Impact of climate change on SARS-CoV-2 epidemic in China

Temperature was the most direct characterization indicator for each weather factor, and in Hubei, where the outbreak was the most severe. For example, temperatures from January 20, 2020 to April 30, 2020 indicated that Hubei province (particularly Wuhan city) was in the late winter and early spring season, with an average daily temperature range of 1˚C to 18˚C. In February, the average temperature in Wuhan City was within the optimal range for coronavi- rus transmission [17, 18]. Low temperatures and significant diurnal temperature differences resulted in a decrease in human immunity and ease of viral infection, thus facilitating the out- break of SARS-CoV-2. When atmospheric temperature variation was not considered, the SP decreased exponen- tially as the terrain increased, i.e., the SP was lower in higher-altitude regions. The SP increased gradually as the geographical latitude increased. The annual variation pattern of continental atmospheric pressure showed a higher SP in the winter than in the summer [47]. If only the effect of SP is considered, then highland regions such as Yunnan, Guizhou, and Tibet will indi- cate higher altitudes and lower SPs. Regions such as Guangdong, Shandong, Jiangsu, and Wuhan in Hubei had lower altitudes and higher SPs. Meanwhile, Heilongjiang was located in the northernmost region of China and belonged to the region with the highest latitude and higher SPs. The study was performed in the winter and early spring. The SP in the winter showed an overall decreasing trend and was lower than that in summer. Thus, it can be con-

cluded that fewer people had SARS-CoV-2 when the SP was low. More confirmed SARS-CoV- 2 cases were indicated when the SP was high. Therefore, a lower SP decreases the GR, which is contrary to the findings of Correa-Araneda et al. [19]. Many studies have shown that WS inhibits epidemics and infectious diseases such as SARS-CoV-2 [10]. Increasing the WS promotes indoor air circulation; however, wind can serve as a carrier of infectious disease pathogens. Therefore, wind direction and WS affect the spread and distribution of certain contagious diseases. The results showed that WS was nega- tively correlated with the GR and that the wind speed imposed an inhibitory effect on the GR. In summary, the effect of weather on SARS-CoV-2 was demonstrated using spatio–tempo- ral analysis. In addition, the effects of six weather factors (H, WS, SP, T, UV, and TP) on SARS-CoV-2 was quantified using statistical analysis to contribute to the prevention and con- trol of the SARS-CoV-2 epidemic. Conclusion The Chinese region was selected as the study area owing to its intense outbreaks and improved prevention and control. ECMWF reanalysis data were used for weather factors, and mathe- matical, statistical, and spatial analysis methods were used to analyze the temporal and spatial effects of the weather factors on the SARS-CoV-2 epidemic. Using the environmental and weather characteristics of infectious disease outbreaks for reference, the effects of six weather factors on the epidemic were discussed to facilitate the future prevention, control, interrup-

tion, and prediction of the epidemic. The main findings of this study are as follows: 1. In terms of spatial and temporal characteristics, the average GR of all administrative regions in China showed a logarithmic distribution with a significant downward trend (P-value < 0.05). The average GR was 5.15%, and 84,385 confirmed cases were recorded as of April 31, with an average of 833 new confirmed cases per day. The ratio of confirmed cases to the population showed a characteristic consistent with the spatial distribution of the Hu Line. 2. In the correlation analysis, UV was significantly and negatively correlated with GR, TP, and SP, with UV having the highest correlation with T (RT = 0.87), followed by SP (RSP = -0.55) and GR (RGR = -0.53). The GR was significantly and positively correlated with SP (RSP = PLOS ONE Impact of climate change on SARS-CoV-2 epidemic in China PLOS ONE | https://doi.org/10.1371/journal.pone.0285179 July 27, 2023 17 / 21