Situação da Covid-19 no estado do Tocantins: a relação com os indicadores socioeconômicos e de saúde

Abstract

The COVID-19 pandemic exposed social and economic inequalities in different regions of Brazil, and the state of Tocantins was no exception. Factors such as the Municipal Human Development Index (IDHM), the Social Vulnerability Index (IVS), and the Sustainable Development Cities Index (IDSC) proved to be crucial for understanding the spread of the disease and its impacts in various regions. This study aims to analyze the relationship between COVID-19 incidence and mortality rates and socioeconomic and health indicators in the 139 municipalities of Tocantins. This ecological study includes temporal and spatial analysis. Data on confirmed cases and COVID-19 deaths recorded between March 17, 2020, and March 31, 2023, were collected. Generalized Additive Models (GAM) were used to explore non-linear relationships between the incidence and mortality rates and the socioeconomic and health indicators. Temporal (epidemiological weeks) and geographic (latitude and longitude) variables were included to capture spatial and temporal variations. During the study period, the state of Tocantins recorded 366,609 confirmed cases of COVID-19 and 4,235 deaths over 159 epidemiological weeks. The highest incidence rate was recorded in epidemiological week 4 of 2022, with 925.99 confirmed cases per 100,000 inhabitants, and the highest mortality rate occurred in week 12 of 2021, with 11.63 deaths per 100,000 inhabitants. Regarding the relationship with socioeconomic and health indicators, the relationship between the incidence rate and IDSC (edf = 6.279, p < 0.001) was significant and non-linear. Municipalities with higher sustainable development indices had lower incidence rates. The same trend was observed for the IDHM (edf = 7.944, p < 0.001). It was also observed that the incidence rate increased in municipalities with higher social vulnerability, measured by the IVS (edf = 2.001, p < 0.001), and higher infant mortality. However, the model adjusted for mortality rate did not show significant precision. The results indicate that municipalities with better socioeconomic and health conditions were more successful in mitigating the pandemic's impacts. The findings suggest that public policies aimed at improving human development indicators and reducing social inequalities may be effective in mitigating future health crises. The study also highlights the importance of using geospatial data to understand the unequal distribution of pandemic impacts.