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Transmission Dynamics, Heterogeneity and Controllability of SARS-CoV-2: A Rural–Urban Comparison

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  • Yuying Li

    (Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China)

  • Taojun Hu

    (Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China)

  • Xin Gai

    (Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China)

  • Yunjun Zhang

    (Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China)

  • Xiaohua Zhou

    (Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China
    Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China
    Center for Statistical Sciences, Peking University, Beijing 100871, China)

Abstract

Few studies have examined the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in rural areas and clarified rural–urban differences. Moreover, the effectiveness of non-pharmaceutical interventions (NPIs) relative to vaccination in rural areas is uncertain. We addressed this knowledge gap through using an improved statistical stochastic method based on the Galton–Watson branching process, considering both symptomatic and asymptomatic cases. Data included 1136 SARS-2-CoV infections of the rural outbreak in Hebei, China, and 135 infections of the urban outbreak in Tianjin, China. We reconstructed SARS-CoV-2 transmission chains and analyzed the effectiveness of vaccination and NPIs by simulation studies. The transmission of SARS-CoV-2 showed strong heterogeneity in urban and rural areas, with the dispersion parameters k = 0.14 and 0.35, respectively ( k < 1 indicating strong heterogeneity). Although age group and contact-type distributions significantly differed between urban and rural areas, the average reproductive number ( R ) and k did not. Further, simulation results based on pre-control parameters ( R = 0.81, k = 0.27) showed that in the vaccination scenario (80% efficacy and 55% coverage), the cumulative secondary infections will be reduced by more than half; however, NPIs are more effective than vaccinating 65% of the population. These findings could inform government policies regarding vaccination and NPIs in rural and urban areas.

Suggested Citation

  • Yuying Li & Taojun Hu & Xin Gai & Yunjun Zhang & Xiaohua Zhou, 2021. "Transmission Dynamics, Heterogeneity and Controllability of SARS-CoV-2: A Rural–Urban Comparison," IJERPH, MDPI, vol. 18(10), pages 1-10, May.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5221-:d:554508
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    References listed on IDEAS

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    1. J. O. Lloyd-Smith & S. J. Schreiber & P. E. Kopp & W. M. Getz, 2005. "Superspreading and the effect of individual variation on disease emergence," Nature, Nature, vol. 438(7066), pages 355-359, November.
    2. Seth Blumberg & James O Lloyd-Smith, 2013. "Inference of R0 and Transmission Heterogeneity from the Size Distribution of Stuttering Chains," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-17, May.
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