Abstract
Since the COVID-19 was confirmed to have human-to-human transmissibility, it has become a severe global public health crisis. Since environmental factors such as temperature and humidity are critical factors affecting the transmission of other infectious diseases such as Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), the infection rate of viruses such as COVID-19 are likely to be influenced by the change in temperature and humidity. Therefore, a better understanding of the impact of both weather factors on the COVID-19 infection rate from areas of ongoing infection is needed. Therefore, this review explores the role of temperature and humidity in COVID-19 transmission and finds a limited effect of environmental factors on infection rate.
Introduction
In late December 2019, a novel Coronavirus disease (named later as COVID-19) rapidly spread from Wuhan, China, to other areas in the country [1]. It eventually affected the whole world by June 2020 and gained intense international attention along the way [1]. There are several factors involved in transmitting the virus. Environmental and human behavior are major components that are involved in other previously studied viruses such as SARS and MERS [2,3]. A previous study indicated that influenza outbreaks occur every winter in temperate regions [4], and a study in China indicated that outbreaks of SARS were significantly associated with the temperature and humidity [4]. Therefore, the seasonal nature in the outbreaks of respiratory virus infection is a common phenomenon that often occurs in low temperatures, during the winter. However, the impact of environmental factors is understudied on the COVID-19 infection rate. Thereafter, this paper provides a systematic review to describe current knowledge about the emergence and replicability of COVID-19 and its correlation with environmental factors.
COVID-19 and temperature
Table 1. Summary of the studies that shows a significant association of temperature change on COVID-19 infection rate
| Study sample location | Temperature Change | R-value Change |
COVID-19 infection rate | Reference |
| China, US | Increase 1oC | -0.023 | Decrease | [5] |
| China, US | Increase 1oC | -0.0225 | Decrease | [6] |
| Australia, China, Canada, US | Above 18oC | N/A | Decrease | [7] |
| Brazil | Increase 1oC | N/A | Decrease | [8] |
| Japan | Decrease | N/A | Increase | [9] |
Limited studies have investigated that higher temperature has a negative influence on the number of infected cases of COVID-19 in different locations (Table 1). Many researchers measured the daily effective reproductive numbers (R-value), which indicates the transmissibility of COVID-19 [5]. The following factors are taken into account to calculate the R-value: infectious period, contract rate, and mode of transmission [5]. For example, if R-value is less than one, it means that each existing infection causes less than one new infection, which indicates that the disease will decline and eventually die out. If R-value equals one, the existing infection causes one new infection. When R-value is more than one, the disease will be transmitted between people, and there may be an outbreak. The R-values can be calculated with two steps. Firstly, estimation of a serial interval, which is the time between successive cases in a chain of transmission, is calculated with the Weibull distribution (a distribution commonly used to fit the serial interval of the virus). After the mean and standard deviation of the serial intervals are determined, R-value can be calculated through a time-dependent method from the date when the first confirmed case occurred in the county based on Maximum Likelihood Estimation (MLE) [5].
The reduction of average R-value by 0.023 in both China and the US indicated that a 1°C increase in temperature reduces the transmissibility of COVID-19 [5]. 1°C increase in temperature was associated with a reduction in R-value by 0.0225 in 69,498 cases in China and 740,843 in the USA [6]. The combined studies from Australia, China, Canada, and the US demonstrated that the warmer temperature above 18°C slows the spread of the COVID-19 [7]. Although, the tropical temperature of Brazil indicated that the temperature had a negative linear relationship with the number of confirmed cases [8]. When the study in Japan evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020, the decreased mean temperature was positively associated with the cumulative number of COVID-19 infections [9]. Overall, many studies from different countries indicated that increased temperature is associated with a decreased number of confirmed cases worldwide.
Table 2. Summary of the studies that shows a non-significant association of temperature change on COVID-19 infection rate
| Study sample location | Statistical Modeling | Correlation between temperature change and confirmed case | Association of temperature and COVID-19 infection rate | Reference |
| India | Location dependent distribution model | 0.18 (p>0.05) |
No significant change | [10] |
| 224 cities from China | Cumulative incidence rate model | 5.03 (p=0.28) |
No significant change | [11] |
| 122 cities from China | Generalized additive model | 3.11 (p>0.05) |
No significant change | [12] |
Even though many studies indicated that increased temperature is significantly associated with confirmed cases, few studies showed that temperature does not affect the number on it (Table 2). A p-value is a probability that a null hypothesis is true. In the papers indicated in table 2, it represents the probability that the correlation between change in temperature and change in confirmed cases in the sample data occurred by chance. A p-value of 0.05 means that there is only a 5% chance that correlation results from the indicated sample occurred due to chance. In most research, the threshold of the p-value of 0.05 or below is considered to be statistically significant. The p-values are greater than 0.05 in the papers in table 2, indicating that there is no significant association between temperature and confirmed cases.
When the distribution modeling of new cases of COVID-19 across temperature was analyzed with worldwide data, the result was not correlated with India’s pattern of new cases of COVID-19[10]. This result suggested that variation of temperature does not correlate with the number of new cases in India, as of April 9, 2020 [10]. The study in the cities of Hubei, China indicated that the cumulative incidence rate is not significantly associated with the temperature [11]. The data of averaged daily temperature, maximum temperature, minimum temperature from early January to early March for 224 cities in China showed that the temperature held no association with cumulative incidence rate [11]. Other studies in China indicated that no evidence was found that case counts of COVID-19 could decline when the weather becomes warmer [12]. These observations predict that other factors such as demographic variations and lockdowns affected the transmission dynamics more than the temperature itself.
COVID-19 and humidity
Humidity is the atmospheric moisture of a place or location. It is a very important component in the environment, as it can affect human bodies and living conditions drastically. Humidity can make the bodies feel a lot hotter than usual since the sweat cannot evaporate. Therefore, to cool down, hard work is needed, which can result in extreme sweating. Very high humidity levels can even affect human health through the pollution of homes. Research done by Naran, a technology organization, found that indoor humidity can help the spread and growth of viruses, fungi, bacteria, and even dust mites [13].
Table 3. Summary of the studies that shows a significant association of humidity change on COVID-19 infection rate
| Study sample location | Humidity Change |
R-value Change |
COVID-19 infection rate | Reference |
| China, US | Increase 1% | -0.0078 | Decrease | [5] |
| Wuhan city, China | Increase 1 unit | -0.32 | Decrease | [14] |
| 166 countries | Increase 1% | N/A | Decrease | [15] |
| India | Increase in relative humidity | N/A | Decrease | [16] |
Most studies and experiments found that humidity also has an influence on the number of confirmed cases of COVID-19 in contrasting locations (Table 3). In China and the U.S, one study conducted by professors at Beihang University showed that a 1% percent increase in the rate of relative humidity can affect the rate of the spread of COVID-19, as it decreases the R-value in both China and the US by 0.0076 and 0.0080 respectively [5]. Also, in a different study conducted in Wuhan, China, a decrease in transmission rates of COVID-19 was shown as relative humidity increased [14] Furthermore, another study, including all 166 countries, found that a 1% increase in relative humidity resulted in a 0.85% reduction in daily new cases, and a 0.51% reduction in daily new deaths [15]. A study conducted in India also indicated that average relative humidity can reduce the incidence of COVID-19, but the results are inconsistent between various states, so further studies are needed [16]. Overall, most studies find that humidity does influence the transmission rate of COVID-19, usually an influence that decreases the rates of infection when relative humidity is increased.
Table 4. Summary of the studies that shows a non-significant association of humidity change on COVID-19 infection rate
| Study sample location | Statistical Modeling | Correlation between relative humidity and confirmed case | Association of temperature and COVID-19 infection rate | Reference |
| China, Italy, Japan, and 51 other countries | Single-factor non-linear regression model | 0.24 (p>0.05) |
No significant change | [17] |
| China | Linear model | 0.17 (p>0.05) |
No significant change | [18] |
However, on the other hand, various studies claim that humidity and weather, in general, cannot influence the number of COVID-19 cases and the infection rate (Table 4). For example, one study about the roles of meteorological conditions of COVID-19 transmission on a worldwide scale conducted by researchers from the Jiangsu Province Hospital of Chinese Medicine showed that across 430 cities and districts across China, 21 cities/provinces in Italy, 21 cities/provinces in Japan, and 51 other countries in the world, one single weather factor, like humidity or temperature, could not correspond with the COVID-19 case counts [17]. Additionally, another study conducted by researchers from Harvard Medical School found out that the role of absolute humidity in the infection rates of COVID-19 hasn’t been identified yet [18]. This study found that changes in weather factors like humidity and temperature won’t necessarily decrease COVID-19 case counts alone [18]. To sum up, some studies show that humidity might not have any sort of effect on the spread of COVID-19, neither decreasing the spread nor increasing the spread.
Conclusion
COVID-19 cannot replicate outside living cells but it can infect humans and be transmitted to others. Hence, the duration of the persistence of the viable virus is an important factor for analyzing its transmissibility. Many studies have been done on the effect of weather factors on the infectivity of previously detected viruses such as coronavirus 229E, Severe acute respiratory syndrome (SARS) [19,20]. The virus viability was rapidly lost at a higher temperature and higher relative humidity [19,20]. However, there is little information about how COVID-19 was affected by environmental factors. Therefore, understanding the role of these factors on the transmissibility of COVID19 is important to control the pandemic.
There was a slight influence overall that both environmental factors did not have that much of a big effect. An increased number of confirmed cases were reported recently from the study from African equatorial and Amazon rainforest regions, which has both high temperatures and humidities[21]. This study indicates that several other aspects might have also affected these correlational observations in different countries: healthcare infrastructure and social policies such as lockdowns. Also, since most of these studies have not been peer-reviewed, they should be evaluated with caution. Some of these studies also do not investigate the combined effect of these environmental factors. Since other factors could have a much bigger impact on COVID-19 infection rates than weather constituents like humidity and temperature, future studies should aim to investigate the combined effect of such factors to fully understand the transmission rate of COVID-19.
Reference
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About the Author
Sahngwon Lee is a Seoul International School(SIS) student from South Korea. He is a rising 9th grader now. He went to many different schools in his life, as he had to move to many other countries because of his dad’s job. Sahngwon is most fluent in English, but he is also fluent in Chinese and Korean.