Bias in observational study designs: cross sectional studies

Abstract The geographical area around a health facility characterizing the population that utilizes some or all of its services – a health facility catchment area (HFCA)-, forms the fundamental basis of estimating reliable population denominator for disease mapping and routine healthcare planning. Consequently, the approaches used to delineate the catchment area have a direct impact on the health of a population. To date, there is no systematic literature review documenting different approaches that have been used to define HFCAs while elucidating the implications on derived population denominators. To fill this gap, we systematically reviewed literature and documented approaches that have been used to define HFCA in sub–Saharan Africa (SSA). Simple to complex approaches have been used to define catchment areas in SSA with varying degrees of complexity and limitations in the last four decades. These approaches are mainly driven by lack of geocoded data on the residential address of care seekers and their care-seeking behaviour. To generate closer-to-reality HFCA, for robust disease mapping and healthcare planning, additional data and innovative approaches balancing between model complexity and routine programmatic use are required.