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The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R 0 is successfully managed below one.
Engen, Steinar; Tian, Huaiyu; Yang, Ruifu; Bjørnstad, Ottar N; Whittington, Jason D; Stenseth, Nils Chr.
  • Engen S; Centre for Biodiversity Dynamics (CBD), Department of Mathematical Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway.
  • Tian H; State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, People's Republic of China.
  • Yang R; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, People's Republic of China.
  • Bjørnstad ON; Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802, USA.
  • Whittington JD; Center for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences and Faculty of Mathematics and Natural Sciences, University of Oslo, PO Box 1032 Blindern, 316 Oslo, Norway.
  • Stenseth NC; Center for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences and Faculty of Mathematics and Natural Sciences, University of Oslo, PO Box 1032 Blindern, 316 Oslo, Norway.
R Soc Open Sci ; 8(6): 202234, 2021 Jun 09.
Article in English | MEDLINE | ID: covidwho-1266245
ABSTRACT
Since COVID-19 spread globally in early 2020 and was declared a pandemic by the World Health Organization (WHO) in March, many countries are managing the local epidemics effectively through intervention measures that limit transmission. The challenges of immigration of new infections into regions and asymptomatic infections remain. Standard deterministic compartmental models are inappropriate for sub- or peri-critical epidemics (reproductive number close to or less than one), so individual-based models are often used by simulating transmission from an infected person to others. However, to be realistic, these models require a large number of parameters, each with its own set of uncertainties and lack of analytic tractability. Here, we apply stochastic age-structured Leslie theory with a long history in ecological research to provide some new insights to epidemic dynamics fuelled by external imports. We model the dynamics of an epidemic when R 0 is below one, representing COVID-19 transmission following the successful application of intervention measures, and the transmission dynamics expected when infections migrate into a region. The model framework allows more rapid prediction of the shape and size of an epidemic to improve scaling of the response. During an epidemic when the numbers of infected individuals are rapidly changing, this will help clarify the situation of the pandemic and guide faster and more effective intervention.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: R Soc Open Sci Year: 2021 Document Type: Article Affiliation country: Rsos.202234

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: R Soc Open Sci Year: 2021 Document Type: Article Affiliation country: Rsos.202234