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COVID-19 spreading under containment actions

Author

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  • Cornes, F.E.
  • Frank, G.A.
  • Dorso, C.O.

Abstract

We propose an epidemiological model that explores the effect of human mobility on the spatio-temporal dynamics of the COVID-19 outbreak, in the spirit to those considered in Refs. Barmak et al. (2011, 2016) and Medus and Dorso (2011) [1]. We assume that people move around in a city of 120 × 120 blocks with 300 inhabitants in each block. The mobility pattern is associated to a complex network in which nodes represent blocks while the links represent the traveling path of the individuals (see below). We implemented three confinement strategies in order to mitigate the disease spreading: (1) global confinement, (2) partial restriction to mobility, and (3) localized confinement. In the first case, it was observed that a global isolation policy prevents the massive outbreak of the disease. In the second case, a partial restriction to mobility could lead to a massive contagion if this was not complemented with sanitary measures such as the use of masks and social distancing. Finally, a local isolation policy was proposed, conditioned to the health status of each block. It was observed that this mitigation strategy was able to contain and even reduce the outbreak of the disease by intervening in specific regions of the city according to their level of contagion. It was also observed that this strategy is capable of controlling the epidemic in the case that a certain proportion of those infected are asymptomatic.

Suggested Citation

  • Cornes, F.E. & Frank, G.A. & Dorso, C.O., 2022. "COVID-19 spreading under containment actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
  • Handle: RePEc:eee:phsmap:v:588:y:2022:i:c:s0378437121008396
    DOI: 10.1016/j.physa.2021.126566
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    References listed on IDEAS

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    1. Seth Flaxman & Swapnil Mishra & Axel Gandy & H. Juliette T. Unwin & Thomas A. Mellan & Helen Coupland & Charles Whittaker & Harrison Zhu & Tresnia Berah & Jeffrey W. Eaton & Mélodie Monod & Azra C. Gh, 2020. "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe," Nature, Nature, vol. 584(7820), pages 257-261, August.
    2. Barmak, D.H. & Dorso, C.O. & Otero, M., 2016. "Modelling dengue epidemic spreading with human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 129-140.
    3. Neil M. Ferguson & Derek A.T. Cummings & Simon Cauchemez & Christophe Fraser & Steven Riley & Aronrag Meeyai & Sopon Iamsirithaworn & Donald S. Burke, 2005. "Strategies for containing an emerging influenza pandemic in Southeast Asia," Nature, Nature, vol. 437(7056), pages 209-214, September.
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    Cited by:

    1. Rozan, E.A. & Bouzat, S. & Kuperman, M.N., 2023. "Testing lockdown measures in epidemic outbreaks through mean-field models considering the social structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    2. Panicker, Akhil & Sasidevan, V., 2024. "Social adaptive behavior and oscillatory prevalence in an epidemic model on evolving random geometric graphs," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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