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  1. Article ; Online: COVID-19 epidemic curve in Brazil: a sum of multiple epidemics, whose inequality and population density in the states are correlated with growth rate and daily acceleration. An ecological study.

    Pinto, Airandes de Sousa / Rodrigues, Carlos Alberto / Nascimento Sobrinho, Carlito Lopes / Cruz, Lívia Almeida da / Santos Junior, Edval Gomes Dos / Nunes, Paulo Cesar / Costa, Matheus Gomes Reis / Rocha, Manoel Otávio da Costa

    Revista da Sociedade Brasileira de Medicina Tropical

    2022  Volume 55, Page(s) e0118

    Abstract: Background: The epidemic curve has been obtained based on the 7-day moving average of the events. Although it facilitates the visualization of discrete variables, it does not allow the calculation of the absolute variation rate. Recently, we ... ...

    Abstract Background: The epidemic curve has been obtained based on the 7-day moving average of the events. Although it facilitates the visualization of discrete variables, it does not allow the calculation of the absolute variation rate. Recently, we demonstrated that the polynomial interpolation method can be used to accurately calculate the daily acceleration of cases and deaths due to COVID-19. This study aimed to measure the diversity of epidemic curves and understand the importance of socioeconomic variables in the acceleration, pek cases, and deaths due to COVID-19 in Brazilian states.
    Methods: Epidemiological data for COVID-19 from federative units in Brazil were obtained from the Ministry of Health's website from February 25 to July 11, 2020. Socioeconomic data were obtained from the Instituto Brasileiro de Geografia e Estatística (https://www.ibge.gov.br/). Using the polynomial interpolation methods, daily cases, deaths and acceleration were calculated. Moreover, the correlation coefficient between the epidemic curve data and socioeconomic data was determined.
    Results: The combination of daily data and case acceleration determined that Brazilian states were in different stages of the epidemic. Maximum case acceleration, peak of cases, maximum death acceleration, and peak of deaths were associated with the Gini index of the gross domestic product of Brazilian states and population density but did not correlate with the per capita gross domestic product of Brazilian states.
    Conclusions: Brazilian states showed heterogeneous data curves. Population density and socioeconomic inequality were correlated with a more rapid exponential growth in new cases and deaths.
    MeSH term(s) Acceleration ; Brazil/epidemiology ; COVID-19 ; Epidemics ; Humans ; Population Density ; SARS-CoV-2
    Language English
    Publishing date 2022-02-25
    Publishing country Brazil
    Document type Journal Article
    ZDB-ID 1038126-0
    ISSN 1678-9849 ; 0037-8682
    ISSN (online) 1678-9849
    ISSN 0037-8682
    DOI 10.1590/0037-8682-0118-2021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Covid-19 growth rate analysis

    Pinto, Airandes de Sousa / Santos Júnior, Edval Gomes dos / Rodrigues, Carlos Alberto / Nunes, Paulo Cesar Mendes / Cruz, Livia Almeida da / Costa, Matheus Gomes Reis / Rocha, Manoel Otávio da Costa

    Revista da Sociedade Brasileira de Medicina Tropical v.53 2020

    application of a low-complexity tool for understanding and comparing epidemic curves

    2020  

    Abstract: Abstract INTRODUCTION: The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial ... ...

    Abstract Abstract INTRODUCTION: The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation method. METHODS: Covid-19 epidemic curves from Brazil, Germany, the United States, and Russia were obtained. We calculated the instantaneous acceleration of the curve using the first derivative of the representative polynomial. RESULTS: The acceleration for all curves was obtained. CONCLUSIONS: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation.
    Keywords Covid-19 ; SARS-CoV-2 ; Polynomial interpolation ; covid19
    Language English
    Publishing date 2020-01-01
    Publisher Sociedade Brasileira de Medicina Tropical - SBMT
    Publishing country br
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves.

    Pinto, Airandes de Sousa / Santos Júnior, Edval Gomes Dos / Rodrigues, Carlos Alberto / Nunes, Paulo Cesar Mendes / Cruz, Livia Almeida da / Costa, Matheus Gomes Reis / Rocha, Manoel Otávio da Costa

    Revista da Sociedade Brasileira de Medicina Tropical

    2020  Volume 53, Page(s) e20200331

    Abstract: Introduction: The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial ... ...

    Abstract Introduction: The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation method.
    Methods: Covid-19 epidemic curves from Brazil, Germany, the United States, and Russia were obtained. We calculated the instantaneous acceleration of the curve using the first derivative of the representative polynomial.
    Results: The acceleration for all curves was obtained.
    Conclusions: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation.
    MeSH term(s) Betacoronavirus ; Brazil/epidemiology ; COVID-19 ; Coronavirus Infections/epidemiology ; Coronavirus Infections/mortality ; Data Analysis ; Germany/epidemiology ; Humans ; Incidence ; Normal Distribution ; Pandemics ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/mortality ; Russia/epidemiology ; SARS-CoV-2 ; United States/epidemiology
    Keywords covid19
    Language English
    Publishing date 2020-07-06
    Publishing country Brazil
    Document type Journal Article
    ZDB-ID 1038126-0
    ISSN 1678-9849 ; 0037-8682
    ISSN (online) 1678-9849
    ISSN 0037-8682
    DOI 10.1590/0037-8682-0331-2020
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves

    Pinto, Airandes de Sousa / Santos Junior, Edval Gomes Dos / Rodrigues, Carlos Alberto / Nunes, Paulo Cesar Mendes / Cruz, Livia Almeida da / Costa, Matheus Gomes Reis / Rocha, Manoel Otavio da Costa

    Revista da Sociedade Brasileira de Medicina Tropical

    Abstract: INTRODUCTION: The acceleration of new cases is important for the characterization and comparison of epidemic curves The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation ... ...

    Abstract INTRODUCTION: The acceleration of new cases is important for the characterization and comparison of epidemic curves The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation method METHODS: Covid-19 epidemic curves from Brazil, Germany, the United States, and Russia were obtained We calculated the instantaneous acceleration of the curve using the first derivative of the representative polynomial RESULTS: The acceleration for all curves was obtained CONCLUSIONS: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #636451
    Database COVID19

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