key: cord-318757-po0zpvw5 authors: Beig, Gufran; Bano, S.; Sahu, S.K.; Anand, V.; Korhale, N.; Rathod, A.; Yadav, R.; Mangaraj, P.; Murthy, B.S.; Singh, S.; Shinde, R. title: COVID-19 and Environmental -Weather Markers: Unfolding Baseline Levels and Veracity of Linkages in Tropical India date: 2020-08-22 journal: Environ Res DOI: 10.1016/j.envres.2020.110121 sha: doc_id: 318757 cord_uid: po0zpvw5 The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading across the globe due to its contagion nature. We hereby report the baseline permanent levels of two most toxic air pollutants in top ranked mega cities of India. This could be made possible for the first time due to the unprecedented COVID-19 lockdown emission scenario. The study also unfolds the association of COVID-19 with different environmental and weather markers. Although there are numerous confounding factors for the pandemic, we find a strong association of COVID-19 mortality with baseline PM(2.5) levels (80% correlation) to which the population is chronically exposed and may be considered as one of the critical factors. The COVID-19 morbidity is found to be moderately anti-correlated with maximum temperature during the pandemic period (-56%). Findings although preliminary but provide a first line of information for epidemiologists and may be useful for the development of effective health risk management policies. This research did not receive any specific grant from funding agencies in the public, 23 commercial, or not-for-profit sectors. 24 25 The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 28 (SARS-CoV-2), is rapidly spreading across the globe due to its contagion nature. We hereby 29 report the baseline permanent levels of two most toxic air pollutants in top ranked mega cities 30 of India. This could be made possible for the first time due to the unprecedented COVID-19 31 lockdown emission scenario. The study also unfolds the association of COVID-19 with 32 different environmental and weather markers. Although there are numerous confounding 33 factors for the pandemic, we find a strong association of COVID-19 mortality with baseline 34 PM 2.5 levels (80% correlation) to which the population is chronically exposed and may be 35 considered as one of the critical factors. The COVID-19 morbidity is found to be moderately 36 anti-correlated with maximum temperature during the pandemic period (-56%). Findings 37 although preliminary but provide a first line of information for epidemiologists and may be 38 useful for the development of effective health risk management policies. 39 Introduction: 53 The 90% of people worldwide are exposed to high levels of air pollution as per the World 54 Health Organisation which estimated that around 7 million mortality every year from 55 exposure to fine particles in polluted air. The foul air penetrates deep into the lungs and 56 cardiovascular system, causing diseases including stroke, heart disease, lung cancer, chronic 57 obstructive pulmonary diseases and respiratory infections, including pneumonia (WHO, 58 2018). On every continent, people suffer the negative health impacts of air 59 pollution. However, in recent times, the outbreak of novel coronavirus (COVID-19) has 60 become a global public health challenge and it's ever-increasing in India. The first case 61 of COVID-19 was found in the Wuhan city of China during the month of December and has 62 been spread from Wuhan to the many countries of the world (i.e. Italy, Europe, Asia) within a 63 few months (Bontempi, 2020; Bontempi, et al., 2020) and turned to be a worldwide epidemic. 64 To control the epidemic conditions, the world wide countries went to the lockdown 65 (Muhammad. et al., 2020) . First COVID-19 case in India was confirmed on 30 January, 66 2020, which rose to three cases by 3 rd February. Later, no significant transmissions were 67 observed in February. However, in the beginning of March, 22 cases were identified. In view 68 work reported here focuses on understanding the association of COVID-19 related mortality 127 and morbidity with various other environmental and weather parameters like temperature and 128 long-term ambient levels of pollution in search of an environmental marker which can be 129 considered closely associated with COVID-19. Present work considers 6 major mega cities 130 reported to be pollution hot spots of India, namely, Delhi, Mumbai, Ahmedabad, Pune, 131 Kolkata and Chennai. 132 Material and Method 133 • Study Area: 134 This study focuses on six Indian mega cities as shown in Figure 1 . Delhi is a highly 135 urbanized landlocked city situated at an elevation of 216 m above sea level and covers an 136 area of 1483 sq. km. with a population of about 17 million and it is rapidly growing. Due to 137 the proximity to the Arabian sea Mumbai has a humid weather, Mumbai is at an elevation of 138 about 14 m above sea level and has a population of 12 million and surrounded on 3 sides by 139 ocean. Pune is located in the Western Ghats of Sahyadri mountain range and at 559m above 140 mean sea level with a population of approximately 9 million. Ahmedabad has a tropical 141 semiarid climate located at an elevation of about 53 m above mean sea level having a 142 population of over 5 million. Kolkata is located in the eastern part of India. It has spread 143 linearly along the banks of the Hooghly River. The city is near sea level, with the average 144 elevation being 17 feet. The whole area in the Ganges Delta starts within 100 km south of the 145 city. Most of the city was originally marshy wetlands, remnants of which can still be found 146 especially towards the eastern parts of the city. Kolkata has a subtropical climate with a 147 seasonal regime of monsoons. It is warm year-round, with average high temperatures ranging 148 from about 27°C in December and January to nearly 38°C) in April and May. The 149 atmospheric pollution has greatly increased since the early 1950s. Factories, motor vehicles, India, Chennai is located at 13.04°N 80.17°E on the southeast coast of India. It is located on a 153 flat coastal plain known as the Eastern Coastal Plains. The city has an average elevation of 6 154 meters. Chennai features a tropical wet and dry climate. Chennai lies on the thermal 155 equator and near the coast, which prevents extreme variation in seasonal temperature. Table 1 . The number of patients tested 179 positive for COVID-19 and fatality counts in different Indian cities, considered in this work, 180 are given in Table- The basic dataset of PM 2.5 in the present study was recorded for 1 hr interval and averaging 219 has been done to derive daily data while NO 2 were recorded for 5 min. interval and averaging 220 has been done to derive 24 hr data. The saturation point methodology under fair weather 221 conditions is used in this work to determine the baseline levels of PM 2.5 and NO 2 using the 222 above-mentioned data. The emission inventory of major pollutants in Indian mega cities have Results and Discussion 254 The data thus obtained from the above study design as per the saturation point methodology 255 is shown in Figure S1 from the mean. The correlation between these two parameters are found to be 0.84 (84%) 296 which is found to be significant at 95% confidence level (p-value<0.05) as shown in table shown in the bottom panel as Figure 1c . The highest mortality counts are found in Mumbai 302 where the baseline level of PM 2.5 is highest. The PM 2.5 baseline level and mortality count also 303 indicates significant correlation (r=0.80 with p-value<0.1) at 90% confidence level (Table 2) . 304 These are two most significant correlations found among all the environmental parameters 305 accounted for in the present study and both are associated with PM 2.5 baseline levels. NO 2 , respectively with mortality, morbidity, and standardized mortality rate in various cities 311 accounted for in this work. The calculated correlation coefficient is provided in Table 2 . 312 Although insignificant but relatively higher correlation is noticed between annual mean PM 2.5 313 level and mortality rate (49%), PM 2.5 base level and infection counts (43%), and NO 2 314 baseline levels with mortality and infections counts (42%). Hence, the current study confirms 315 that the COVID-19 in India at present do not have any significant association with prevailing 316 pollution levels, annual pollution levels as shown in Table 2 of later 2 cities are higher than that of Delhi (Table 1) . Present work tends to suggest a 336 significant rise in the fatality in people with underlying conditions because of chronic 337 exposure to baseline air pollution levels rather than averaged ambient air pollution levels for 338 PM 2.5 and shown in Figure 1 To understand the association of COVID-19 with weather and climatological parameters, the 360 correlation study has been done in the present work. Figure S4 shows the correlation plots of 361 COVID-19 related mortality, morbidity, and mortality rate with mean temperature (March-362 May), minimum temperature. The correlation coefficients of all these parameters are shown 363 in Table 2 . In addition to the above, correlation with many other parameters like wind speed 364 and humidity has also been calculated but not shown in Figure. The morbidity and maximum 365 temperature of the day during the pandemic period so far (March to May) in different cities 366 of India are found to be anti-correlated with the correlation coefficient of -0.56 (-56%) as 367 indicated in Table 2 . This result indicates that higher the maximum temperature, probability 368 of infection due to COVID-19 reduces and the population is less susceptible to be infected. 369 However this correlation is not significant even at 90% confidence level. It can be noticed 370 from Table 1 suggested that the respiratory droplets remain suspended for a long time and can make 385 aerosol transmission at low relative humidity. One of the reasons we could not find any 386 significant correlation of COVID-19 with wind speed may be attributed to higher wind speed 387 during summer months in India mega cities as evident from Table 1 . J o u r n a l P r e -p r o o f J o u r n a l P r e -p r o o f HIGHLIGHTS • COVID-19 affinity with environment and weather marker explored in Indian mega cities. • Baseline levels of critical air pollutants unfolded from Covid-19 lockdown. • Strong correlation of COVID-19 deaths and PM2.5 baseline found (80%) but no linkages with ambient pollution levels. • A moderate but significant correlation with maximum temperature is also revealed. • Critical information for epidemiologists for health risk management policies. J o u r n a l P r e -p r o o f ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Can atmospheric pollution be considered a co-424 factor in extremely high level of SARS-CoV-2 lethality in Northern Italy? Factors determining the diffusion of COVID-19 and suggested strategy 427 to prevent future accelerated viral infectivity similar to COVID How High Wind Speed Can Reduce Negative Effects of Confirmed 430 Cases and Total Deaths of COVID-19 Infection in Society Roles of meteorological conditions in COVID-19 transmission on a 434 worldwide scale Air 436 pollution and its effects on the immune system Eosinophilic and neutrophilic sirway inflammation in the phenotyping of mild-to-440 moderate asthma and chronic obstructive pulmonary disease Relationship between global 475 distribution of COVID 19 with environmental and demographic factors: an updated three-476 month study Correlation Coefficients: Appropriate Use and Interpretation Effect of restricted emissions during COVID-19 on air quality in High Resolution emission inventory of NOx and 482 CO for Mega City Delhi More than 90% of the world's children breath 485 toxic air every day