Transmissibility of COVID-19 in 11 major cities in China and its association with temperature and humidity in Beijing, Shanghai, Guangzhou, and Chengdu

Abstract

Background: The new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19. Methods: In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R 0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R 0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables. Results: It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R 0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R 0 in Wuhan. R 0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level. Conclusions: The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R 0 and weather, the spread of disease will be suppressed as the weather warms.

Independent Association of Meteorological Characteristics With Initial Spread of Covid-19 in India

“…Several researchers around the world have demonstrated an inverse relationship between air temperature and COVID-19 transmissibility. [23][24][25][26][27] Our results also are in agreement with the general understanding that higher ambient temperature can inversely influence COVID-19 transmissibility. 23,27 The study duration mark a period of increasing temperature in the Indian peninsula and our results indicate that, in general, high ambient temperatures were associated with lower R 0 estimates such that unit standard deviation increase in air temperature was associated with a 0.08 lower R 0 (Table 1, final model).On the other hand, we observed that a unit standard deviation increase in wind speed was associated with a 0.08 higher R 0 ( Table 1, (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.…”

Correlations between Meteorological Indicators, Air Quality and the COVID-19 Pandemic in 12 Cities across China

“…Daily COVID-19 death counts were positively associated with the diurnal temperature range, but had a negative association with relative humidity from January 20, 2020 to February 29, 2020 in Wuhan [17]. The effects of low temperatures, a mild diurnal temperature range and low humidity was said to increase the spread of COVID-19, conversely, it was said the warmer weather in China from January 20 to March 2020 minimized its spread [18][19][20]. A recent meta-analysis showed that the overall intensity of the COVID-19 epidemic in China reduced slightly following the days with higher temperatures [16].…”

Independent association of meteorological characteristics with initial spread of Covid-19 in India

“…Several researchers around the world have demonstrated an inverse relationship between air temperature and number of COVID-19 cases ( Demongeot et al, 2020 ; Guo et al, 2020 ; Harmooshi et al, 2020 ; Jahangiri et al, 2020 ; Malki et al, 2020 ; Pramanik et al, 2020 ; Ran et al, 2020 ; Ren et al, 2020 ; Seligmann et al, 2020a ; Steiger et al, 2020 ). Our results are in agreement with the general understanding that higher ambient temperature can inversely influence COVID-19 transmissibility ( Guo et al, 2020 ; Jahangiri et al, 2020 ). Our study duration marks a period of increasing temperature in the Indian peninsula and our results indicate that, in general, high ambient temperatures were associated with lower R 0 estimates such that one standard deviation increase in air temperature was associated with a 0.08 lower R 0 ( Table 3 , final model).…”