Dinâmica temporal e espacial dos casos de Covid-19 gerais e os relacionados ao trabalho notificados no município de Fortaleza-Ceará

• Ano de defesa: 2024
• Autor(a) principal: Fernandes, Mike Douglas Lopes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Acidentes de trabalho; Covid-19; Saúde Ocupacional; Monitoramento Epidemiológico; Accidents, Occupational; Occupational Health; Epidemiological Monitoring; CNPQ::CIENCIAS DA SAUDE::SAUDE COLETIVA::SAUDE PUBLICA
• Link de acesso: http://repositorio.ufc.br/handle/riufc/79713

Introduction: Covid-19 has revived old concerns about occupational health and safety. Occupational exposure to the biological agent put all workers at risk. Some professional categories are more prone to contamination, and their social and labor factors can be contributory. Objective: To analyze the temporal and spatial dynamics of overall Covid-19 cases and work-related cases reported in Fortaleza, Ceará, from 2020 to 2022. Methods: spatial ecological study, where data on Covid 19 from E-SUS Notifica and work-related Covid-19 registered in SINAN of Fortaleza CE, from 2020 to 2022, were analyzed. Descriptive analysis was carried out using absolute and relative frequency. Covid-19 incidence rates were calculated and smoothed to reduce biases from random fluctuations using the empirical Bayesian spatial estimator. The Moran Index was used to estimate spatial correlations of Covid-19 incidence. The Global Indices were calculated and subsequently, the local ones, which were arranged using the categorizations of the LISA map. (LISA map Local Indicators of Spatial Association). To identify high and low-risk neighborhoods for Covid-19, the spatial scanning technique was used. The descriptive analysis was conducted in Microsoft Excel 365, the Bayesian rates and the Moran's Index in GeoDa 1.20, and the scan in SaTScan 10.1.2. Results: In E-SUS Notifica, three peaks of the disease were observed: June-2020, March-2021, and January-2022. In the spatial distribution: in 2020 the highest rate ranged from 31.67 to 55.86 cases/1,000 inhabitants, in 2022 it ranged from 64.16 to 85.88 cases/1,000 inhabitants. The results of the Global Moran's Index demonstrated statistically significant dependence (p<0.001) in all the analyzed years [2020: I=0.416; 2021: I=0.137; 2022: I=0.238]. According to the LISA map, it was observed that 2020 mostly showed a high-high pattern in wealthy neighborhoods, while a low-low pattern was seen in peripheral neighborhoods. In 2022, the location of the high-high and low low patterns is similar to 2020. In SINAN, the temporal distribution of work-related Covid-19 cases was observed: peak in June 2020, July 2021, and January 2022. In the spatial distribution: in 2020 the highest rate varied from 1.20 to 2.34 cases/1,000 inhabitants, dropping to 1.10 to 1.45 cases/1,000 inhabitants in 2021, and in 2022 it varied from 0.48 to 0.93 cases/1,000 inhabitants. The results of the Global Moran's Index demonstrated statistically significant dependence (p<0.001) in the years 2021 [I=0.380 p<0.001] and 2022 [I=0.358 p<0.001], while the year 2020 was not significant [I=0.087 p=0.052]. The clustering patterns indicated on the LISA map appeared distinctly. In 2020, the high-high pattern was identified in neighborhoods to the West, while the low-low pattern appeared dispersed on the map. In 2021, the high-high standard concentrated in the north, reaching 17 neighborhoods. And in 2022, the high-high pattern was predominant in the periphery. Low-low patterns were diffusely identified by the map. Final Considerations: This research provided a comprehensive view of the spatial dynamics of Covid-19 incidence in two populations. Such analyses can contribute to mitigating the effects of future health crises, encompassing occupation as an important axis for health surveillance.