Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19

Background: The coronavirus disease 2019 (COVID-19) pandemic is a worldwide epidemiological emergency, and the risk factors for the multiple waves with new COVID-19 strains are concerning. This study aims to identify the most significant risk factors for spreading COVID-19 to help policymakers take early measures for the next waves. Methods: We conducted the study on randomly selected 29 countries where the pandemic had a downward trend in the daily active cases curve as of June 10, 2020. We investigated the association with the standardized spreading index and demographical, environmental, socioeconomic, and government intervention. To standardize the spreading index, we accounted for the number of tests and the timeline bias. Furthermore, we performed multiple linear regression to identify the relative importance of the variables. Results: In the correlation analysis, air pollution, PM2.5 (r = 0.37, p = 0.0466), number of days to impose lockdown from first case (r = 0.38, p = 0.0424) and total confirmed cases on the first lockdown (r = 0.61, p = 0.0004) were associated with outcome measures. In the adjusted model, air pollution (β1 = 4.5, p = 0.0127, |t| = 3.1) and overweight prevalence (β1 = 4.7, p = 0.0187, |t| = 2.9) were the most significant exposure variable for spreading of COVID-19. Conclusion: Our findings showed that countries with larger PM2.5 values and comparatively more overweight populations are at higher risk of spreading COVID-19. Proper preventive measures may reduce the spreading