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High Temperature and High Humidity Reduce the Transmission of COVID-19
Open accessAbstract
With the ongoing global pandemic of COVID-19, a question is whether the coming summer in the northern hemisphere will reduce the transmission intensity of COVID-19 with increased humidity and temperature. In this paper, we investigate this problem using the data from the cases with symptom-onset dates from January 19 to February 10, 2020 for 100 Chinese cities, and cases with confirmed dates from March 15 to April 25 for 1,005 U.S. counties. Statistical analysis is performed to assess the relationship between the transmissibility of COVID-19 and the temperature/humidity, by controlling for various demographic, socio-economic, geographic, healthcare and policy factors and correcting for cross-sectional correlation. We find a similar influence of the temperature and relative humidity on effective reproductive number (R values) of COVID-19 for both China and the U.S. before lockdown in both countries: one-degree Celsius increase in temperature reduces R value by about 0.023 (0.026 (95% CI [-0.0395,-0.0125]) in China and 0.020 (95% CI [-0.0311, -0.0096]) in the U.S.), and one percent relative humidity rise reduces R value by 0.0078 (0.0076 (95% CI [-0.0108,-0.0045]) in China and 0.0080 (95% CI [-0.0150,-0.0010]) in the U.S.). If assuming a 30 degree and 25 percent increase in temperature and relative humidity from winter to summer in the northern hemisphere, we expect the R values to decline about 0.89 (0.69 by temperature and 0.20 by humidity). Moreover, after the lockdowns in China and the U.S., temperature and relative humidity still play an important role in reducing the R values but to a less extent. Given the notion that the non-intervened R values are around 2.5 to 3, only weather factors cannot make the R values below their critical condition of R<1, under which the epidemic diminishes gradually. Therefore, public health intervention such as social distancing is crucial to block the transmission of COVID-19 even in summer.
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Metadata
- Authors
- Wang, J., Tang, K., Feng, K., & Lv, W.
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2020
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W3011996584
- Cited by
- 684
- References
- 30
- Type
- posted content
- Language
- en
- Open access
- green
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