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Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy
Ibn Tofail University, Morocco.
Ibn Tofail University, Morocco.ORCID iD: 0000-0001-5157-5267
University of Sydney, Australia.
Linnaeus University, Faculty of Technology, Department of Mathematics. Region Kronoberg, Sweden.ORCID iD: 0000-0002-7790-0539
2021 (English)In: Mathematical Population Studies, ISSN 0889-8480, Vol. 28, no 4, p. 228-242Article in journal (Refereed) Published
Abstract [en]

In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes' theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2021. Vol. 28, no 4, p. 228-242
Keywords [en]
Basic reproduction number, Bayes' theorem, COVID-19, epidemic model, stochastic diffusion
National Category
Probability Theory and Statistics Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Mathematics, Applied Mathematics
Identifiers
URN: urn:nbn:se:lnu:diva-106004DOI: 10.1080/08898480.2021.1941661ISI: 000671478800001Scopus ID: 2-s2.0-85110343670Local ID: 2021OAI: oai:DiVA.org:lnu-106004DiVA, id: diva2:1581593
Available from: 2021-07-22 Created: 2021-07-22 Last updated: 2022-05-24Bibliographically approved

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Pettersson, Roger

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