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A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions

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  • Bouchnita, Anass
  • Jebrane, Aissam

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that emerged in Wuhan, China in December 2019. It has caused a global outbreak which represents a major threat to global health. Public health resorted to non-pharmaceutical interventions such as social distancing and lockdown to slow down the spread of the pandemic. However, the effect of each of these measures remains hard to quantify. We design a multi-scale model that simulates the transmission dynamics of COVID-19. We describe the motion of individual agents using a social force model. Each agent can be either susceptible, infected, quarantined, immunized or deceased. The model considers both mechanisms of direct and indirect transmission. We parameterize the model to reproduce the early dynamics of disease spread in Italy. We show that panic situations increase the risk of infection transmission in crowds despite social distancing measures. Next, we reveal that pre-symptomatic transmission accelerates the onset of the exponential growth of cases. After that, we demonstrate that the persistence of SARS-CoV-2 on hard surfaces determines the number of cases reached during the peak of the epidemic. Then, we show that the restricted movement of the individuals flattens the epidemic curve. Finally, model predictions suggest that measures stricter than social distancing and lockdown were used to control the epidemic in Wuhan, China.

Suggested Citation

  • Bouchnita, Anass & Jebrane, Aissam, 2020. "A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:chsofr:v:138:y:2020:i:c:s0960077920303404
    DOI: 10.1016/j.chaos.2020.109941
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    References listed on IDEAS

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    1. Namilae, S. & Srinivasan, A. & Mubayi, A. & Scotch, M. & Pahle, R., 2017. "Self-propelled pedestrian dynamics model: Application to passenger movement and infection propagation in airplanes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 248-260.
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    Citations

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    Cited by:

    1. Hanthanan Arachchilage, Kalpana & Hussaini, Mohammed Yousuff, 2021. "Ranking non-pharmaceutical interventions against Covid-19 global pandemic using global sensitivity analysis—Effect on number of deaths," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    2. Qiang Wang & Min Su & Min Zhang & Rongrong Li, 2021. "Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare," IJERPH, MDPI, vol. 18(11), pages 1-50, June.
    3. Fabian Lorig & Emil Johansson & Paul Davidsson, 2021. "Agent-Based Social Simulation of the Covid-19 Pandemic: A Systematic Review," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(3), pages 1-5.
    4. Dramane Sam Idris Kanté & Aissam Jebrane & Anass Bouchnita & Abdelilah Hakim, 2023. "Estimating the Risk of Contracting COVID-19 in Different Settings Using a Multiscale Transmission Dynamics Model," Mathematics, MDPI, vol. 11(1), pages 1-19, January.
    5. Wei, Mengke & Han, Xiujing & Bi, Qinsheng, 2022. "Sufficient conditions and criteria for the pulse-shaped explosion related to equilibria in a class of nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    6. Cui, Hongjun & Xie, Jinping & Zhu, Minqing & Tian, Xiaoyong & Wan, Ce, 2022. "Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    7. Luis Vargas Tamayo & Vianney Mbazumutima & Christopher Thron & Léonard Todjihounde, 2021. "Three-Stage Numerical Solution for Optimal Control of COVID-19," Mathematics, MDPI, vol. 9(15), pages 1-26, July.

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