Leveraging Routinely Collected Program Data to Inform Extrapolated Size Estimates for Key Populations in Namibia: Small Area Estimation Study.
Talia A LoebKalai WillisFrans VelishavoDaniel LeeAmrita RaoStefan David BaralKatherine Blair RucinskiPublished in: JMIR public health and surveillance (2024)
Using SAE approaches, we combined epidemiologic and program data to generate subnational size estimates for key populations in Namibia. Overall, estimates were highly sensitive to the inclusion of program data. Program data represent a supplemental source of information that can be used to align PSEs with real-world HIV programs, particularly in regions where population-based data collection methods are challenging to implement. Future work is needed to determine how best to include and validate program data in target settings and in key population size estimation studies, ultimately bridging research with practice to support a more comprehensive HIV response.
Keyphrases
- electronic health record
- quality improvement
- big data
- healthcare
- hiv infected
- primary care
- hiv positive
- public health
- hepatitis c virus
- human immunodeficiency virus
- hiv testing
- data analysis
- machine learning
- artificial intelligence
- south africa
- social media
- mass spectrometry
- single molecule
- case control
- genetic diversity
- health information