Differences between gridded population data impact measures of geographic access to healthcare in sub-Saharan Africa

Knowing where people reside and what health services are accessible to them in a timely manner can make a difference in life-or-death situations. Geographic models that mimic the journey of patients can help understand where people cannot access healthcare and can provide valuable insights for policy and research. Population distribution data is essential for these models, as it determines the relative coverage provided by the existing health system. However, there are several datasets available on population distribution that vary widely. In this study, we quantify the impact of using six different population data sets to calculate healthcare coverage in sub-Saharan Africa. Our results show large continental, national, and subnational differences between the different gridded population datasets, which can strongly influence the uncertainty of healthcare accessibility models and thus the decisions based on them.