Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors. (June 2021)

• Record Type: Journal Article
• Authors: Duarte, Pablo; Riveros-Perez, Efrain
• Is Part Of: Annals of medicine and surgery. Volume 66(2021)
• Publication Date: 2021-06
• Subjects: COVID-19 -- Principal component analysis -- Predictive model -- Epidemiological data -- Viral spread; Surgery -- Periodicals; Medicine -- Periodicals; General Surgery -- Periodicals; Education, Medical -- Periodicals; Periodicals; 617
• DOI: 10.1016/j.amsu.2021.102437
• Languages: English
• ISSNs: 2049-0801

Abstract

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. Highlights: Incidence of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. Four components determine 90% of variability in COVID-19 incidence curves. Biological and socio-political factors determine the cyclical patterns of the disease.