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

  1. Jianfeng Li
  2. Linyuan Zhang
  3. Zhihua Ren
  4. Caihong Xing
  5. Peihuan Qiao
  6. Bing Chang

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Abstract

Objective

many potential factors contribute to the outbreak of COVID-19.It aims 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 confirmed cases (total 67773 cases) and ten meteorological parameters up to March 10. Correlation analysis and linear regression were used to judge the relationship of meteorological factors and increment of COVID-19 confirmed cases.

Results

Under 95% CI, the increment of confirmed cases in Hubei were 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).The negative correlations included average temperature (r=-0.306), minimum temperature (r=-0.347), and average water vapor pressure (r=-0.326). 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

Statistically, the incidence of COVID-19 was 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.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.01.20050526: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study has some limitations. First, we did not distinguish the gender, age, health status and other information of the patients in the case, nor did we consider the host factors that play a role in the spread of the disease, such as immunity, this may result in bias of the derived results. In addition, we cannot rule out the possible influence of some mixed factors such as human movement and air pollution. Second, previous studies have shown that viruses that cause respiratory infectious diseases are sensitive to climate. Climate factors may affect the survival and transmission of viruses in the environment, host susceptibility and exposure possibilities. We found that meteorological factors played an important role during the COVID-19 in Hubei province, but we are also very clear that, as scholars have known, meteorological parameters can only explain no more than 30% of influenza activity changes (Monamele et al.,2017), and there are still many problems to be confirmed about 2019-nCoV. Third, the impact of social distancing measures on the epidemic situation should be considered in the study. This measure is an important part of the public health response to COVID-19. The corresponding measures taken in Hubei province and Wuhan City have seen actual results.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.04.01.20050526 on medRxiv