org/10.34976/d12y-1z67
Tulane University School of Public Health, University of Kinshasa School of Public Health; the Bill & Melinda Gates Institute for Population and Reproductive Health at The Johns Hopkins Bloomberg School of Public Health; and Jhpiego.
In PMA surveys, GPS coordinate data are collected at the household level during the household listing process and after the completion of every household interview. The household listing process involves listing every household in a sampled enumeration area (EA). EAs usually include about 200 households. Within each EA, between 35 and 42 households are randomly selected for the household interview per PMA survey round. The GPS data are recorded as geographic coordinates (i.e. degrees in latitude and longitude). During ideal GPS data collection situations (i.e. flat horizon, no obstructions from vegetation canopy or buildings), the level of accuracy of the coordinates is typically within six meters. However, because GPS data can be used to identify individuals, raw GPS data from confidential surveys cannot be released publicly. Performance Monitoring for Action (PMA) uses the DHS approach to randomly displace the GPS latitude and longitude positions of PMA survey respondents. This procedure nearly eliminates the likelihood of identifying individuals with GPS data, yet retains the locational detail for spatial analysis. PMA data can be used to perform research using location information while respondent confidentiality is maintained.
Democratic Republic of Congo