Mortalidade por COVID-19 em uma população do sudoeste de Minas Gerais

Abstract

Introduction: On December 31, 2019, the World Health Organization (WHO) was alerted to several cases of pneumonia in Wuhan City, Hubei Province, People's Republic of China. It was a new strain (type) of coronavirus that had not been identified before in humans. A week later, on January 7, 2020, Chinese authorities confirmed that they had identified a new type of coronavirus. Coronaviruses are everywhere. They are the second leading cause of the common cold (after rhinoviruses) and, until recent decades, rarely caused more serious illness in humans than the common cold. Objective: To describe mortality from COVID-19 and possible associated sociodemographic and clinical factors among users of two municipalities in the southwest of Minas Gerais. Methodology: Descriptive, retrospective, analytical and cross-sectional study, using secondary data from the e-SUS Notifica System and the Influenza Epidemiological Surveillance Information System - SIVEP-Influenza, of the Brazilian Ministry of Health. We included users over 18 years of age notified in both systems of the two municipalities of the study and excluded users whose notifications were flawed, making analysis impossible. The data collected referred to the total number of mild, moderate and severe cases of the disease, in the period from April 2020 to July 2022. Results: A total of 38,146 notified cases were identified in both systems, of which 20,594 were positive cases of COVID-19 (18,846 users notified in e-SUS Notifica and 1748 users notified in SIVEP-Influenza). Of these, 8.48% evolved to severe cases of the disease (SIVEP-Influenza), with the outcome of 1113 cured and 537 deaths. Advanced ages, predominance of males, white ethnicity, prevalence of respiratory signs and symptoms, and comorbidities such as heart disease and diabetes were observed for those who died. Conclusion: In the context of the municipalities studied, recognizing this profile is important in order to contribute with data records, planning and execution of public health policies in the different spheres, aimed at populations at higher risk of worsening and death from the disease. By recognizing the population groups most subject to complications and deaths due to the disease, such information becomes valuable tools to guide decision-making.