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Características socioeconómicas, medidas gubernamentales y resultados sanitarios de COVID-19

  • Tomás Gómez Rodríguez [1] ; Arturo Martínez Camacho [1] ; Humberto Ríos Bolívar [2]
    1. [1] Universidad Autónoma del Estado de Hidalgo

      Universidad Autónoma del Estado de Hidalgo

      México

    2. [2] Instituto Politécnico Nacional

      Instituto Politécnico Nacional

      México

  • Localización: Contaduría y administración, ISSN 0186-1042, ISSN-e 2448-8410, Vol. 66, Nº. Extra 5, 2021 (Ejemplar dedicado a: lecciones de la pandemia de Covid-2019)
  • Idioma: español
  • Títulos paralelos:
    • Socioeconomic characteristics, containment measures and health outcomes of COVID-19
  • Enlaces
  • Resumen
    • español

      Se analiza el impacto de las características socioeconómicas pre existentes a la pandemia, así como las medidas tomadas por los distintos gobiernos para reducir los efectos de la pandemia de COVID-19, con el fin de examinar su contribución al número de casos y decesos. Para analizar estas propuestas se emplean dos muestras. Ambas muestras se conforman con datos de 187 países organizados en forma transversal, el método de estimación es Mínimos Cuadrados Ordinarios. Los resultados muestran evidencia de que las variables PIB per cápita y gastos sanitarios (DE) tienen una relación positiva con los casos totales de COVID-19 por millón. Mientras que la variable pobreza extrema muestra evidencia de una relación negativa con respecto al número de casos y decesos totales por millón. Por otro lado, se encuentra evidencia de una relación positiva entre el número de decesos totales por millón (DM) y las variables índice de repuesta gubernamental (IRG) y gastos sanitarios.

    • English

      The impact of pre-pandemic socioeconomic characteristics, as well as the measures taken by different governments to reduce the effects of the COVID-19 pandemic, are analyzed in order to examine their contribution to the number of cases and deaths. Two samples are used to analyze these proposals. Both samples are made up of data from 187 countries organized in a cross-sectional manner, the estimation method is Ordinary Least Squares. The results show evidence that the variables GDP per capita and health expenditure (DE) have a positive relationship with the total cases of COVID-19 per million. While the extreme poverty variable shows evidence of a negative relationship with respect to the number of cases and total deaths per million. On the other hand, there is evidence of a positive relationship between the number of total deaths per million (DM) and the variables government response index (IRG) and health expenditures.

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