Impact of altitude on COVID-19 aggregation infection in China: evidence from linkage of environmental factors, COVID-19, and genome diversity (Preprint)

BACKGROUND The novel coronavirus disease due to SARS-Cov-2 (COVID-19) has been declared as a global pandemic and is still ongoing worldwide. While based on the government report and genome diversity study, the overall COVID-19 mortality and infection cases are significantly low in high altitude place. Several factors which may effect the development tendency of COVID-19 were investigated. However, there is limited information on the evidence of low infection cases in altitude area, and how underlying biological mechanism effect the aggregation infection of COVID-19 in altitude area of China. OBJECTIVE This study is aiming to investigate the impacts of altitude on COVID-19 aggregation infection in China by analyzing the correlation between environmental factors with COVID-19 confirmed cases and viral mutations. METHODS We first examined the correlation between altitude and COVID-19 infection through linear regression, and further identified several major factors correlated to COVID-19 through text mining in the zero-shot model. Spearman correlation was conducted to analyze the correlation between selected meteorological factors and air quality with COVID-19 confirmed cases in high altitude regions of China. We further identified different virus mutations at both high and low altitudes, and the relationship between our environmental factors and mutation frequency using the same correlation technique. RESULTS The linear regression analysis revealed a negative correlation between altitude and COVID-19 confirmed case in China. The Spearman correlation analysis indicated that the average temperature, sun hours, UV index, wind speed and average concentration of NO2 were negatively correlated to daily new confirmed cases at high altitude regions in China, while air pressure, average concentration of PM2.5 were positively correlated. Further research of mutation diversity in low- and high-altitude groups showed lower genetic diversity among nucleotides for each SARS-CoV-2 genome (p < .001) and three open reading frames (ORFs) (p < .001) compared to 300 sequences of low altitude. Further correlation analysis investigated positive correlations between altitude, wind speed, atmospheric pressure with some key nonsynonymous mutations, and negative correlation with temperature, UV index, sun hours. CONCLUSIONS The characteristics of environmental factors including meteorology and air quality parameters largely reflect the evidence of low COVID-19 confirmed cases in high altitude region of China. Besides, environmental factors on virus mutation also adds knowledge of altitude impact on aggregation infection of COVID-19 and provides novel suggestions for preventive intervention.