ANALYSIS FACTORS AFFECTING COVID-19 MORTALITY USING COUNT REGRESSION

Authors

DOI:

https://doi.org/10.25077/jmua.13.4.270-286.2024

Keywords:

COVID-19, WHO, Overdispersion, Zero-inflation, Mixed-effects, Death counts,

Abstract

The â€2019 novel coronavirus†known as “ the 2019-nCoV†or simply
“COVID-19†has been declared by the World Health organization (WHO), in first quarter of 2020, as a world pandemic and a public health emergency of international concern. Alas, many details related to the COVID-19 have remained unsolved completely. The success of government strategies in fighting the COVID-19 relays mainly on the results from epidemiological or statistical studies. Statistical models play a major role in providing reliable results based on appropriate analyses. Traditional (one-part) models, mixture models and mixed-effects models for counts are used to investigate effects of the WHO-regions and Cumulated COVID-19 cases on the outcome variable COVID-19 new deaths tolls. Overall result reveals there is a strong association between number of new deaths COVID-19 with predictors including the WHO regions and cumulated cases.
Besides, models that account for the overdispersion feature have smallest AICs and have reasonable regression model fits.

Author Biographies

Niswatul Qona'ah, Sebelas Maret University

Statistics Study Program

T. Martin Walukusa, Feng Chia University

Department of Statistics

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Published

31-10-2024

Issue

Vol. 13 No. 4 (2024)

Section

Articles

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