Correlation Analyses between Ultraviolet Radiation, Global Solar Radiation, and Metrological Variables and the COVID-19 Cases in Arid Climate

Maghrabi Abdullrahman

National Centre for Applied Physics, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia.

DOI: 10.4236/aid.2022.122015                

Abstract

The transmission of infectious diseases is influenced by several meteorological factors. In this study, the influence of several such factors in the transmission of COVID-19 (from 26 March 2020 to 29 July 2021) in the arid weather of Riyadh, Saudi Arabia was investigated using the Spearman and Kendall rank tests. The factors considered were the average, maximum, and minimum values of air temperatures, air pressure, wind speed, relative humidity, absolute humidity, dew point temperatures, and the average values of the global solar radiation and ultraviolet radiation at bands A and B. The data on meteorological factors were obtained from the King Abdulaziz City for Science and Technology (KACST) weather station, whereas the data on the daily COVID-19 cases were obtained from the official webpage of the Saudi Arabian Ministry of Health (MOH). The results revealed that air temperature (average, minimum, and maximum) average and maximum wind speed, maximum dew point temperature, global solar radiation, and ultraviolet radiation at A and B bands are positively associated with the daily number of COVID-19 cases reported in Riyadh. However, relative humidity, atmospheric pressure (averages, minimum, and maximum) is anti-correlated with the number of daily COVID-19 cases, while absolute humidity exerts no influence. These results are in total agreement with some of the previously established studies and are either contradicted partly or totally with others conducted at several locations around the world. The results could help not only epidemiologists understand the behavior of COVID-19 against meteorological variables but also national and international organizations and healthcare policymakers devise control strategies to combat the virus.

Keywords

COVID-19, Dry Conditions, Meteorology, Ultraviolet Radiation, Correlation

1. Introduction

Ever since it was first reported in Wuhan, China, in December 2019, the Coronavirus disease (COVID-19) has spread worldwide, developing into a pandemic and one of the most significant global health threats in a century (e.g., Wang et al., 2020). Shortly afterwards, several research studies were conducted worldwide to investigate the association between COVID-19 and a wide range of factors—social and economic as well as weather-related, including meteorological and environmental factors such as air temperature and air pollution [1]. The effect of meteorological conditions on COVID-19 transmission has been studied in several places, including China [2] - [7], Iran [8], Europe [9], Turkey [10], Brazil [11] [12] and the United States of America [13] [14] [15].

These studies did report the significant effect of meteorological factors on COVID-19 transmission, but regarding the relationship between the two, they reached contradictory conclusions. The exact mechanisms the meteorological factors employ to increase COVID-19 transmission and their potential role in it remain overlooked and yet to be clearly understood. The reported association could also differ from one climatic region to another. Moreover, most of the studies covered extremely short investigative periods, which could have affected their outcomes, thus necessitating the examination and evaluation of each region within its dynamics.

To the best of our knowledge, very few studies have been conducted between weather parameters and the evolution of COVID-19 in desert climate regions. In light of this, this study aims to fill this research gap by exploring the relationships between the metrological variables and the daily confirmed COVID-19 infections in Riyadh, Saudi Arabia. Riyadh was chosen because of its arid conditions, its population density, and its highest number of daily COVID-19 cases in Saudi Arabia.

2. Material and Method

2.1. Data

The maximum, minimum, and average values of the air temperature, relative humidity, atmospheric pressure, dew point temperature, wind speed, the daily mean values of the global solar radiation, and ultraviolet radiation in bands A and B were the considered meteorological variables. These data were collected from the KACST weather station installed on the roof of the radiation detector lab. The station is equipped with all the sensors that continuously monitor several weather parameters. The detailed explanations about these sensors are described in [16]. The daily data of the COVID-19 cases were taken from the official website of the Saudi Ministry of Health. The data used in this study cover the period from 26 March 2020 to 29 July 2021.

2.2. Statistical Tests

Studies have used several statistical tests and procedures to investigate the relationships between the number of daily COVID-19 cases and meteorological parameters: the Spearman’s rank correlation coefficient [17], Kendall’s rank correlation, the generalized linear model [18], and polynomial linear regression. In this study, the Spearman and Kendall rank correlation tests were used. The factors were considered influential in COVID-19 transmission if significant differences were observed in both statistical tests. The Spearman’s rank correlation coefficient is the nonparametric version of the Pearson product-moment and is used to examine the associative strength between two variables (monotonic relationship). The Spearman rank correlation test’s formula is as follows (e.g., [9] ):

$\rho =1-6\times \frac{{\displaystyle \sum d_i^2}}{n\left(n^2-1\right)}$

ρ is the Spearman rank correlation coefficient; d_i is the difference between the ranks of corresponding values x_i and y_i; n is the number of x and y pairs.

Kendall rank correlation, also another non-parametric test, is used to assess the statistical associations based on the ranks of data and can be estimated as follows:

$\tau =\frac{n_c-n_d}{\frac{1}{2}n\left(n-1\right)}$

τis the Kendall rank correlation coefficient; n_c and n_d represent the number of concordant and discordant pairs, respectively; n represents the number of pairs.

3. Results

Since the first confirmed case of COVID-19 in Saudi Arabia (on March 2, 2020), a total of 542,000 cases have been reported as of August 20, 2021. During our study period-26 March 2020 to 29 July 2021-103,729 confirmed locally transmitted COVID-19 cases were identified in Riyadh.

Figure 1 shows the daily mean values of the confirmed COVID-19 cases and the meteorological variables in Riyadh considered in this study.

During the study period, the mean number of COVID-19 confirmed cases was 207.54 ± 256.38, with a maximum of 2371 and a minimum of 13. The time series profile (Figure 1(a)) of the reported cases can be divided into three phases.

The first period covered the period between April 3, 2020 to August 10, 2020. This period was characterized by great variations in the number of reported COVID-19 cases. The number of cases increased rapidly and reached a maximum of 2317 cases on June 16. Then it dropped significantly within about a week, reaching 225 on June 26, and then reached a minimum of 45 by about August 10.

Figure 1. the time series of the daily values of (a) the number of cases of COVID-19; (b) the maximum, minimum, and mean values of air temperatures; (c) the maximum, minimum, and mean values of dew point temperature; (d) the maximum, minimum, and mean values of relative humidity; (e) the maximum, minimum, and mean values of wind speed (f) the maximum, minimum, and mean values of atmospheric pressure; (g) absolute humidity; (h) ultraviolet radiation at band A; and (i) ultraviolet radiation at band b; (j) global solar radiation in Riyadh during the study period.

The second phase covered the period between August 10, 2020 to February 3, 2021. This period had small variations in the number of cases. The mean number of the reported cases was 42, with a minimum of 14 and a maximum of 78.

The third phase was from the end of the second phase until the end of the study period. This phase featured a steady and slight increasing trend in the number of the reported cases until March 18, 2021. The average number of cases was 114. Afterwards, the number of cases increased dramatically to reach a maximum of about 400 cases on April 14, which may be attributed to family gatherings and social activities after the holy month of fasting during April. For the next two months, the number of cases decreased slightly to reach a mean of about 220 cases and remained around this number for the rest of the period.

Apart from the wind speed, absolute humidity, mean dew point temperature, all of which showed no clear trends during the study period, the rest of the variables followed a cyclical pattern. Air temperature, ultraviolet (A and B), and global solar radiation reached their maximum in summer and minimum in winter. On the other hand, relative humidity and atmospheric pressure showed the opposite trend.

The considered variables obviously covered a wide range of values during the study period. For instance, the air temperature ranged between 47.78 and 2.77, RH was between 4% to 100%, and air pressure was 965.12 and 927.80 hPa.

Table 1 summarizes the results of the Kendall and Spearman correlation tests on the association of daily COVID-19 cases and weather parameters in Riyadh from 26 March 2020 to 29 July 2021.

Table 1. Summary of nonlinear correlation (Kendall τ and Spearman ρ) results between COVID-19 and meteorological parameters and solar radiation data (26 March 2020 to 29 July 2021; N = 492) in Riyadh.

The results reveal that, unlike the mean and minimum values of the dew point temperatures, the minimum values of wind speed, and absolute humidity, the rest of the considered variables do have significant correlations with the number of the COVID-19 cases with a 99% confidence interval (2-tailed significance). However, the strength and type of this correlation (either positive or negative) were different from one variable to another.

Moreover, the Kendall and Spearman tests revealed that global solar radiation, UVA, UVB, air temperature, and wind speed (maximum, minimum, and mean values) are correlated positively with the number of COVID-19 cases. While the correlations between the number of COVID-19 cases and the mean wind speed and maximum dew point temperature were the lowest (τ = 0.134; ρ = 0.207 for the former and τ = 0.0.091; ρ = 0.139 for the latter), the rest of the variables presented slightly stronger relationships with the number of the COVID-19 cases (τ ranges between 0.300 - 0.360; ρ ranges between 0.532 - 0.400).

The mean values of the relative humidity, atmospheric pressure, and their maximum and minimum values anti-correlated significantly with the number of COVID-19 cases. For all the correlations, the Kendall coefficients ranged between 0.319 and 0.290, whereas the Spearman coefficients ranged between 0.427 and 0.494.

4. Discussions and Conclusions

According to the no-parametric analyses conducted in this study, the air temperature (mean, minimum, and maximum) mean and maximum wind speed, the maximum dew point temperature, global solar radiation, and ultraviolet radiation at A and B bands are all positively associated with the daily number of the COVID-19 cases reported in the arid climate of Riyadh. Moreover, the relative atmospheric pressure (mean, minimum, and maximum) are anti-correlated with the number of COVID-19 cases, whereas absolute humidity exerts no influence.

These results are aligned with some of the previously established studies and are either contradicted partly or totally with others conducted at several locations around the world. For instance, our finding of the positive effect of the mean temperature and wind speed and the number of COVID-19 cases is supported by [2] [14] [17] [19] [20] [21] reported that only the mean air temperature was significantly correlated with the transmission of COVID-19. According to [22], temperature and absolute humidity have been reported as crucial weather indices associated with the spread of COVID-19. Auler [11] established that mean temperature and average relative humidity are significant in the transmission of COVID-19 in Brazil. Yao et al. [3] claimed no correlation between COVID-19 and UV radiation. Rosario et al. [23] showed that solar radiation has a strong negative relationship with COVID-19 transmission. Wang et al. [15] showed that warm weather plays an important role in suppressing the virus. Islam et al. [24] found that temperature and wind speed have a negative relationship with the number of infections. Xie and Zhu [2] conducted a study in 122 cities across China and established that the humidity, wind speed, and temperature are inversely associated with the infection rate of COVID-19. Wu et al. [25] and Qi et al. [18] stated that the temperature and RH were both negatively associated with daily new cases and mortality.

As we can see from our results and the findings of different studies, the meteorological factors, though they exert different degrees of influence, do have pronounced effects on COVID-19 transmission. Moreover, this study covers a longer period than most of the previous researches and contributes additional knowledge to the understanding of the effects of meteorological and atmospheric factors on influenza activities. Our findings can be useful and important for the development of influenza surveillance and early warning systems.

This study has several limitations. First, the infected cases might have been impacted by several additional factors—such as social behaviors, demography, economic, immunology, and epidemiology factors—and so the number of confirmed cases due to meteorological factors might be inaccurate. Moreover, due to data and time constraints, this study focused only on one region, so further studies covering more sites are recommended to better confirm the relationship between meteorological factors and COVID-19 cases.

Authorship Contribution Statement

The author was responsible for all the work presented in this article.

Conflicts of Interest

We declare no conflict of interest.

References

[1]	Qu, G., Li, X., Hu, L. and Jiang, G. (2020) An Imperative Need for Research on the Role of Environmental Factors in Transmission of Novel Coronavirus (COVID-19). Environmental Science & Technology, 54, 3730-3732. https://doi.org/10.1021/acs.est.0c01102
[2]	Xie, J. and Zhu, Y. (2020) Association between Ambient Temperature and COVID-19 Infection in 122 Cities from China. Science of Total Environment, 724, Article ID: 138201. https://doi.org/10.1016/j.scitotenv.2020.138201
[3]	Yao Y., Pan, J., Liu, Z., et al. (2020) No Association of COVID-19 Transmission with Temperature or UV Radiation in Chinese Cities. European Respiratory Journal, 55, 7-9. https://doi.org/10.1183/13993003.00517-2020
[4]	Ma, Y., Zhao, Y., Liu, J., He, X., et al. (2020) Effects of Temperature Variation and Humidity on the Death of COVID-19 in Wuhan, China. Science of the Total Environment, 724, Article ID: 138226. https://doi.org/10.1016/j.scitotenv.2020.138226
[5]	Qi, H., Xiao, S., Shi, R., Ward, M., et al. (2020) COVID-19 Transmission in Mainland China Is Associated with Temperature and Humidity: A Time-Series Analysis. Science of the Total Environment, 728, Article ID: 138778. https://doi.org/10.1016/j.scitotenv.2020.138778
[6]	Pani, S., Lin, N. and RavindraBabu, S. (2020) Association of COVID-19 Pandemic with Meteorological Parameters over Singapore. Science of the Total Environment, 740, Article ID: 140112. https://doi.org/10.1016/j.scitotenv.2020.140112
[7]	Mofijur, M., Fattah, I., Saiful Islam, A., Rahman, S. and Chowdhury, M. (2020) Relationship between Climate Variables and New Daily COVID-19 Cases in Dhaka, Bangladesh. Sustainability, 12, 20. https://doi.org/10.3390/su12208319
[8]	Ahmadi M., Sharifi, A., Dorosti, S., Jafarzadeh Ghoushchi, S. and Ghanbari, N. (2020) Investigation of Effective Climatology Parameters on COVID-19 Outbreak in Iran. Science of the Total Environment, 729, Article ID: 138705. https://doi.org/10.1016/j.scitotenv.2020.138705
[9]	Ceylan, Z. (2021) Insights into the Relationship between Weather Parameters and COVID-19 Outbreak in Lombardy, Italy. International Journal of Healthcare Management, 14, 255-263. https://doi.org/10.1080/20479700.2020.1858394
[10]	Şahin, M. (2020) Impact of Weather on COVID-19 Pandemic in Turkey. Science of the Total Environment, 728, Article ID: 138810. https://doi.org/10.1016/j.scitotenv.2020.138810
[11]	Auler, A.C., Cássaro, F.A.M., da Silva, V.O. and Pires, L.F. (2020). Evidence That High Temperatures and Intermediate Relative Humidity Might Favor the Spread of COVID-19 in Tropical Climate: A Case Study for the Most Affected Brazilian Cities. Science of the Total Environment, 729, 1-34. https://doi.org/10.1016/j.scitotenv.2020.139090
[12]	Prata, D., Rodrigues, W. and Bermejo, P. (2020) Temperature Significantly Changes COVID-19 Transmission in (Sub)tropical Cities of Brazil. Science of the Total Environment, 729, Article ID: 138862. https://doi.org/10.1016/j.scitotenv.2020.138862
[13]	Li, K. (2020) The Link between Humidity and COVID-19 Caused Death. Journal of Biosciences and Medicines, 8, 50-55. https://doi.org/10.4236/jbm.2020.86005
[14]	Bashir, M.F., Ma, B., Bilal, Komal, B., Bashir, M.A., Tan, D. and Bashir, M. (2020) Correlation between Climate Indicators and COVID-19 Pandemic in New York, USA. Science of the Total Environment, 728, 1-4. https://doi.org/10.1016/j.scitotenv.2020.138835
[15]	Wang, Y., Wang, Y., Chen, Y. and Qin, Q. (20200 Unique Epidemiological and Clinical Features of the Emerging 2019 Novel Coronavirus Pneumonia (COVID-19) Implicate Special Control Measures. Journal of Medical Virology, 92, 568-576. https://doi.org/10.1002/jmv.25748
[16]	Maghrabi, A., Almutairi, M., Aldosari, A., Altilasi, M. and Al shehri, A.A. (2021) Charged Particle Detector-Related Activities of the KACST Radiation Detector Laboratory. Journal of Radiation Research and Applied Sciences, 14, 111-124. https://doi.org/10.1080/16878507.2021.1877393
[17]	Tosepu, R., Gunawan, J., Effendy, D.S., et al. (2020) Correlation between Weather and COVID-19 Pandemic in Jakarta, Indonesia. Science of the Total Environment, 725, Article ID: 138436. https://doi.org/10.1016/j.scitotenv.2020.138436
[18]	Qi, L., Gao, Y., Yang, J., Ding, X., Xiong, Y., Su, K. and Liu, Q. (2020) The Burden of Influenza and Pneumoniamortality Attributable to Absolute Humidity among Elderly People in Chongqing, China, 2012-2018. Science of the Total Environment, 716, Article ID: 136682. https://doi.org/10.1016/j.scitotenv.2020.136682
[19]	Tan, J., Mu, L., Huang, J., Yu, S., Chen, B. and Yin, J. (2005) An Initial Investigation of the Association between the SARS Outbreak and Weather: With the View of the Environmental Temperature and Its Variation. Journal of Epidemiology and Community Health, 59, 186-192. https://doi.org/10.1136/jech.2004.020180
[20]	Vandini, S., Corvaglia, L., Alessandroni, R., et al. (2013) Respiratory Syncytial Virus Infection in Infants and Correlation with Meteorological Factors and Air Pollutants. Italian Journal of Pediatrics, 39, Article No. 1. https://doi.org/10.1186/1824-7288-39-1
[21]	Park, J., Son, W., Ryu, Y., Choi, S., Kwon, O., Ahn, I. (2020) Effects of Temperature, Humidity, and Diurnal Temperature Range on Influenza Incidence in a Temperate Region. Influenza and Other Respiratory Viruses, 14, 11-18. https://doi.org/10.1111/irv.12682
[22]	Gupta, S., Raghuwanshi, G. and Chanda, A. (2020) Effect of Weather on COVID-19 Spread in the US: A Prediction Model for India in 2020. Science of the Total Environment, 728, Article ID: 138860. https://doi.org/10.1016/j.scitotenv.2020.138860
[23]	Rosario, D., Mutz, Y.S., Bernardes, P.C. and Carlos, A. (2020) Relationship between COVID-19 and Weather: Case Study in a Tropical Country. International Journal of Hygiene and Environmental Health, 229, Article ID: 113587. https://doi.org/10.1016/j.ijheh.2020.113587
[24]	Islam, N., Shabnam, S. and Erzurumluoglu, A.M. (2020) Temperature, Humidity, and Wind Speed Are Associated with Lower Covid-19 Incidence. 1-4. https://doi.org/10.1101/2020.03.27.20045658
[25]	Wu, Y., Jing, W., Liu, J., Ma, Q., et al. (2020) Effects of Temperature and Humidity on the Daily New Cases and New Deaths of COVID-19 in 166 Countries. Science of the Total Environment, 729, Article ID: 139051. https://doi.org/10.1016/j.scitotenv.2020.139051