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 temperatureand 0.20 by humidity ). 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 .
Objectives: We aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status, and human mobility status. Design: A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted. Setting: We use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1,005 U.S. counties. Participants: A total of 69,498 cases in China and 740,843 cases in the U.S. are used for calculating the effective reproductive numbers. Primary outcome measures: Regression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value). Results: Statistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the U.S. Conclusions: Higher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1 degree Celsius is associated with a reduction in the R value of COVID-19 by 0.026 (95\% CI [-0.0395,-0.0125]) in China and by 0.020 (95\% CI [-0.0311, -0.0096]) in the U.S. ; an increase in relative humidity by 1\% is associated with a reduction in the R value by 0.0076 (95\% CI [-0.0108,-0.0045]) in China and by 0.0080 (95\% CI [-0.0150,-0.0010]) in the U.S. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic .
R
With the ongoing global pandemic of COVID-19, a question is whether the coming summer in the northern hemisphere will reduce the transmission intensity
Objectives: We aim to assess the impact of temperature and relative humidity on the transmission
R
with increased humidity and temperature. In this paper, we investigate this problem using the data from the cases with
across communities after accounting for community-level factors such as demographics, socioeconomic status, and human mobility status. Design: A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted. Setting: We use the data for COVID-19 daily
R
dates from January 19 to February 10, 2020
cases
R
, and cases with confirmed dates from March 15 to April 25
and COVID-19 daily confirmed cases
R
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
Participants: A total of 69,498 cases in China and 740,843 cases in the U.S. are used for calculating the effective reproductive numbers. Primary outcome measures: Regression analysis of the impact of
A
the
R
values)of COVID-19 for
value). Results: Statistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in
R
before lockdown in both countries: one-degree Celsius
Conclusions: Higher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an
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reduces R value
R
about 0.023 (
1 degree Celsius is associated with a reduction in the R value of COVID-19 by
A
by
R
), and one percent relative humidity rise reduces
; an increase in relative humidity by 1\% is associated with a reduction in the
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0.0078 (
A
by
R
). 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 temperatureand 0.20 by humidity ). 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
Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic