Meteorological factors correlate with transmission of 2019-nCoV: Proof of incidence of novel coronavirus pneumonia in Hubei Province, China

Jianfeng Li; Linyuan Zhang; Zhihua Ren; Caihong Xing; Peihuan Qiao; Bing Chang

increment was introduced, and finally 4 parameters were found to have strong correlation with case increment. Considering the three-month statistical cycle, the actual valid data is only 53. In the case of limited observations, there can be 4 parameters with obvious correlation. We have every reason to believe that, first, with the increase of effective observations, the statistical correlation between parameters will gradually appear; secondly, case increment is very sensitive to meteorological parameters, and analyzing cases with meteorological parameters is an effective method; thirdly, in addition to the minimum temperature, the other three parameters cannot establish a linear regression equation. Similarly, this study also uses the method of multiple linear regression analysis, but the overall fitting degree is very poor, the ultimate reason, it is not the problem of statistical method itself, but the effective observations for sudden infectious diseases is too little and the law is not obvious. 2019-nCoV evolution to seasonal infectious disease such as influenza virus is possible, if this happens, then periodic and repetitive data can be accumulated; meanwhile, this study finds that meteorological parameters, such as the minimum temperature and the average water vapor pressure, are the specific influencing factors of 2019-nCoV, this will become very meaningful for predicting the 2019-nCoV epidemic trend in the future.