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Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics

Tang, Biao ; Zhou, Weike ; Wang, Xia ; Wu, Hulin ; Xiao, Yanni

Bulletin of mathematical biology, 2022-10, Vol.84 (10), p.106-106, Article 106 [Periódico revisado por pares]

New York: Springer US

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Título:
Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics
Autor: Tang, Biao ; Zhou, Weike ; Wang, Xia ; Wu, Hulin ; Xiao, Yanni
Assuntos: Behavior ; Cell Biology ; Control theory ; Coronaviruses ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - prevention & control ; COVID-19 vaccines ; Disease control ; Disease transmission ; Dynamics ; Epidemics ; Epidemics - prevention & control ; Feedback loops ; Game Theory ; Humans ; Immunization ; Life Sciences ; Mathematical and Computational Biology ; Mathematical Concepts ; Mathematics ; Mathematics and COVID-19 ; Mathematics and Statistics ; Models, Biological ; Scale models ; Special Issue: Mathematics and Covid-19 ; Vaccination ; Viral diseases
É parte de: Bulletin of mathematical biology, 2022-10, Vol.84 (10), p.106-106, Article 106
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SourceType-Scholarly Journals-1
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Descrição: COVID-19 epidemics exhibited multiple waves regionally and globally since 2020. It is important to understand the insight and underlying mechanisms of the multiple waves of COVID-19 epidemics in order to design more efficient non-pharmaceutical interventions (NPIs) and vaccination strategies to prevent future waves. We propose a multi-scale model by linking the behaviour change dynamics to the disease transmission dynamics to investigate the effect of behaviour dynamics on COVID-19 epidemics using game theory. The proposed multi-scale models are calibrated and key parameters related to disease transmission dynamics and behavioural dynamics with/without vaccination are estimated based on COVID-19 epidemic data (daily reported cases and cumulative deaths) and vaccination data. Our modeling results demonstrate that the feedback loop between behaviour changes and COVID-19 transmission dynamics plays an essential role in inducing multiple epidemic waves. We find that the long period of high-prevalence or persistent deterioration of COVID-19 epidemics could drive almost all of the population to change their behaviours and maintain the altered behaviours. However, the effect of behaviour changes fades out gradually along the progress of epidemics. This suggests that it is essential to have not only persistent, but also effective behaviour changes in order to avoid subsequent epidemic waves. In addition, our model also suggests the importance to maintain the effective altered behaviours during the initial stage of vaccination, and to counteract relaxation of NPIs, it requires quick and massive vaccination to avoid future epidemic waves.
Editor: New York: Springer US
Idioma: Inglês

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Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics

Tang, Biao ; Zhou, Weike ; Wang, Xia ; Wu, Hulin ; Xiao, Yanni

New York: Springer US

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