Perspectives of HIV policy makers and program implementers regarding the design and utilization of HIV surveillance systems in Sub-Saharan African countries experiencing a declining HIV epidemic: a qualitative study

BackgroundThe burden of new HIV infections and HIV-related deaths have declined dramatically in sub-Saharan Africa (SSA). However, current HIV surveillance systems are primarily donor-funded and rely on data from population-based surveys and routine health services. These need to evolve so that they can reliably monitor future HIV trajectory, in the context of declining burden of HIV and limited donor funding. We qualitatively assessed stakeholder perceptions of the current status and future needs for HIV surveillance. MethodsFrom September 2024 to February 2025, we conducted a grounded-theory qualitative study whose participants were representatives of international HIV agencies, policy makers and health sector development partners and HIV programme managers from Malawi, Lesotho, Zimbabwe, Ghana and Kenya, and HIV programme implementers from Malawi. We conducted 28 online and in-person key informant interviews and three focus group discussions with 34 Malawi-based participants working at sub-national level. These were audio-recorded for transcription. We conducted sequential deductive and inductive content analyses. ResultsWe found that HIV programs in SSA are familiar with and have successfully used routine health system data, population-based surveys, and mathematical modeling for HIV surveillance and monitoring and evaluation (M&E). However, most respondents could not distinguish the differences between M&E and surveillance and were unaware of the key inputs for mathematical models used to estimate key impact indicators. They expressed concern over the parallel HIV data systems, lack of integration with the broader health surveillance systems, sub-optimal quality of routine facility-based data, and the huge cost and limited precision of population-based surveys. They recommended investment in several areas including data quality improvement, adoption of digital technology and artificial intelligence to improve the efficiency of the surveillance system, expanded stakeholder sensitization in mathematical modeling, implementation of targeted surveys focusing on high-risk populations, and prioritization of HIV morbidity and mortality indicators. ConclusionsFuture HIV surveillance strategies need to invest in institutionalizing local capacity for using multiple HIV data streams to inform key surveillance indicators through modeling and analytic tools, establishing management systems to enhance routine data quality, streamlining HIV surveillance and M&E indicators, and fostering disease surveillance integration. Targeted surveys will be required to complement routine facility-based surveillance.