The first year of the COVID-19 pandemic in an indigenous population in Brazil: an epidemiological study

ABSTRACT This cross-sectional observational study that describes the epidemiological data of the first year of the COVID-19 pandemic in the Mato Grosso do Sul State, aimed to demonstrate the differences between indigenous and non-indigenous populations, characterize confirmed cases of COVID-19 according to risk factors related to ethnicity, comorbidities and their evolution and to verify the challenges in facing the disease in Brazil. SIVEP-Gripe and E-SUS-VE, a nationwide surveillance database in Brazil, from March 2020 to March 2021 in Mato Grosso do Sul state, were used to compare survivors and non-survivors from indigenous and non-indigenous populations and the epidemiological incidence curves of these populations. A total of 176,478, including 5,299 indigenous people, were confirmed. Among the indigenous population, 52.5% (confidence interval [CI] 51.2-53.9) were women, 38% (CI 36.7-39.4) were 20-39 years old, 56.7% were diagnosed by rapid antibody tests, 12.3% (CI 95%:11.5-13.2) had at least one comorbidity, and 5.3% (CI 95%:4.7-5.9) were hospitalized. In the non-indigenous patients, 56.8% were confirmed using RT-PCR, 4.4% (CI 95%:4.3-4.5) had at least one comorbidity, and 8.0% (CI 95%:7.9-8.2) were hospitalized. The majority of non-survivors were ≥60 years old (65.1% indigenous vs. 74.1% non-indigenous). The mortality in indigenous people was more than three times higher (11% vs. 2.9%). Indigenous people had a lower proportion of RT-PCR diagnoses; deaths were more frequent in younger patients and were less likely to be admitted to hospital. Mass vaccination may have controlled the incidence and mortality associated with COVID-19 in this population during the period of increased viral circulation.

Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil

Abstract INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.