Dynamical Variations of the Global COVID‐19 Pandemic Based on a SEICR Disease Model: A New Approach of Yi Hua Jie Mu

Xia Wang, Gang Yin, Zengyun Hu*, Daihai He, Qianqian Cui, Xiaomei Feng, Zhidong Teng, Qi Hu, Jiansen Li, Qiming Zhou

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)

Abstract

The ongoing coronavirus disease 2019 (COVID-19) pandemic has caused more than 150 million cases of infection to date and poses a serious threat to global public health. In this study, global COVID-19 data were used to examine the dynamical variations from the perspectives of immunity and contact of 84 countries across the five climate regions: tropical, arid, temperate, and cold. A new approach named Yi Hua Jie Mu is proposed to obtain the transmission rates based on the COVID-19 data between the countries with the same climate region over the Northern Hemisphere and Southern Hemisphere. Our results suggest that the COVID-19 pandemic will persist over a long period of time or enter into regular circulation in multiple periods of 1–2 years. Moreover, based on the simulated results by the COVID-19 data, it is found that the temperate and cold climate regions have higher infection rates than the tropical and arid climate regions, which indicates that climate may modulate the transmission of COVID-19. The role of the climate on the COVID-19 variations should be concluded with more data and more cautions. The non-pharmaceutical interventions still play the key role in controlling and prevention this global pandemic.
Original languageEnglish
Article numbere2021GH000455
Number of pages20
JournalGeoHealth
Volume5
Issue number8
DOIs
Publication statusPublished - 2 Aug 2021

Scopus Subject Areas

  • Global and Planetary Change
  • Epidemiology
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution
  • Public Health, Environmental and Occupational Health
  • Management, Monitoring, Policy and Law
  • Health, Toxicology and Mutagenesis

User-Defined Keywords

  • COVID-19 pandemic
  • Koppen-Geiger climate classification
  • periodic variation
  • scenario analysis

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