Sistema de suporte à decisão espacial Fuzzy para o combate à Covid-19 no estado da Paraíba, Brasil

• Ano de defesa: 2021
• Autor(a) principal: Silva, Luiz Henrique da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Ciências Exatas e da Saúde; Programa de Pós-Graduação em Modelos de Decisão e Saúde; UFPB
• Palavras-chave em Português: Infecções por coronavírus; Análise espacias; Epidemiologia; Lógica fuzzy; Gestão em saúde; Coronavirus infections; Spatial analysis; Epidemiology; Fuzzy logic; Health management; CNPQ::CIENCIAS DA SAUDE::SAUDE COLETIVA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/21506

Early monitoring of COVID-19 encourages efficient decision-making in the face of outbreaks and epidemics. Managers and professionals, once provided with this information can outline effective and specific public policies. This study aimed to identify the municipalities according to four levels of priority "non-priority", "trend to non-priority", "tendency to priority" and "priority" to combat COVID-19 in the state of Paraíba, from a Spatial Decision Support System based on fuzzy logic. This was an ecological, retrospective study of quantitative approach, with secondary data from the cases of COVID-19 of the State Department of Health of Paraíba. The study population consisted of all confirmed cases of COVID-19 in the state of Paraíba from the 12th epidemiological week of 2020 to the 1st epidemiological week of 2021. The data were analyzed through the modules of the Spatial Decision Support System architecture: Statistical Analysis, Normality Test, Spatial Incidence Ratio, Spatial and space-time Analysis, Correlation Analysis and Fuzzy logic, using Excel 2016, R and SaTScan software. A total of 172,261 cases and 3,800 deaths were reported due to COVID-19, with the state capital recording the highest number. Descriptive statistics: Individuals from 30 to 39 (23.15%), female (55.77%) and mixed race/color (51.03%) were the most affected; the capital was the first epicenter of COVID19 in the state. Therefore, the application of the Fuzzy rules-based system allowed the detection and spatial visualization of priority municipalities, such as small and medium-sized municipalities São José do Sabugi, São Bento, Ingá and Guarabira. The present study allowed the identification of different levels of priority and, from then on, direct the decision-making of managers and health professionals according to the territory and the multiple risk factors for COVID-19 in the state of Paraíba.