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A comprehensive analysis of COVID-19 transmission and mortality rates at the county level in the United States considering socio-demographics, health indicators, mobility trends and health care infrastructure attributes

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  • Tanmoy Bhowmik
  • Sudipta Dey Tirtha
  • Naveen Chandra Iraganaboina
  • Naveen Eluru

Abstract

Background: Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that can contribute to the COVID-19 transmission/mortality rate. The current study effort is designed to remedy this by analyzing COVID-19 transmission/mortality rates considering a comprehensive set of factors in a unified framework. Methods and findings: We study two per capita dependent variables: (1) daily COVID-19 transmission rates and (2) total COVID-19 mortality rates. The first variable is modeled using a linear mixed model while the later dimension is analyzed using a linear regression approach. The model results are augmented with a sensitivity analysis to predict the impact of mobility restrictions at a county level. Several county level factors including proportion of African-Americans, income inequality, health indicators associated with Asthma, Cancer, HIV and heart disease, percentage of stay at home individuals, testing infrastructure and Intensive Care Unit capacity impact transmission and/or mortality rates. From the policy analysis, we find that enforcing a stay at home order that can ensure a 50% stay at home rate can result in a potential reduction of about 33% in daily cases. Conclusions: The model framework developed can be employed by government agencies to evaluate the influence of reduced mobility on transmission rates at a county level while accommodating for various county specific factors. Based on our policy analysis, the study findings support a county level stay at home order for regions currently experiencing a surge in transmission. The model framework can also be employed to identify vulnerable counties that need to be prioritized based on health indicators for current support and/or preferential vaccination plans (when available).

Suggested Citation

  • Tanmoy Bhowmik & Sudipta Dey Tirtha & Naveen Chandra Iraganaboina & Naveen Eluru, 2021. "A comprehensive analysis of COVID-19 transmission and mortality rates at the county level in the United States considering socio-demographics, health indicators, mobility trends and health care infras," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    • Handle: RePEc:plo:pone00:0249133
    DOI: 10.1371/journal.pone.0249133
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    References listed on IDEAS

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    Cited by:

    1. Dina Albassam & Mariam Nouh & Anette Hosoi, 2023. "The Effectiveness of Mobility Restrictions on Controlling the Spread of COVID-19 in a Resistant Population," IJERPH, MDPI, vol. 20(7), pages 1-14, March.
    2. Stephanie Griggs & Christine Horvat Davey & Quiana Howard & Grant Pignatiello & Deepesh Duwadi, 2022. "Socioeconomic Deprivation, Sleep Duration, and Mental Health during the First Year of the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(21), pages 1-10, November.
    3. Costase Ndayishimiye & Christoph Sowada & Patrycja Dyjach & Agnieszka Stasiak & John Middleton & Henrique Lopes & Katarzyna Dubas-Jakóbczyk, 2022. "Associations between the COVID-19 Pandemic and Hospital Infrastructure Adaptation and Planning—A Scoping Review," IJERPH, MDPI, vol. 19(13), pages 1-22, July.
    4. Dey Tirtha, Sudipta & Bhowmik, Tanmoy & Eluru, Naveen, 2022. "An airport level framework for examining the impact of COVID-19 on airline demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 169-181.

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