National COVID-19 vaccination plan: using artificial spatial intelligence to overcome challenges in Brazil. / Plano nacional de vacinação contra a COVID-19: uso de inteligência artificial espacial para superação de desafios.

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.

O objetivo deste artigo é analisar o uso da inteligência artificial espacial no contexto da imunização contra COVID-19 para a seleção adequada dos recursos necessários. Trata-se de estudo ecológico de caráter transversal baseado em uma abordagem espaço-temporal utilizando dados secundários, em Unidades Básicas de Saúde do Brasil. Foram adotados quatro passos analíticos para atribuir um volume de população por unidade básica, aplicando algoritmos de inteligência artificial a imagens de satélite. Em paralelo, as condições de acesso à internet móvel e o mapeamento de tendências espaço-temporais de casos graves de COVID-19 foram utilizados para caracterizar cada município do país. Cerca de 18% da população idosa brasileira está a mais de 4 quilômetros de distância de uma sala de vacina. No total, 4.790 municípios apresentaram tendência de agudização de casos de Síndrome Respiratória Aguda Grave. As regiões Norte e Nordeste apresentaram o maior número de Unidades Básicas de Saúde com mais de 5 quilômetros de distância de antenas de celular. O Plano nacional de vacinação requer o uso de estratégias inovadoras para contornar os desafios do país. O uso de metodologias baseadas em inteligência artificial espacial pode contribuir para melhoria do planejamento das ações de resposta à COVID-19.

The covid-19 pandemic and hospital morbidity due to mental and behavioral disorders in Brazil: an interrupted time series analysis, from January 2008 to July 2021.

OBJECTIVE: to analyze records of hospitalizations due to mental and behavioral disorders before and after the beginning of the covid-19 pandemic in Brazil, from January 2008 to July 2021. METHODS: this was a descriptive ecological interrupted time series study, using secondary data retrieved from the Brazilian National Health System Hospital Information System; a time series analysis of hospitalizations was conducted based on a population-weighted Poisson regression model; relative risk (RR) and respective 95% confidence intervals (95%CI) were calculated. RESULTS: we identified 6,329,088 hospitalizations due to mental and behavioral disorders; hospitalization rates showed an 8% decrease (RR = 0.92; 95%CI 0.91;0.92) after the start of the pandemic, compared to the pre-pandemic period. CONCLUSION: the pandemic changed the trend of hospitalizations due to mental and behavioral disorders in Brazil; the drop observed in the period is evidence that the pandemic affected the mental health care network.