This study investigated the association between weather conditions including air temperature, and relative humidity with the confirmed cases of COVID-19 infection (Table 1s). The trend of changes in the positive cases of COVID-19 infections, ambient air temperature and relative humidity was presented in Fig. 1. Two major peaks of COVID-19 cases were observed in 15th October (n = 22 cases) and 8th November (n = 20 cases). The overall trend of confirmed cases is increasing over study period. However as expected small fluctuations can be observed. In case of Temperature, the overall trend is decreasing from the peak at 37.3°C (5th August) to the lowest values around 21.2°C (25th November). In case of RH, some large fluctuations were detected, namely in 30th August − 5th September, 9th September − 26th September, and 10th October – 1st November. The total number of positive cases COVID-19 infection was 1041 in Bandar Abbas during the study period. In addition, the averages of air temperature, and relative humidity were 30.04 ± 4.34°C and 53.18 ± 17.93%, respectively (Table 1). These results show that Bandar Abbas has a warm and humid climate.
Table 1
Spearman coefficients between positive cases of Covid-19 infection with weather variables.
Weather variables
|
Mean ± SD
|
Coefficient
|
P value
|
Ambient air temperature (°C)
|
30.04 ± 4.34
|
-0.303
|
0.001
|
Relative humidity (%)
|
53.18 ± 17.93
|
0.088
|
0.340
|
The Spearman correlation analysis shows that there was a significant association between the daily number of confirmed cases of COVID-19 and ambient air temperature (Coefficient = -0.303 and P-value = 0.001) (Table 1 and Fig. 2A). In case of relative humidity, no significant correlation with daily number of COVID-19 cases was observed (Coefficient = 0.088 and P-value = 0.340) (Table 1 and Fig. 2B). These results show that ambient air temperature can negatively affect the spread of COVID-19, i.e. with increasing air temperature, a decrease in number of COVID-19 cases could be expected. While, increasing relative humidity can increase the daily confirmed cases of the disease.
Our findings are consistent with some other studies. In a study conducted on 31 provincial-level regions in China, using a distributed lag non-linear model (DLNM), the authors found that although higher temperatures directly affected the number of COVID-19 cases in some regions, the association in most of the areas and also in the whole country was negative, indicating a reduction in positive cases of COVID-19 after the incidence of high temperatures (RR: 0.96, 95% CI: 0.93–0.99). In the same study, a significant negative association was found between temperature and relative risk of COVID-19 infection in mainland China (Coefficient = − 0.0100, 95% CI: −0.0125, − 0.0074) [29]. In another study on 11 cities of China, temperature and humidity negatively associated with the transmissibility of COVID-19 ( P-value < 0.001) [30]. In a study of 430 cities around the world for 52 days, a meteorological model was able to predict the global outbreak with a high association (R2 > 0.6) [31]. Despite our study, a study in Indonesia showed that the average air temperature has a positive significant association with the daily positive cases of COVID-19, indicating an increase in the number of positive cases with the increase in temperature. The association was also positive for other weather variables including minimum and maximum temperature, relative humidity, and rainfall [32]. In a study of Wuhan, the mortality of COVID-19 was associated with temperature positively (R = 0.44) and with relative humidity negatively (R = − 0.32) [33].
The contradiction between the results of studies may be due to the range of temperature and RH observed in each place. An analysis of 122 Chinese cities shows that the association between COVID- 19 and ambient air temperature was approximately linear in the range of < 3°C. When ambient air was less than 3°C, each 1°C rise temperature was associated with a 4.86% (95% CI: 3.21–6.51) increase in positive cases of COVID-19 [18]. In another study, the spread of the virus showed a strong association within the 4–12°C mean daily air temperature [34]. Shi et al. (2020) considering 31 provincial-level regions in China reported that the association between daily cases of COVID-19 and air temperature is biphasic (with a peak at 10°C). For temperatures higher than 10°C, a decrease in the number of positive cases was observed; while, with increasing temperature up to 10°C, positive cases increased [29].
There are many other factors that can potentially affect the spread of COVID-19 infection, and interfere with the effect of weather [32]. This is probably why the results of relevant studies contradict. First, the mobility of the population i.e. entry and exit into the city can change the daily number of positive cases. Second, the change in individual health parameters consist of use of hand sanitizers and hand washing habits due to education could alter the trends. Third, there are other weather variables such as visibility and atmospheric variables such as ultra-violet (UV) radiation that are included in other studies [31, 34], but these data were not accessible. And last but not the least, socio-economic development, urbanization ,population immunity, and level can all be other affecting factors [35].
To draw a conclusion whether meteorological parameters such as temperature and humidity can affect the spread of SARS-CoV-2, more comprehensive studies with longer study periods and broader study areas are required. Since the SARS-CoV-2 is novel, current evidence stands only on data recorded during a few months and from some limited areas. Therefore, the results of this study and similar ones should be used conservatively. In addition, the association between weather conditions and the number of positive cases of COVID-19 could be non-linear. Therefore, investigating a limited range of temperatures and also other variables could lead to different results.