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Geographic Access to Primary Health Facilities Dashboard

The Geographic Access to Primary Health Facilities Dashboard presents unprecedented estimates of the population with potential geographic access to primary care services across 25 countries in the Americas. The analysis was based on the quality of available data, which means not all countries in the region were included in this first release. The resulting data are disaggregated by subregion, country, administrative levels (levels 1 and 2), age groups, and sex, enabling a detailed and comparable view of primary care territorial coverage.

This dashboard provides a strategic foundation for advancing discussions on equitable access to health in the Americas, offering concrete evidence to guide actions aimed at strengthening primary care as a pillar of the response to chronic diseases.

Data Sources: The regional portal draws on data from multiple sources compiled by PAHO/WHO and other reliable sources.

Methods

To generate these estimates, georeferenced points of primary care facilities were extracted from the Master List of health units. Concentric buffers of 500, 1,000, 1,500, and 2,000 meters were drawn around each point to simulate influence areas based on linear distances. These zones were merged to eliminate overlaps and ensure that each area represented an exclusive coverage zone. Each resulting polygon was then linked to its nearest facility to guarantee a clear relationship between the estimated population and the corresponding point of care.

Next, high-resolution dasymetric population layers from WorldPop 2020, which provide estimates by sex and five-year age groups, were used to calculate the population within each coverage area. This calculation employed an exact spatial extraction technique, taking into account the proportion of each raster cell overlapping the influence polygon to achieve highly accurate population estimates.

The result is a robust database combining demographic and administrative attributes, offering an essential tool for assessing geographic equity in primary care access. Viewing these estimates across multiple territorial and demographic dimensions allows the identification of coverage gaps, supports the prioritization of interventions, and informs resource planning and allocation. Furthermore, integrating these data with epidemiological and socioeconomic indicators opens opportunities for more advanced spatial analyses, such as accessibility modeling or identifying areas that most urgently require network expansion.

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