Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96535
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Title: Heterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimation
Authors: Wen, C
Wei, J
Ma, ZF
He, M
Zhao, S
Ji, J
He, D 
Issue Date: Jun-2022
Source: Infectious disease modelling, June 2022, v. 7, no. 2, p. 1-24
Abstract: Since March 11th, 2020, COVID-19 has been a global pandemic for more than one years due to a long and infectious incubation period. This paper establishes a heterogeneous epidemic model that divides the incubation period into infectious and non-infectious and employs the Bayesian framework to model the ‘Diamond Princess’ enclosed space incident. The heterogeneity includes two different identities, two transmission methods, two different-size rooms, and six transmission stages. This model is also applicable to similar mixed structures, including closed schools, hospitals, and communities. As the COVID-19 pandemic continues, our mathematical modeling can provide management insights to the governments and policymakers on how the COVID-19 disease has spread and what prevention strategies still need to be taken.
Keywords: COVID-19
Epidemic model
Incubation period
Transmission
Publisher: Elsevier
Journal: Infectious disease modelling 
ISSN: 2468-0427
DOI: 10.1016/j.idm.2022.02.001
Rights: © 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Wen, C., Wei, J., Ma, Z. F., He, M., Zhao, S., Ji, J., & He, D. (2022). Heterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimation. Infectious Disease Modelling, 7(2), 1-24 is available at https://doi.org/10.1016/j.idm.2022.02.001.
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