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WP02/20 Datos de mortalidad diarios durante la crisis del COVID-19: una propuesta de mejora

Author

Listed:
  • Juan Equiza-Goñi

    () (University of Navarra)

Abstract

Cuando una crisis epidemiológica recrudece, el exceso de mortalidad publicado diariamente por MoMo (CNE-Instituto de Salud Carlos III) está gravemente sesgado a la baja. La razón es que el retraso habitual en la notificación de las defunciones se prolonga precisamente en esos momentos en los que dichas estimaciones tienen mayor relevancia social y epidemiológica. Proponemos ajustar los datos diarios (o “en tiempo real†) aplicando proyecciones en el futuro de revisiones observadas de datos ya publicados. Dichas revisiones suman defunciones que se notifican con retraso a excesos de mortalidad ya anunciados. Aplicamos este método a los excesos de mortalidad publicados por MoMo entre el 15 de abril y el 25 de mayo de 2020 durante la crisis del COVID-19 en España. Las correcciones basadas en los modelos polinómicos reducen entre un 18 y un 25% la raíz del error cuadrático medio (RMSE) de los datos “en tiempo real†.

Suggested Citation

  • Juan Equiza-Goñi, 2020. "WP02/20 Datos de mortalidad diarios durante la crisis del COVID-19: una propuesta de mejora," Faculty Working Papers 01/20, School of Economics and Business Administration, University of Navarra.
  • Handle: RePEc:una:unccee:wp0120
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    File URL: http://www.unav.edu/documents/10174/6546776/UNAV_0220/73afd8b1-6cbd-23c2-6ebb-815d40468827
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    More about this item

    Keywords

    monitoreo epidemiológico; coronavirus; “nowcasting†; epidemia; epidemiología; mortalidad; SAS-CoV-2; enfermedades transmisibles;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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