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

Abstract

Objective: many potential factors contribute to the outbreak of COVID-19. The aim of this study was to explore the effects of various meteorological factors on the incidence of COVID-19. Methods:Taking Hubei province of China as an example, where COVID-19 was first reported and there were the most cases, we collected 53 days of cases up to March 10(total 67773 confirmed cases).COVID-19 confirmed cases were retrieved from the official website of Hubei Health Commission. Ten meteorological parameters were provided by China meteorological administration, including average pressure (hPa), average temperature ( ), maximum temperature, minimum temperature ( ), average water vapor pressure (hPa), average relative humidity (%),etc.Cross correlation analysis and linear regression were used to judge the relationship of . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) : medRxiv preprint meteorological factors and increment of COVID-19 confirmed cases. Results:Under 95% CI, the increment of confirmed cases in Hubei were significantly correlated with four meteorological parameters of average pressure, average temperature, minimum temperature and average water vapor pressure (equivalent to absolute humidity).The average pressure was positively correlated with the increment ( r=+0.358,p=0.010).The negative correlations included average temperature (r=-0.306,p=0.029), minimum air temperature (r=-0.347,p=0.013), average water vapor pressure (r=-0.326,p=0.020). The linear regression results show if minimum temperature increases by 1 , the incremental confirmed cases in Hubei decreases by 72.470 units on average. Conclusion:The incidence of COVID-19 was significantly correlated with average pressure, average temperature, minimum temperature and average water vapor pressure. It is positively correlated with the average pressure and negatively correlated with the other three parameters. Compared with relative humidity, 2019-nCov is more sensitive to water vapor pressure. The reason why the epidemic situation in Hubei expanded rapidly is significantly related to the climate characteristics of low temperature and dryness of Hubei in winter.

Atmospheric pressure and population density as super-factors influencing the transmission of coronavirus disease 2019 (COVID-19)

“…This study showed that higher AAP led to the rapid spread of COVID-19 during the early stage of the pandemic. Our results are consistent with a previous study conducted in Hubei Province of China, which demonstrated that the incidence of COVID-19 was positively correlated with AAP 15 ; however, our results are in contrast with other studies conducted in Japan 16 and China 17 . Use of a larger dataset than in those previous studies and systematic approaches may lead to more robust conclusions.…”

“…The underlying mechanism behind the relationship of AAP with the transmission of COVID-19 is unclear. One explanation might be that increased AAP may lead to an increase in the number of viruses per unit area when the human body expels respiratory viruses 15 . A positive correlation was observed between COVID-19 transmission and PD, consistent with previous study 20 , which also strengthens the notion that lockdown policies can help to atten the epidemic curve 21 .…”

Is coronavirus disease (COVID-19) seasonal? A critical analysis of empirical and epidemiological studies at global and local scales

“…Another analysis of data from 16 Chinese provinces concluded that RH and SARS-CoV-2 transmission rates have no significant spatial correlation (R = -0.17, p = 0.48) ( Lin et al, 2020a ). Similarly, multiple other studies did not find a significant association between RH and SARS-CoV-2 transmission in China ( Li et al, 2020b ; Metelmann et al, 2020 ; Rahman et al, 2020 ; Yao et al, 2020b ).…”

“…Out of those 14 provinces, 12 showed a negative correlation between daily temperature and the number of infected cases ( Rahman et al, 2020 ). A group of studies reported that with regression and correlation analysis, increment in temperature resulted in a decrease in the daily number of confirmed cases ( Li et al, 2020a ; Li et al, 2020b ; Liu et al, 2020b ; Luo et al, 2020 ; Rouen et al, 2020 ; Oliveiros et al, 2020 ; Qi et al, 2020 ; Xie and Zhu, 2020 ). Several other studies analyzed variables from the Susceptible-Exposed-Infectious-Recovered (SEIR) model with regression analysis and showed that the transmission rate was negatively related to temperature ( Guo et al, 2020 ; Lin et al, 2020b ).…”

Super Environmental Adaptability of SARS CoV2

“…The growth rate of COVID-19 cases peaked at a temperature of ~5°C and a humidity of 0.6 to 1 kPa in the temperate regions of the Northern Hemisphere during the outbreak month, while it decreased in regions that had warmer or colder temperatures 9 . Likewise, average pressure, average temperature, minimum temperature, and average water vapor pressure were found to be significantly correlated with the incidence of COVID-19 10,11 . Generally, the largest contiguous syndromes outbreak in the regions of cooler weather, leading to the theories that high temperatures might begin to the tail of in the summer season 1 .…”