Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors

Pablo Duarte, Efrain Riveros-Perez

Research output: Contribution to journalArticlepeer-review

Abstract

The incidence curve of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. We examine the cyclical properties of the incidence curves in various countries and use principal components analysis to shed light on the underlying dynamics that are common to all countries. We find that the cyclical series of 37 countries can be summarized in four principal components which explain over 90% of the variation. We also discuss the influence of complex interactions between biological viral natural history and socio-political reactions and measures adopted by different countries on the cyclical patterns exhibited by COVID-19 around the globe.

Original languageEnglish (US)
Article number102437
JournalAnnals of Medicine and Surgery
Volume66
DOIs
StatePublished - Jun 2021
Externally publishedYes

Keywords

  • COVID-19
  • Epidemiological data
  • Predictive model
  • Principal component analysis
  • Viral spread

ASJC Scopus subject areas

  • Surgery

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