Estimating spatial disease rates using health statistics without geographic identifiers

Abstract Morbidity statistics can be reported as grouped data for health services rather than individual residence area, especially in low-middle income countries. Although such reports support some evidence-based decisions, these are of limited use if the geographical distribution morbidity cannot identified. This study estimates spatial rate Acute respiratory infections (ARI) census districts Cúcuta -Colombia, using an analysis providers. The scope (geographical area influence) each service was established from their and population covered. Three levels aggregation were considering primary, intermediate tertiary ARI cases per district then calculated mapped provider proportion level respectively. Hotspots risk identified Local Moran’s I statistic. There 98 providers that attended 8994, 18,450 91,025 1, 2 3, Higher rates found central south; northwest northeast; southwest with hotspots south west Cucuta. method used allowed overcoming limitations lacking information to implementing epidemiological analyses identify at communities. methodology socioeconomic contexts where geographic identifiers not attached statistics.