Plano nacional de vacinação contra a COVID-19: uso de inteligência artificial espacial para superação de desafios
Thiago Augusto Hernándes Rocha, Ghabriela Moura Boitrago, Rayanne Barbosa Mônica, Dante Grapiuna de Almeida, Núbia Cristina da Silva, Débora Marcolino Silva, Sandro Haruyuki Terabe, Catherine A. Staton, Luiz Augusto Facchini, João Ricardo Nickenig Vissoci
Abstract
This article explores the use of spatial artificial intelligence to estimate the resources needed to implement Brazil's COVID-19 immu nization campaign. Using secondary data, we conducted a cross-sectional ecological study adop ting a time-series design. The unit of analysis was Brazil's primary care centers (PCCs). A four-step analysis was performed to estimate the popula tion in PCC catchment areas using artificial in telligence 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 stra tegies 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.