Defining service catchment areas in low-resource settings
Peter M. Macharia, Nicolas Ray, Emanuele Giorgi, Emelda A. Okiro, Robert W. Snow
Abstract
Defining an accurate, representative service catchment area is important for computing population denominators for disease mapping and efficient public planning, including health, education and social care.\n<br>\nThe growth in population settlement modelling techniques and provision of geocoded service databases has fuelled an increase in local and regional service access mapping to examine coverage and equity in much of sub-Saharan African countries.\n<br>\nHowever, metrics of service access and catchments are often implemented based on convenience, disregarding the implications on accuracy of the catchment population, complexities of service use and the likely implications for public service planning.\n<br>\nLack of high spatial resolution geolocated data on residential locations of the service users has led to the use of rudimentary, inexact approaches to complex processes that define service catchment areas and should be used with caution.\n<br>\nThe improved collection of residential addresses of service users and service providers has increased the ability to develop new innovative models of service catchment.\n<br>\nImproved data availability and data sharing must be accompanied by better models of service use.\n<br>\nIn this commentary, we revisit the issue by considering common approaches, key issues and best practices in defining a reliable service catchment area.\n<br>\nWe hope this will lead to further granular studies to populate and compare methods to improve the definition of service catchment areas in sub-Saharan Africa, ultimately improving efficiencies and equity in service use and more reliable interpretations of routine service use data.