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The COVID-19 Mortality Rate in Latin America: A Cross-Country Analysis

Author

Listed:
  • Fernando José Monteiro de Araújo

    (Graduate Program of Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre 90010-150, Brazil)

  • Renata Rojas Guerra

    (Graduate Program of Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre 90010-150, Brazil
    Departament of Statistics, Universidade Federal de Santa Maria, Santa Maria 97105-900, Brazil)

  • Fernando Arturo Peña-Ramírez

    (Departament of Statistics, Universidade Federal de Santa Maria, Santa Maria 97105-900, Brazil)

Abstract

Latin America was one of the hotspots of COVID-19 during the pandemic. Therefore, understanding the COVID-19 mortality rate in Latin America is crucial, as it can help identify at-risk populations and evaluate the quality of healthcare. In an effort to find a more flexible and suitable model, this work formulates a new quantile regression model based on the unit ratio-Weibull (URW) distribution, aiming to identify the factors that explain the COVID-19 mortality rate in Latin America. We define a systematic structure for the two parameters of the distribution: one represents a quantile of the distribution, while the other is a shape parameter. Additionally, some mathematical properties of the new regression model are presented. Point and interval estimates of maximum likelihood in finite samples are evaluated through Monte Carlo simulations. Diagnostic analysis and model selection are also discussed. Finally, an empirical application is presented to understand and quantify the effects of economic, social, demographic, public health, and climatic variables on the COVID-19 mortality rate quantiles in Latin America. The utility of the proposed model is illustrated by comparing it with other widely explored quantile models in the literature, such as Kumaraswamy and unit Weibull regressions.

Suggested Citation

  • Fernando José Monteiro de Araújo & Renata Rojas Guerra & Fernando Arturo Peña-Ramírez, 2024. "The COVID-19 Mortality Rate in Latin America: A Cross-Country Analysis," Mathematics, MDPI, vol. 12(24), pages 1-17, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:24:p:3934-:d:1543596
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    References listed on IDEAS

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    1. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    2. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    3. Juan Li & Shengjie Lai & George F. Gao & Weifeng Shi, 2021. "The emergence, genomic diversity and global spread of SARS-CoV-2," Nature, Nature, vol. 600(7889), pages 408-418, December.
    4. Sachiko Kodera & Essam A. Rashed & Akimasa Hirata, 2020. "Correlation between COVID-19 Morbidity and Mortality Rates in Japan and Local Population Density, Temperature, and Absolute Humidity," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
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