Analyzing the effect of duration on the daily new cases of COVID-19 infections and deaths using bivariate Poisson regression: a marginal conditional approach

Rafiqul Chowdhury; Gary Sneddon; M Tariqul Hasan

doi:10.3934/mbe.2020323

Analyzing the effect of duration on the daily new cases of COVID-19 infections and deaths using bivariate Poisson regression: a marginal conditional approach

Math Biosci Eng. 2020 Sep 14;17(5):6085-6097. doi: 10.3934/mbe.2020323.

Authors

Rafiqul Chowdhury¹, Gary Sneddon², M Tariqul Hasan¹

Affiliations

¹ Department of Mathematics and Statistics, University of New Brunswick, Fredericton, NB E3B 5A3, Canada.
² Mathematics Department, Mount Saint Vincent University, Halifax, NS, B3M 2J6, Canada.

PMID: 33120590
DOI: 10.3934/mbe.2020323

Abstract

The whole world is devastated by the impact of the COVID-19 pandemic. The socioeconomic and other effects of COVID-19 on people are visible in all echelons of society. The main goal of countries is to stop the spreading of this pandemic by reducing the COVID-19 related new cases and deaths. In this paper, we analyzed the correlated count outcomes, daily new cases, and fatalities, and assessed the impact of some covariates by adopting a generalized bivariate Poisson model. There are different effects of duration on new cases and deaths in different countries. Also, the regional variation found to be different, and population density has a significant impact on outcomes.

Keywords: Bivariate Poisson; count data; daily death; marginal conditional models; new cases.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
COVID-19
Coronavirus Infections / epidemiology*
Coronavirus Infections / mortality*
Global Health
Humans
Models, Statistical
Pandemics
Pneumonia, Viral / epidemiology*
Pneumonia, Viral / mortality*
Poisson Distribution
Population Density
Probability
Regression Analysis
World Health Organization