key: cord-0765753-46a2cyy5 authors: Deyal, N.; Tiwari, V.; Bisht, N. title: Impact of climatic parameters on COVID-19 pandemic progression in India: analysis and prediction date: 2020-07-28 journal: nan DOI: 10.1101/2020.07.25.20161919 sha: 4cbc594498130c42d23d99ab2b1740f72c9c7bc6 doc_id: 765753 cord_uid: 46a2cyy5 COVID-19 is spreading rapidly worldwide and various factors of it have to be analysed. We analyze the effect of climatic parameters (Average Temperature (AT), Atmospheric Pressure (AP), Relative Humidity (RH), Solar Radiation (SR) and Wind Speed (WS)) on the COVID-19 epidemic during 25 March 2020 to 15 June 2020 in most affected states of India i.e. Maharashtra, Delhi and Tamilnadu. We quantitatively establish the correlation between these parameters by using Kendall & Spearman rank correlation test. The results indicate that the positive cases are highly correlated with the AT (r^2 >0.6,p<0.001) in Delhi where as a moderate correlation ( r^2<0.6,p<0.001) has been estimated for Maharashtra and Tamilnadu. Similarly, an intermediate range of correlation coefficient has been observed for other climatic parameters. The range of climatic parameters have been found corresponding to maximum number of cases results as AT (25~40 0 C), RH (40~70%), AT (740~965 mmHg), SR (200-250 W/mt2) and WS (.5~14 m/sec). Time series analysis depicts that the positive cases and mortality are increasing rapidly. COVID-19 epidemic peak is predicted and would be appearing October 2020 using SIR model for capital of India (New Delhi). The outcomes of this study will be helpful for the containment of COVID-19 worldwide. COVID-19 has been declared as a worldwide pandemic by World Health organization (WHO) on March 11, 2020 (Cucinotta et al., 2020) . Globally, the first COVID-19 case was reported on December 31, 2019 in Wuhan (China) Li et al., 2020 , Deepak et al., 2020 . At present, it has affected around 80% of world population and still growing at decent rate (https://www.worldometers.info/coronavirus). Investigation on recognized that its transition occurred by respiratory droplets, as well as human to human transition (Ge et al., 2013 , Huang et al., 2020 , Vandini et al., 2013 . The common symptoms of COVID-19 infected patients are fever, cough and respiratory disorders (Holshue et al., 2020) . In worst conditions, it might results as serious health issues like kidney failure, pneumonia which might cause death of patients , Ten et al., 2005 , Perman,2020 . The major concerns about COVID-19 are its tremendously growing cases and vulnerable community transmission in world. In addition, no vaccination of COVID-19 has been officially reported till date. Therefore, adequate precautions and preliminary research work on the factors affecting the spreading of COVID-19 might be helpful for development of vaccination process of Recent studies suggest that the spreading of COVID-19 is highly correlated with the atmospheric factors such as temperature, humidity etc (Ma et al., 2020 , Qi et al.,2020 . It has been reported that abrupt change in climatic conditions and population might be responsible for virus transmission (Rockloy et al., 2020 , Sohrabi et al., 2020 , Dalziel et al.,2018 , Jaiswal et al.,2015 , Hansel eta al., 2016 . Conflictingly, few studies are not accounting meteorological parameters as carriers of transition of COVID-19 (Jamil et al.,2020 , Mollalo et al.,2020 . Another study indicates that the temperature, humidity can be responsible of transmission and existence of SARS-COV virus [(Bashir et al., 2020 b, Tan et al., 2020 , Yuan et al., 2020 . However, limited studies have been carried out in context of COVID-19 and climatic factors. Tosepu et al. have studied the correlation between weather and COVID-19 in Jakarta (Indonesia) in earliest stage of COVID-19 (Tosepu et al,. 2020 ). Further, it is expected that this correlation also depends on geographical conditions of study area. So far, such reported studies are only limited to European countries ( Briz et al., 2020 , Sajadi et al., 2020 . To best of author's knowledge, no such study has been carried out for south Asian countries till date. In this paper, we study the effects of varying climatic parameters (CPs) on the spread of COVID-19 from 15 March 2020 to 15 June 2020 in India. The aim of this study is to analyse journey of COVID-19 in India and forecast the effect of COVID-19 on climatic conditions in subsequent times. Moreover, to obtain detailed analysis of the COVID-19, we have emphasized our study to three most COVD-19 affected states of India i.e. Maharashtra, Tamilnadu and Delhi. In addition, the strategies such as nationwide lockdown implemented by Indian government to reduce COVID-19 spreading have been quantitatively evaluated in climatic framework. In India, the first confirmed COVID-19 case was reported in Kerala on January 30, 2020 (https://www.mohfw.gov.in). The total confirmed cases has been raised up to 3,54,065 within five months in India, which is the highest number of confirmed COVID-19 cases in Asia and fourth highest in world as on 15 June 2020 ( https://www.worldometers.info/coronavirus). It implies that COVID-19 is drastically spreading among 1.3 billions of people in India. Out of the total confirmed cases, 1, 86,935 patients have been recovered and total 11,900 deaths in country till mid June 2020 (https://www.covid19india.org). As anticipation, nationwide lockdown was imposed by Indian government in five phases. During this lockdown period, all social activities like transport, industries, shopping malls etc. had been strictly prohibited in India. The population of these states are 1.8x10 7 , 1.23x10 8 and 7.7x10 7 respectively as on 2019 (Census 2011; http://census2011.co.in). Most importantly, these three are most affected states of India from COVID-19 as on mid June 2020. The digital dataset for the COVID-19 in India has been obtained from Ministry of Health and The spatial distribution of COVID -19 parameters (Positive cases (PC), recovery and Death(DT)) during the lockdown in India is shown in fig.2 . The whole lockdown period has been categorized in two phases i.e. period-I (from 25 March 2020 to 3 May 2020) and period-II (from 4 May to 15 June). Fig. 2 clearly indicates that Delhi, Maharashtra and Tamil Nadu are the most affected states of India from COVID-19 pandemic till mid June 2020. The additional details of COVID-19 parameters during the different lockdown phases are mentioned in (Table. 1). On observing table.1 carefully, it is clear that PC and mortality increases rapidly all over India during lockdown period. One more important observation is that the cases are still increases as on June 2020 and the saturation state of COVID-19 cases still not achieved in India. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. The variation in CPs (24hrs average value) of during the period of three months (25 th April to 15 th June) has been observed for previous three years (2018-2020) for three states of India i.e. Maharashtra, Delhi and Tamilnadu illustrated in fig.3 (a) ,(b),(c). We have observed similar trends in 2020 as compared to 2018 and 2019. However, a unique quantitative variation in CPs has been noticed for year 2020. AT significantly reduces with respect to previous years in the range of (5.2% ~ 10.4%). Moreover, the RH represents ascending trend in all three years with All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. . https://doi.org/10.1101/2020.07.25.20161919 doi: medRxiv preprint relative difference (2.4% to 40%). It is an intuition that this variation is correlated with the COVID-19 pandemic up to some extent. Moreover, the study of variation of CPs has been carried out during lockdown period in Maharashtra, Delhi and Tamilnadu. Corresponding parameters have been tabulated in (Table. 2). It depicts that the implementation of lockdown is a factor for considerable variations in CPs and air quality. (Table. 3). It was observed that number of (PC) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. . https://doi.org/10.1101/2020.07.25.20161919 doi: medRxiv preprint was highly correlated with AT for Delhi whereas moderate correlation is observed for Tamil Nadu and Maharashtra with significant level of (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. . https://doi.org/10.1101/2020.07.25.20161919 doi: medRxiv preprint were found very significant with in India. It is further observed that the mortality rate is growing with time. The CPs were shows a moderate correlation with DT. To have more clear insight, the scattered correlation matrices of CPs and COVID-19 parameters for Delhi, Maharashtra and Tamil Nadu shown in fig. 4(a) , 4(b) and 4(c). It is observed that the maximum PC have been reported within the AT range (25~40 0 C). Similarly, the most frequent ranges for other CPs corresponding to most number of PC are 40~70%, 740~965 mmHg and 200~250 W/mt 2 for RH, AP, SR respectively. Particularly, a wide range for WS (.5~ 14 m/sec) has been calculated for having maximum no. of PC from Delhi to Tamilnadu and varying with latitude. In lower latitude the no. of PC are high within the range of WS (10~14 m/sec) although for northern region at higher latitude, it is observed (.5~1.5 m/sec). This lead to conclude that the areas experience such climatically condition have been mostly affected by COVID-19. show critical correlation with transmission of COVID-19 in India with 0.1% of significance All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. has the potential to enhance the current understanding of COVID-19 spreading and will help for the advancement of vaccination process of COVID-19. More over this study indicates that the COVID-19 containment policy i.e. lockdown adapted across the globe leads to reduced pollution level, improve climatic conditions in last few months. Such exceptional change has never been observed in nature before in short time duration. Therefore, such activity in future would be effective in sustainable development of nature. Ahmadi, M., Sharifi, A., Dorosti, S., Jafarzadeh Ghoushchi, S., Ghanbari, N. 2020. Investigation of effective climatology parameters on COVID-19 outbreak in Iran. Science of The Total All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 28, 2020. . https://doi.org/10.1101/2020.07.25.20161919 doi: medRxiv preprint Roles of climaticconditions in COVID-19 transmission on a worldwide scale WHO declares COVID-19 a pandemic Urbanization and humidity shape the intensity of influenza epidemics in U Cardiac and Other Clinical Manifestations and Potential Therapeutic Strategies. JACC; Basic to Translational science Assessing Homogeneity and Climate Variability of Temperature and Precipitation. Series in the Capitals of North-Eastern Brazil Clinical features of patients infected with 2019 novel coronavirus in Wuhan First case of 2019 novel coronavirus in the United States Statistical Analysis for Change Detection and Trend Assessment in Climatological Parameters No Evidence for Temperature-Dependence of the COVID-19 Epidemic Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia Correlation between climate indicator and COVID-19 pandemic GIS-based spatial modeling of COVID-19 incidence rate in the continental United States Another decade, another coronavirus Seasonal Influences on the Spread of SARS-CoV-2 (COVID19), Causality, and Forecastabililty (3-15-2020). Causality, and Forecastabililty (3-15-2020) COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis 2020. Correlation between weather and Covid-19 pandemic in Jakarta High population density catalysis the spreed of COVID-19 The impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak evidence from China. medRxiv Impact of climaticfactors on the COVID-19 transmission: A multi-city study in China All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder World Health Organization declares global emergency: a revie w of the 2019 novel coronavirus (COVID-19) An initial investigation of the association between the SARS outbreak and weather: with the view of the environmental temperature and its variation Respiratory syncytial virus infection in infants and correlation with climaticfactors and air pollutants Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID-19) imp licate special control measures From MathWorld--A Wolfram Web A climatologic investigation of the SARS-CoV outbreak in Beijing, China A novel coronavirus from patients with pneumonia in China Coronavirus disease All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted July 28, 2020. . https://doi.org/10.1101/2020.07.25.20161919 doi: medRxiv preprint