Fight Coronavirus with Global Warming

 

An important study of our experience with the covid19 pandemic shows that warmer, more humid weather works against transmission of the disease.  The paper is High Temperature and High Humidity Reduce the Transmission of COVID-19 by Jingyuan Wang, Ke Tang, Kai Feng and Weifeng Lv. Excerpts in italics with my bolds.

Abstract: This paper investigates how air temperature and humidity influence the transmission of COVID-19. After estimating the serial interval of COVID-19 from 105 pairs of the virus carrier and the infected, we calculate the daily effective reproductive number, R, for each of all 100 Chinese cities with more than 40 cases. Using the daily R values from January 21 to 23, 2020 as proxies of non-intervened transmission intensity, we find, under a linear regression framework for 100 Chinese cities, high temperature and high relative humidity significantly reduce the transmission of COVID-19, respectively, even after controlling for population density and GDP per capita of cities. One degree Celsius increase in temperature and one percent increase in relative humidity lower R by 0.0383 and 0.0224, respectively. This result is consistent with the fact that the high temperature and high humidity significantly reduce the transmission of influenza. It indicates that the arrival of summer and rainy season in the northern hemisphere can effectively reduce the transmission of the COVID-19.

Discussion: Rough observations of outbreaks of COVID-19 outside China show a noteworthy phenomenon. In the early dates of the outbreak, countries with relatively lower air temperature and lower humidity (e.g. Korea, Japan and Iran) see severe outbreaks than warmer and more humid countries (e.g. Singapore, Malaysia and Thailand) do. Considering the natural log of the average number of cases per day from February 8 to 29 as a rough measure of the severity of the COVID-19 outbreaks3 , in Figure 1, we show that the severity is negatively related to temperature and relative humidity using 14 countries with more than 20 new cases during this period.

Figure 1: Severity of COVID-19 outbreaks v.s. temperature and relative humidity for countries outside China.

Inside China, the COVID-19 has spread widely to many cities, and the intensity of transmission and weather conditions in these cities vary largely (shown in Table SI 1), we can, therefore, analyze the determinants of COVID-19 transmission, especially the weather factors. In order to formally quantify the transmission of COVID-19, we first fit 105 samples of serial intervals with the Weibull distribution (a distribution commonly used to fit the serial interval of influenza[8]), then calculate the effective reproductive number, R, a quantity measuring the severity of infectiousness[9] , for each of all 100 Chinese cities with more than 40 cases.

Figure 3: Effective reproductive number R v.s. temperature and relative humidity for 100 Chinese cities

Figure 2 shows the average R values from January 21 to 23 for different Chinese cities geographically. Compared with the southeast coast of China, cities in the northern area of China show relatively larger R values and lower temperatures and relative humidity. The scatter plots in Figure 3 illustrate two negative relations between the daily air temperature and R value and between the daily relative humidity and R value, respectively.

Our finding is consistent with the evidence that high temperature and high humidity reduce the transmission of influenza[10-14] , which can be explained by two possible reasons: First, the influenza virus is more stable in cold temperature, and respiratory droplets, as containers of viruses, remain airborne longer in dry air[15, 16] . Second, cold and dry weather can also weaken the hosts’ immunity and make them more susceptible to the virus[17, 18] . These mechanisms are also likely to apply to the COVID-19 transmission. Our result is also consistent with the evidence that high temperature and high relative humidity reduce the viability of SARS coronavirus[19,20] .

If omitting control variables, 7 the fixed-effects model of Table 2 provides an estimation of the R value for a certain city given its temperature and relative humidity:Assuming that the same relationship of Equation (1) applies to cities outside China and that the temperature and relative humid of 2020 are the same as those in 2019, we can draw a map of R values for worldwide cities in Figure 4 by plugging the average March and July temperatures and relative humidity of 2019 into Equation (1). This figure cautions people of the risk of COVID-19 outbreak worldwide, in March and July of 2020, respectively. As expected, the R values are larger for temperate countries and smaller for tropical countries in March. In July, the arrival of summer and rainy season in the northern hemisphere can effectively reduce the transmission of the COVID-19; however, risks remain in some countries in the southern hemisphere (e.g. Australia and South Africa). If we plug the normal summer temperature and relative humidity of Tokyo (28oC and 85%, respectively) into Equation (1), the transmission of the COVID19 in Tokyo will be seriously reduced between March and the Olympics: the estimated R value decreases from 1.914 to 0.992, a 48% drop!

via Science Matters

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March 25, 2020 at 12:46PM

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