Influence of socio-ecological factors on COVID-19 risk: a cross-sectional study based on 178 countries/regions worldwide

Abstract

The initial outbreak of COVID-19 caused by SARS-CoV-2 in China in 2019 has been severely tested in other countries worldwide. We established the Potential Risk Assessment Framework for COVID-19. We used spatial econometrics method to assess the global and local correlation of COVID-19 risk indicators. To estimate the adjusted IRR, we modelled negative binomial regression analysis with spatial information and socio-ecological factors. We found that 37, 29 and 39 countries/regions were strongly opposite from the IR, CMR and DCI index "spatial autocorrelation hypothesis", respectively. The IR, CMR and DCI were significantly associated with some socio-economic factors. We also found that climatic factors (temperature, relative humidity, precipitation and wind speed) did not significantly reduce COVID-19 risk. To fight against COVID-19 more effectively, countries/regions should pay more attention to controlling population flow, improving diagnosis and treatment capacity, and improving public welfare policies.