Covid-19 Epidemiology in the Southern Brazilian States from 2020 to 2024 - , Eduarda Caroline Ceriolli Martinello; , Almir Walker; , Junir Antônio Lutinski; , Maria Assunta Busato; , Sinval Adalberto Rodrigues Junior; , Thiago André Carniel (Archives of Current Research International, 2025)
Aims: analyze the epidemiology of Covid-19 in southern Brazil from 2020 to 2024 Study Design: this is an epidemiological, descriptive and cross-sectional study. Place and Duration of Study: Brazil. held from April to June 2024. Methodology: data from the IT Department of the Unified Health System were utilized. The Kruskal–Wallis test was employed to compare and analyze the incidence, mortality, and lethality of COVID-19 across the states and municipalities of southern Brazil. The associations between variables were assessed using the Chi-square test in the Past software. Spatial distribution maps of incidence and mortality in the region were generated using MATLAB. Results: Paraná recorded the highest mortality rate (410,1 per 100.000 inhabitants) and lethality rate (1,6%) among the three states. However, the Paraná region had the lowest incidence of cases (26.367,3 per 100.000 inhabitants). Rio Grande do Sul had an incidence of 28.886,6 per 100.000 inhabitants, a mortality rate of 374,4 per 100.000 inhabitants, and a lethality rate of 1.4%. Finally, Santa Catarina had an incidence of 27.353,8 per 100.000 inhabitants and the lowest mortality (303,5 per 100.000) and lethality (1,1%) rates compared to the other regions. Cases and deaths were more concentrated in regions bordering Argentina and Paraguay, as well as along the borders with the states of Mato Grosso do Sul and São Paulo, in addition to the coastal areas. In 2022, the highest incidence was recorded across all states in the region, while the highest lethality and mortality rates occurred in 2021. Conclusion: the mortality and lethality rates of COVID-19 were not homogeneous among the states in the southern region. The distribution of mortality and lethality in the region for each year evaluated may be attributed to the stage of population immunization and the predominant variant. These data are important for guiding public health policies in the management of future pandemics.