PURPOSE Increasing noncommunicable disease burden in sub-Saharan Africa requires the urgent scale-up of pathology and laboratory medicine (PALM) services. To identify service gaps at the district level, we studied geographic variation in the correlation between travel time to health facilities and population density. METHODS We linked geospatial data for Tanzania from multiple sources. Facility locations were extracted from a comprehensive facility list in Africa. Data on geographic factors, demographics, and roads were collected from government and nonprofit databases. We classified facilities assuming increasing PALM service readiness by level: dispensaries, health centers, district hospitals, and regional/referral hospitals. We input these data into the AccessMod 5 algorithm to estimate travel time across Tanzania with 1-km resolution for each PALM classification. We then calculated district-level averages of population and travel time for each PALM category. Associations between these variables were estimated using a bivariable local indicator of spatial autocorrelation, specifying immediate contiguity neighborhood definition. Spatial analysis was restricted to 172 contiguous districts (islands not included). Significance tests were two sided, with an α of .05. RESULTS Analysis included 5,342 dispensaries, 667 health centers, 185 district hospitals, and 34 regional/referral hospitals. Maps revealed clusters of estimated travel time in excess of 6 hours in less populated western and southern districts. More districts reported an average travel time of less than 1 hour to the nearest dispensary (69%) than to regional/referral hospitals (16%). Bivariable local indicators of spatial autocorrelation revealed few significant clusters of spatial correlations; however, significant correlations between low population density and longer travel times in neighboring districts were obtained for 13%, 16%, 15%, and 13% of districts for dispensaries, health centers, district hospitals, and regional/referral hospitals, respectively. CONCLUSION Limited variability of district-level spatial correlations suggests somewhat equitable geographic allocation of PALM services in Tanzania, with small areas of low population density and long travel times that demand additional intervention. Limitations include a lack of ascertainment of specific PALM services.
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