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Dynamics of Inter-community Spread of Covid-19

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Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact

Part of the book series: Infosys Science Foundation Series ((ISFM))

Abstract

We developed a model for the spread of Covid-19 within a community, we paid attention to the sensitivity of the derived basic reproduction number to each model parameter. This model was extended to investigate the impact of migration between two communities on the spread of the disease. Three special cases: unidirectional migration, unrestricted bidirectional migration, and partial bidirectional migration, were considered. Covid-19 data for two Nigerian states, namely Lagos (high burden community) and Ogun (low burden community) were obtained from the website of the Nigeria Centre for Disease Control for parameter estimation and simulation. Our results show that the basic reproduction number of the original model is most sensitive to the recovery rate of symptomatic infectious individuals. From the inter-community spread model, we find that the rate of coupling plays a vital role in the control of the pandemic. Our results project the different possible scenarios based on different lockdown and infection rates in two different communities.

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Authors and Affiliations

  1. Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Tohoku University, Sendai, Japan

    Emmanuel J. Dansu

  2. Department of Mathematical Sciences, Federal University of Technology, Akure, Ondo State, Nigeria

    Emmanuel J. Dansu

  3. Department of Physics, Federal University of Technology, Akure, Nigeria

    Samuel T. Ogunjo

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  1. Emmanuel J. Dansu
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  2. Samuel T. Ogunjo
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Correspondence to Emmanuel J. Dansu .

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Editors and Affiliations

  1. Anand International College of Engineering, Jaipur, Rajasthan, India

    Praveen Agarwal

  2. Institute of Mathematics, University of Santiago de Compostela, Santiago, Spain

    Juan J. Nieto

  3. Mathematical Sciences, Queen Mary University of London, London, UK

    Michael Ruzhansky

  4. Department of Mathematics, University of Aveiro, Aveiro, Portugal

    Delfim F. M. Torres

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Dansu, E.J., Ogunjo, S.T. (2021). Dynamics of Inter-community Spread of Covid-19. In: Agarwal, P., Nieto, J.J., Ruzhansky, M., Torres, D.F.M. (eds) Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact. Infosys Science Foundation Series(). Springer, Singapore. https://doi.org/10.1007/978-981-16-2450-6_18

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