Studying on the impact of media coverage on the spread of COVID-19 in Hubei Province, China

Math Biosci Eng. 2020 Apr 17;17(4):3147-3159. doi: 10.3934/mbe.2020178.

Abstract

Awareness of prevention is enhanced to reduce the rate of infection by media coverage, which plays an important role in preventing and controlling infectious diseases. Based on epidemic situation of the Corona Virus Disease 2019 (COVID-19) in Hubei, an SIHRS epidemic model with media coverage was proposed. Firstly, by the basic reproduction number R0, the globally asymptotically stable of the disease-free equilibrium and the endemic equilibrium were proved. Then, based on the reported epidemic data of Hubei Province from January 26 to February 13, numerical simulations are used to verify the analysis results, and the impact of peak time and the scale of disease transmission were mainly considered with different information implementation rate and the contact rate. It was shown that with the decrease of information implementation rate, the peak of confirmed cases would be delayed to reach, and would increase significantly. Therefore, in order to do a better prevention measures after resumption of work, it is very necessary to maintain the amount of information and implementation rate of media coverage.

Keywords: COVID-19; SIHRS model; basic reproduction number; media coverage; stability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Basic Reproduction Number / statistics & numerical data
  • Betacoronavirus*
  • COVID-19
  • China / epidemiology
  • Communications Media*
  • Computer Simulation
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / prevention & control
  • Coronavirus Infections / transmission
  • Epidemics / prevention & control
  • Epidemics / statistics & numerical data
  • Humans
  • Mathematical Concepts
  • Models, Biological
  • Pandemics* / prevention & control
  • Pandemics* / statistics & numerical data
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / prevention & control
  • Pneumonia, Viral / transmission
  • Quarantine / statistics & numerical data
  • SARS-CoV-2
  • Social Media