Skip to main content
Dryad

Global-scale modeling of early factors and country-specific trajectories of COVID-19 incidence: a cross-sectional study of the first 6 months of the pandemic

Data files

Nov 29, 2022 version files 1.19 MB

Abstract

Studies examining factors responsible for COVID-19 incidence are mostly focused at the national or sub-national level. A global-level characterization of contributing factors and temporal trajectories of disease incidence is lacking. Here we conducted a global-scale analysis of COVID-19 infections to identify key factors associated with early disease incidence. Additionally, we compared longitudinal trends of COVID-19 incidence at a per-country level and classified countries based on COVID-19 incidence trajectories and effects of lockdown responses. Univariate analysis identified eleven variables as independently associated with COVID-19 infections at a global level (p<1e-05). Multivariable analysis identified a 4-variable model as optimal for explaining global variations in COVID-19 (p<0.01). COVID-19 case trajectories for most countries were best captured by a log-logistic model, as determined by AIC estimates. Six predominant country clusters were identified when characterizing the effects of lockdown intervals on variations in COVID-19 new cases per country. Globally, economic and meteorological factors are important determinants of early COVID-19 incidence. Analysis of longitudinal trends and lockdown effects on COVID-19 highlights important nuances in country-specific responses to infections. These results provide valuable insights into disease incidence at a per-country level, possibly allowing for more informed decision making by individual governments in future disease outbreaks.