Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

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.
  Article Metrics

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


  • 1. T. E. Carpenter, J. M. O'Brien, A. D. Hagerman, B. A. McCarl, Epidemic and economic impacts of delayed detection of foot-and-mouth disease: a case study of a simulated outbreak in California, J. Vet. Diagn. Invest., 23 (2011), 26-33.
  • 2. P. W. Uys, R. Warren, P. D. van Helden, M. Murray, T. C. Victor, Potential of rapid diagnosis for controlling drug-susceptible and drug-resistant tuberculosis in communities where Mycobacterium tuberculosis infections are highly prevalent, J. Clin. Mircrobiol., 47 (2009), 1484-1490.
  • 3. D. S. Hui, E. I. Azhar, T. A. Madani, F. Ntoumi, R. Kock, O. Dar, et al., The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health-The latest 2019 novel coronavirus outbreak in Wuhan, China, Int. J. Infect. Dis., 91 (2020), 264-266.
  • 4. C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, et al., Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China, Lancet, 395 (2020), 497-506.
  • 5. Q. Li, X. Guan, P. Wu, X. Wang, L. Zhou, Y. Tong, et al., Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia, N. Engl. J. Med., 382 (2020), 1199-1207.
  • 6. WHO Coronavirus Disease (COVID-19) Dashboard, Map Data, 2020. Available from: https://covid19.who.int/.
  • 7. Worldometer, 2020. Available from: https://www.worldometers.info/.
  • 8. M. A. Islam, R. I. Chowdhury, A Bivariate Poisson Models with Covariate Dependence, Bulletin of Calcutta Mathematical Society, 107 (2015), 11-20.
  • 9. M. A. Islam, R. I. Chowdhury, Analysis of Repeated Measures Data, Springer, Singapore, 2017.
  • 10. bpglm: R package for Bivariate Poisson GLM with Covariates, 2019. Available from: https://www.researchgate.net/publication/333486456_bpglm_R_package_for_Bivariate_Poisson_GLM_with_Covariates.


Reader Comments

your name: *   your email: *  

© 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved