key: cord-0770042-1bxt21za
authors: Pani, Shantanu Kumar; Lin, Neng-Huei; RavindraBabu, Saginela
title: Association of COVID-19 pandemic with meteorological parameters over Singapore
date: 2020-06-12
journal: Sci Total Environ
DOI: 10.1016/j.scitotenv.2020.140112
sha: 862b7b61104521ebac918512629cac71ec2d8900
doc_id: 770042
cord_uid: 1bxt21za

Abstract Meteorological parameters are the critical factors affecting the transmission of infectious diseases such as Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and influenza. Consequently, infectious disease incidence rates are likely to be influenced by the weather change. This study investigates the role of Singapore's hot tropical weather in COVID-19 transmission by exploring the association between meteorological parameters and the COVID-19 pandemic cases in Singapore. This study uses the secondary data of COVID-19 daily cases from the webpage of Ministry of Health (MOH), Singapore. Spearman and Kendall rank correlation tests were used to investigate the correlation between COVID-19 and meteorological parameters. Temperature, dew point, relative humidity, absolute humidity, and water vapor showed positive significant correlation with COVID-19 pandemic. These results will help the epidemiologists to understand the behavior of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus against meteorological variables. This study finding would be also a useful supplement to help the local healthcare policymakers, Center for Disease Control (CDC), and the World Health Organization (WHO) in the process of strategy making to combat COVID-19 in Singapore.

Coronavirus disease 2019 (COVID-19; previously known as 2019-nCoV) outbreak is associated with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is a novel coronavirus with a probable bat origin Lam et al., 2020) , that originated in the area of Wuhan, Hubei province, China, in late December of 2019 . SARS-CoV-2 is a single-stranded positive-sense RNA virus (Satija and Lal, 2007) with diameter ranging from 60 to 140 nm (Hsiao et al., 2020; Zou et al., 2020) . The reproduction number of SARS-CoV-2 is close to or slightly higher than Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and SARS-CoV- 1 (Lipsitch et al., 2003; Wallinga and Teunis, 2004; Lin et al., 2018; Zhou et al., 2020; Lim et al., 2020) . COVID-19 spreads rapidly throughout the globe due to its highly contagious nature and it was officially declared a pandemic by the World Health Organization (WHO) on March 11, 2020 (WHO, 2020a). SARS-CoV-2 is essentially transmitted directly by human-to-human transmission via close contact (i.e., through respiratory droplets emitted from an infected person, during coughing, sneezing, laughing, and exhaling, to another healthy person) and also indirectly J o u r n a l P r e -p r o o f 5 2012). Meteorological parameters are generally believed to be effective drivers in the transmission of viruses causing infectious diseases (e.g. Yuan et al., 2006; Chan et al., 2011; van Doremalen et al., 2013; Kutter et al., 2018; Dalziel et al., 2018) . Both laboratory and epidemiological studies have shown that particularly the ambient temperature is a crucial factor in the transmission and survival of coronaviruses like MERS-CoV and SARS-CoV-1 (e.g. Tan et al., 2005; Bi et al., 2007; Casanova et al., 2010; Chan et al., 2011; van Doremalen et al., 2013) . Qu and Wickramasinghe (2017) reported that high solar radiation can prevent the transmission by inactivating the MERS-CoV and SARS-CoV-1 like coronaviruses.

Transmission of Influenza and pneumonia is greatly affected by meteorological parameters (Steel et al., 2011; Barreca, 2012; Barreca and Shimshack, 2012; Davis et al., 2016a; 2016b) .

However, this is still debatable whether the spread of COVID-19 is being influenced by the meteorology as are other seasonal viruses (Neher et al., 2020) or not. Several recent studies investigated the effects of meteorological/weather conditions on COVID-19 transmission over different worldwide locations such as China Xie and Zhu, 2020; Ma et al., 2020; Qi et al., 2020) , Iran (Ahmadi et al., 2020) , Spain (Briz-Redón and Serrano-Aroca, 2020), the USA (Bashir et al., 2020; Gupta et al., 2020) , Mexico (Méndez-Arriaga, 2020), Turkey (Sahin, 2020), Brazil (Auler et al., 2020; Prata et al., 2020) , Indonesia (Tosepu et al., 2020) , Norway (Menebo, 2020) and also over the globe (Sobral et al., 2020; Wu et al., 2020a) . Conclusions about the effect of meteorological conditions on COVID-19 transmission are still controversial. Evidences published on COVID-19 so far has not certainly resolved that weather condition is a key modulator of the SARS-CoV-2 transmission (e.g. Yao et al., 2020a; Gunthe et al., 2020; Gupta et al., 2020; Xie and Zhu, 2020; Tobías and Molina, 2020) . Nevertheless, there is still an insufficiency of evidence. Moreover, the WHO J o u r n a l P r e -p r o o f 6 also states that vigorous studies are required to improve forecasting models and to adopt public health measures. Therefore, investigations of COVID-19's weather dependency in different regions or countries or cities are important to enhance the present understanding about its spread. Southeast Asia (SEA; here defined as Singapore, Indonesia, Philippines, Malaysia, Thailand, Vietnam, Myanmar, Brunei, Cambodia, and Laos), a well-known region for its high pollution loadings and complex meteorology (Lin et al., 2013; Salinas et al., 2013; Tsay et al., 2016; Kusumaningtyas et al., 2018; Khamkaew et al., 2016; Pani et al., 2016a Pani et al., , 2016b Pani et al., , 2018 Pani et al., , 2019a Pani et al., , 2019b Pani et al., , 2020 Hien et al., 2019; Tham et al., 2019; Dahari et al., 2020) , has been hit hard by the COVID-19 pandemic with a surge of new cases recently (Fig. 1) . The total number of reported cases and deaths, associated with COVID-19 pandemic in SEA as of May 31, 2020, were 91180 and 2773, respectively (https://www.worldometers.info/coronavirus/). Among the SEA countries, the highest number of total cumulative cases was reported for Singapore (Fig. 2) .

Singapore, an urban agglomeration in maritime SEA, declared its first case of COVID-19 (imported case in relation to a 66-year old male Chinese national from Wuhan) on January 23, J o u r n a l P r e -p r o o f 7 controlling factors, this study mainly investigates the association of COVID-19 with various meteorological parameters in Singapore.

Singapore, an industrialized and urbanized city-state and island country, lies off the southern tip of Malay Peninsula in maritime SEA. It is separated from Indonesia's Riau Islands by the Singapore Strait to the south and by the narrow Johore Strait in the north from Peninsular . The foremost climatic concern in such a heavily populated city is the heat island effect of the highly urbanized areas (Priyadarsini et al., 2008) and thermal comfort for the inhabitants (Dear et al., 1991).

Secondary data of COVID-19 pandemic for Singapore were gathered from the official website of the Ministry of Health (MOH), Singapore (https://www.moh.gov.sg/). Daily cases of new infections, recovery rate i.e. number of patients discharged from the hospitals, and deaths were obtained for the period from January 23 to May 31 2020, and included in this study.

Daily records of basic meteorological parameters, including maximum temperature (T max ), average temperature (T avg ), minimum temperature (T min ), maximum relative humidity (RH max ), average relative humidity (RH avg ), minimum relative humidity (RH min ), maximum surface pressure (P max ), average surface pressure (P avg ), minimum surface pressure (P min ), maximum dew point (DP max ), average dew point (DP avg ), minimum dew point (DP min ), maximum wind speed (WS max ), average wind speed (WS avg ), and minimum wind speed (WS min ), were obtained from the online database archives of the Weather Underground 

Atmospheric boundary layer height (ABLH), as the level of the maximum vertical gradient of potential temperature (Stull, 1988; Seidel et al., 2010) , over Singapore was estimated using the radiosonde data (at 12 UTC) from the University of Wyoming database archive (Station ID: WSSS; http://weather.uwyo.edu/upperair/sounding.html).

Spearman and Kendall rank correlation tests were used to examine the associations between COVID-19 and meteorological parameters in this current study. Spearman rank correlation, a non-parametric test, measures the strength of association between two variables.

Spearman rank correlation coefficient i.e. Spearman's Rho ( ) can be estimated as following, ∑

where represents the difference between the ranks of two parameters and represents the number of alternatives. The value of = 1 and -1 means a perfect positive and negative correlation, respectively.

Kendall rank correlation, also another non-parametric test, used to measure the ordinal association between two measured variables. Kendall rank correlation coefficient, also called Kendall's tau ( ), is used to evaluate the similarity of the orderings between two datasets and can be used estimated as following (4) where and represents the number of concordant and discordant pairs, respectively. The represents the number of pairs. The value of ranges from -1 to +1 and has a similar interpretation as Spearman's correlation. In this current study, we used XLSTAT software (https://www.xlstat.com/en/) to perform the above-mentioned statistical calculations.

As of May 31, 2020, the reported numbers of total cases, deaths, and recovered with respect to COVID-19 pandemic over Singapore were 34884, 23, and 21699, respectively ( Fig.   2 ). Daily counts of COVID-19 new infection and recovered cases, from January 23 to May 31, 2020, in Singapore are shown in Fig. 3a . The first case of local human-to-human transmission in Singapore was officially reported on February 4, 2020 (https://www.moh.gov.sg/newshighlights). Despite of the enforcement of lockdown in the country to minimize further spread of COVID-19 (https://www.moh.gov.sg/news-highlights/details/circuit-breaker-to-minimisefurther-spread-of-covid-19), data showed a sharp increase in daily new cases from April 7, 2020 onwards to reach the peak on April 23 (Fig. 3a) . However, the recovery rate was found high during May 2020 as compared to previous months (Fig. 3b) .

Daily variations in different meteorological parameters in Singapore are shown in Fig. 3 and their descriptive statistical analyses are presented in Table 1 . T was recorded as high as 34 °C and as low as 24 °C. DP is the temperature to which air must be cooled to become saturated without changing the pressure and this is greatly associated with the human comfort. Over

Singapore, DP avg ranged between 20 °C and 27 °C (Fig. 3c) and indicated the uncomfortable levels and possible heat stress issues for the human in outdoor. RH mainly depends on the temperature and pressure of the environment. It is the ratio of actual WV pressure to the saturation WV pressure at the prevailing temperature. RH was recorded as low as 46% and as high as 100% over Singapore during the study period (Fig. 3d) . Similar to RH, large day-to-day J o u r n a l P r e -p r o o f 11 variations were also seen in cases of AH and WV (Fig. 3e) over Singapore. WS avg ranged between 1.1 and 4.9 m s -1 (Fig. 3f) with the mean value of 2.8 ± 0.9 m s -1 .

ABLH, height of the lowest part of the troposphere that directly feels the effect of the earth's surface, plays an important role in the weather modulation over a region. ABLH depends on several factors such as geographical location, topography, vegetation cover, surface and vertical wind distributions, and urban roughness (Stull, 1988; Garratt, 1992) . The estimated median value of ABLH over Singapore in this study (at 08:00 pm local time) was found to be Lower VC value indicates less dispersion of pollutants in the atmosphere, and vice-versa. The median VC value was found to be 3076 m 2 s -1 over Singapore during the study period ( Table 1) .

High value of kurtosis for WS min , ABLH, and VC may be explained by long periods of low values, followed by short periods of comparatively high values. 

As the first case of local SARS-CoV-2 transmission was reported on February 4, 2020 in Singapore, hence the daily data (both meteorological parameters and COVID-19 cases) from February 4 to May 31, 2020 were used for the statistical analyses. T min , DP max , DP avg , and DP min showed significant positive correlations with new as well as total COVID-19 cases over Singapore (Table 3) . However, T max , T avg , and T min showed relatively strong associations with COVID-19 cases over Singapore during early phase of the transmission (February 4 -April 30, 2020; Supplemental Table S1 ). But, DP max , DP avg , and DP min showed higher associations in case of up-to-date dataset (February 4 to May 31, 2020; Table 3 ) as compared to early phase of the transmission (February 4 -April 30, 2020; Supplemental Table   S1 ). P max , P avg , and P min showed an inverse relationship with COVID-19 cases over Singapore (Table 3) . RH showed weak but positive significant correlation with COVID-19 cases over Singapore ( Table 3) . It is worth to note here that insignificant statistical results were found in case of RH during early phase of the transmission (February 4 -April 30, 2020; Supplemental Table 3 ). Similar to this study, negative correlation between COVID-19 and WS was also reported over Iran (Ahmadi et al., 2020) . However, WS was positively associated with COVID-19 cases over Oslo, Norway (Menebo, 2020) , New York, USA (Bashir et al., 2020) and

Turkey (Sahin et al., 2020) . ABLH and VC also showed the negative association with the COVID-19 cases over Singapore ( Pirouz et al., 2020; Chakraborty and Ghosh, 2020; Petropoulos and Makridakis, 2020; Sardar et al., 2020) . For instance, as DP showed strong positive association with COVID-19 cases in Singapore, hence the local public health authorities may issue high alert to safeguard the vulnerable groups within the population if any atmospheric forecasting model is predicting high DP values for the upcoming months. This kind of initial assessment would probably give rise to hypotheses for further research in epidemiology and pandemic dynamics of COVID-19 in SEA region. This study also has some limitations. Firstly, meteorological parameters were taken from one single site which may affect the statistical analyses. Secondly, as the COVID-19 is J o u r n a l P r e -p r o o f 15 contagious in nature and primarily affected by population genetics, health infrastructure, peoples' obedience to social-distancing and social-isolation, and persons' immunity and tolerance, so more variables are actually needed to conduct a comprehensive study. Thirdly, the data about personal hygiene such as hand washing and the use of sanitizer needs to be investigated more explicitly. Fourthly, subgroup analysis including the gender and age group needs to be done to investigate the sensitive population. Lastly, virus transmission is influenced by population density (Brown et al., 2008) , host behavior, defense mechanisms, and virus infectivity (Cory, 2015) , and environmental determinants (Menebo, 2020) .

This study mainly aims to contribute the community research by investigating the association between COVID-19 and meteorological parameters over Singapore by using statistical approaches. Our results revealed that T and DP have a positive and significant association with the number of daily as well as cumulative COVID-19 cases. SARS-CoV-1 transmission was found to be favored by high RH condition over Singapore. However, the associations of AH and WV with COVID-19 were relatively strong than that of RH. COVID-19

showed anti-correlation with WS, ABLH, and VC. This study provides needful information for the general public and local healthcare policymakers to understand the weather dependency of COVID-19 over Singapore. Further assessments of this kind are required by including large observational dataset of meteorological parameters and air-pollutants from various observation stations across the island to build a complete picture. This study is limited to the presently available facts during this global pandemic and does not claim any potential seasonal pattern for COVID-19 transmission. Active measures should be taken to control the COVID-19

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The authors declare that there is no conflict of interest regarding financial funding and the publication of this paper.