Understanding SARSCOV-2 Propagation, Impacting Factors To Derive Possible Scenarios and Simulations

Abstract

We aimed to analyze factors impacting the Covid-19 epidemic on a macro level, comparing multiple countries across the world, and verifying the occurrence at a micro-level through cluster analysis. We used publicly available large world datasets (1-11). Data were transformed to fit parametric distributions prior to statistical analyses, which were performed with Student’s t-test, linear regression, and post hoc tests. Especially for ordinary least squares regression, natural logarithmic transformations were done to remediate normality violations in the standardized residuals. The severity of the epidemic was most strongly related to exposure to ultraviolet light and extrapolated levels of vitamin D and the health of the population, especially with regards to obesity.  We found no county with an obesity level < 8% with a severe epidemic. We also found that countries, where the population benefited from sun exposure or vitamin D supplementation and spent time outside, fared well. Factors related to increased propagation of the virus included the use of heating ventilation and air conditioning (HVAC), population density, poorly aerated gatherings, relative humidity, timely policies of closing clustering places until aeration was improved, and daily amount of ridership on public transportation, especially subways.  Population lockdowns, masks, and blood type did not provide much explanatory power. The excess mortality observed is within the ranges of severe past influenza epidemics of 2016/2017 or 1999/2000. Our study suggested that prevention measures should be directed to improving aeration systems, enhancing diets and exercise, and ensuring adequate levels of vitamin D. Further research on masking is indicated as our study could not separate policies from how well they were followed.