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COVID-19 and underlying health conditions: A modeling investigation

Chayu Yang1, Jin Wang2

  • 1Department of Mathematics, University of Florida, Gainesville, FL 32607, USA.

Mathematical Biosciences and Engineering : MBE
|July 2, 2021
PubMed

Insights

COVID-19 transmission is higher for individuals with chronic health conditions. Mathematical modeling in Hamilton County, Tennessee, shows reducing transmission between groups protects vulnerable populations.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Public Health

Background:

  • COVID-19 disproportionately affects individuals with chronic health conditions.
  • Understanding transmission dynamics within and between population groups is crucial for effective control strategies.

Purpose of the Study:

  • To develop and apply a mathematical model investigating COVID-19 transmission dynamics in populations with underlying chronic health conditions.
  • To assess the specific risks faced by individuals with chronic conditions.

Main Methods:

  • A system of differential equations was formulated to model disease transmission.
  • The model stratified the population into two groups: those with and without underlying conditions.
  • A case study was conducted in Hamilton County, Tennessee, to apply and validate the model.

Main Results:

  • The model quantified a significantly higher risk of COVID-19 for the population group with underlying health conditions.
  • Data fitting and simulations confirmed the increased vulnerability of this group.
  • Analysis highlighted the importance of transmission routes between population groups.

Conclusions:

  • Targeted interventions to reduce transmission, particularly between susceptible and exposed individuals and between different population groups, are essential.
  • Protecting vulnerable populations with chronic conditions requires focused strategies to mitigate disease spread.

Keywords:
COVID-19 transmissionchronic conditionsdata fitting

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