National covid-19 vaccination plan: Using artificial spatial intelligence to overcome challenges in brazil

Abstract

This article explores the use of spatial artificial intelligence to estimate the resources needed to implement Brazil’s COVID-19 immunization campaign. Using secondary data, we conducted a cross-sectional ecological study adopting a time-series design. The unit of analysis was Brazil’s primary care centers (PCCs). A four-step analysis was performed to estimate the population in PCC catchment areas using artificial intelligence algorithms and satellite imagery. We also assessed internet access in each PCC and con ducted a space-time cluster analysis of trends in cases of SARS linked to COVID-19 at municipal level. Around 18% of Brazil’s elderly population live more than 4 kilometer from a vaccination point. A total of 4,790 municipalities showed an upward trend in SARS cases. The number of PCCs located more than 5 kilometer from cell towers was largest in the North and Northeast regions. Innovative strategies are needed to address the challenges posed by the implementation of the country’s National COVID-19 Vaccination Plan. The use of spatial artificial intelligence-based methodologies can help improve the country’s COVID-19 response.