Epidemiological behavior of the COVID-19 contamination curve in Brazil: Time-series analysis

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Abstract

Brazil is experiencing the greatest episode of sanitary collapse ever known in the country’s history. Therefore, the relevance of this study is highlighted for the scientific advance of the epidemiological behavior of the virus in Brazil, enabling the development of analyses and discussions on the factors that influenced the high rates of contamination by SARS-CoV-2 in the country. Given the above, this study aims to analyze the epidemiological behavior of the COVID-19 contamination curve by epidemiological weeks (EW), in the years 2020–2021, in Brazil. This is an ecological study of time series, prepared using information collected through secondary means. The country of origin of the study is Brazil, and its main theme is the number of people infected during the COVID-19 pandemic, this being the dependent variable of the study. The data has been analyzed from February 23, 2020, when the first case was confirmed in Brazil, to January 1, 2022. In 2021, the country’s graph shows an exponential growth, reaching a peak of approximately 250 new cases per 100,000 inhabitants in the 12th EW. This data represents the highest rate of the pandemic in Brazil, and did not vary significantly for the next twelve weeks. Thus, it was identified that Brazil was severely impacted by the new coronavirus, considering the high rates of confirmed cases of the virus in the country, the low adherence of the population to preventive measures, the late start of mass vaccination in the Brazilian population, and the lack of structure in the health system, which was not appropriately prepared for the high demand generated by COVID-19.

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  1. SciScore for 10.1101/2022.04.25.22274291: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The next step after data collection was to clean the data in Microsoft Excel® software and then perform a more rigorous analysis in JoinPoint software, version 4.9.0.0 (Surveillance Research, National Cancer Institute, USA), provided by the National Cancer Institute of the United States (http://surveillance.cancer.gov/joinpoint/) with free access and open to all public.
    Microsoft Excel®
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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