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

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

Special Issues: Modeling the Biological, Epidemiological, Immunological, Molecular, Virological Aspects of COVID-19

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

Citation: Rafiqul Chowdhury, Gary Sneddon, M. Tariqul Hasan. Analyzing the effect of duration on the daily new cases of COVID-19 infections and deaths using bivariate Poisson regression: a marginal conditional approach. Mathematical Biosciences and Engineering, 2020, 17(5): 6085-6097. doi: 10.3934/mbe.2020323

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