COVID-19 pandemic in India: Chronological comparison of the regional heterogeneity in the pandemic progression and gaps in mitigation strategies

COVID-19 pandemic in India: Chronological comparison of the regional heterogeneity in the pandemic progression and gaps in mitigation strategies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review COVID-19 pandemic in India: Chronological comparison of the regional heterogeneity in the pandemic progression and gaps in mitigation strategies Satabdi Datta, Neloy Kumar Chakroborty, Deepinder Sharda, Komal Attri, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-666506/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract The second wave of COVID-19 exerted more catastrophe in India than the first. The progressions of both waves were heterogeneous in the six different regions involving 28 states and 8 union territories. An analysis of the temporal variations in new cases and fatalities in all the states of India was done for both the 1st (30th January 2020 to 31st January 2021) and 2nd wave (1st February 2021 to 29th May 2021), which showed that India accounted for over 16% and 9% of the cases and fatalities of the world respectively. The Southern and Western regions remained the top contributor of cases and fatalities in both waves. The state of Punjab and Maharashtra reported the highest CFR (3.24 and 2.5 respectively) in the country during the 1st wave, and in the second wave, Andaman & Nicobar Islands (2.6), and Punjab (2.25) reported the highest CFR. The states of Goa and Delhi showed the highest CCR and CDR during the 1st wave respectively, whereas Lakshadweep and Goa reported the highest CCR and CDR respectively in the 2nd wave. The study comprehends the severity of the second wave over all the states of the country and highlights the major hotspots regions and some gaps in mitigation strategies. Epidemiology COVID-19 first wave second wave India regional heterogeneity cases fatality hotspots mitigation strategies Figures Figure 1 Figure 2 Figure 3 Introduction India is currently the second-largest contributor of total COVID-19 cases of the world, accounting for about 16% of the total cases and around 9% of deaths worldwide 1 . The Indian subcontinent reported its first case of COVID-19 on January 30th, 2020 2 from Kasargod district in the state of Kerala. However, most of the other states reported their first cases in March 2020, and during this period the number of active cases started to amplify at a rapid pace. Amid this crisis, the government of India announced a nationwide lockdown with implementations of public health and social measures 3 , but in spite of such stringent measures, the cases in India showed a steady acceleration in numbers, particularly aggravated after the unlock phase 1 from 31st May, 2020. In most of the states, the surges in cases were visualized from the beginning of June 2020, which reached their respective maxima in the middle of September, 2020 4 . The first wave however subsided towards the end of January 2021 with only about 1.5 lakhs active cases and a much lower test positivity rate in the whole subcontinent 5 . This led to the withdrawal of many restrictions on social and political gatherings, albeit the consequence of these measures turned out to be catastrophic soon afterward 6 . Towards the beginning of March 2021, the number of infections began to soar, which marked the beginning of the catastrophic second wave of COVID-19 pandemic that overwhelmed the medical facilities of most of the states and compelled the state governments to implement lockdown-like restrictions 7 . The emergence of new indigenous mutants of the SARS-CoV-2 virus along with other international mutants was accessed as one of the major reasons for such a surge in cases 8 , 9 and fatalities in the second wave of the pandemic. The Indian subcontinent is characterized by diverse geographical and demographical regions, populated by heterogeneous cultural, political, linguistic, and ethnic groups of people 10 , 11 , 12 , covering an area of 3.28 million square kilometers with a total population of about 138 cores 13 , 14 . Thus the progression pattern of the pandemic was also turned out to be heterogeneous in each region of the country, which therefore demands the analysis of chronological heterogeneity in the regional and state-specific infection rates, death rates, wave patterns, and testing capacities for a clear interpretation of the progression patterns of the wave across the country. In this study, we did a comprehensive analysis of the chronological changes in the first and the second-wave patterns of the pandemic in each region of the country and its respective states. India comprises 28 states and 8 unions territories 15 , divided along 6 administrative subdivisions, 14 the Northern region(NR), Central region(CR), Western Region (WR), Eastern (ER), North Eastern Region (NER) and Southern region (SR), Indian states (Table-1,2). The analyses of the progression patterns of the two waves across these different subdivisions and their respective states are a significant step forward to evaluate the real scenario of the COVID-19 situation across the nation as well as the pandemic mitigation strategies. Methods Study design and data sources A detailed study of the COVID-19 infections and their related statistics in India was done between January 2020 to May 29th, 2021. The days of first reported infection, rising(10% consistent increase in active cases) and declining phases of the two respective pandemic waves, wave’s peak, numbers of new infections, death, recoveries along with the testing and demographical data for all the 6 administrative regions comprising of 28 states and 8 union territories of the country, were obtained from the online monitoring official website of the Government of India 4 and other government and international websites. 16 The pandemic wave or phase was defined as a rising number of COVID-19 cases with a definite peak, which was followed by a declining number of cases, or the trough period, where the rates of new infections and active cases have declined significantly. The day reporting the highest number of active cases was defined as the peak of the wave. The number of monthly new cases, recoveries, and deaths for each state were calculated, the chronological (monthly) contribution of new cases, deaths, and recoveries of each administrative region of the subcontinent, was calculated by summing up the respective values of the aforesaid parameters of all the states and union territories of the concerned region. Statistical Analysis CCR, cases per 1 lakh or 100000 populations; CDR, deaths per 100000 populations], CFR; the number of deaths reported per number of cases reported × 100), tests per case (total tests: total case) ratio for both the first (30th January 2020–31st January 2021) and second waves (early February 2021 till 29th May, 2021) of the pandemic were calculated. The weekly-average numbers of confirmed cases, active cases, and deaths were quantified by estimating the changes in numbers from one day to the other day average over the span of a week. The fold changes, for the Kumbh Mela 2021, were calculated by dividing the weekly-average numbers of the later week (3rd May – 9th May 2021) by the earlier week (1st March – 7th March, 2021). The fold changes in average daily new cases for each month [before LAE (march-21), during LAE (April-21), and after LAE (May-21)] for the 5 States which underwent elections were calculated and compared with 5 states (a major contributor of cases) that had no major public gathering events. Results A chronological overview of the contributions of different regions of India towards the cases and fatalities in the two waves The chronological variations in the number of new cases and new deaths in India (Fig. 1 A and 1 B) and the contributions of different regions of the country towards the total cases and fatalities of the nation are noteworthy (Fig. 1 E and 1 F). At the beginning of the 1st wave, the SR accounted for nearly 40% of total cases in March 2020 (Fig. 1 C). From April, 2020 till June 2020, the WR remained the major contributor of COVID-19 cases, (43%, 46%, and 31% of the total cases in the respective months). Subsequently from June 2020, when the first phase of unlocking (unlock-1) started in the country (Fig. 1 A), till the end of October 2020, the SR contributed 41%, 40%, 34%, and 41% of the total COVID-19 cases of the country in the respective months (Fig. 1 C). Only in November 2020, the NR became the highest contributor of new cases (31%), however from December 2020 till February 2021 (in the declining phase of 1st wave), SR contributed 31%, 47% and 43% of the total cases in the subsequent months(Fig. 1 C). At the beginning of the rising phase of the second wave, from March 2021 till April, 2021, the WR contributed about 63%, and 30% of the nations’ total cases respectively. In May 2021, the SR once again turned out to be the major contributor of new cases in the country (42%) (Fig. 1 C). In terms of fatality, the WR accounted for the highest monthly fatality from March 2020 till October 2020 (contributed nearly 35%, 59%, 62%, 51%, 41%, 37%, 39%, and 31% of total monthly deaths of the nation respectively) (Fig. 1 D). The NR contribute over 33% and 31% of total fatality in November and December 2020. The WR was the highest monthly contributor of COVID-19 related fatality from January 2021 till April, 2021(30%, 40%, 39%, and 33% of total fatality). However, in May 2021, the SR accounted for the maximum proportion of fatality of the country (28%) (Fig. 1 D). Thus, it can be inferred from these results that both the Western and Southern Indian states have been the major hotspots of the COVID-19 pandemic in the Indian subcontinent (Fig. 1 E, F) The first wave of COVID-19 in India – A detailed analysis Apart from Kerala, most of the Indian states reported their first infection in March or April 2020. The Government of India has implemented a nationwide complete lockdown protocol from 25th March 2020 to combat the spread, like many other nations. A continuous lockdown was applied, in four phases, until 31st May 2020. The unlock process, implemented in six phases, commenced from 1st June, 2020 to 30th November, 2020. 17 The daily-cases though began to surge steadily, especially from the end of May 2020 (just before the beginning of the 1st phase of unlock) to September 2020 in the majority of the states (Table-1). The adverse effects of unlocking can be understood from the following statistics – from the week, before the last week of lockdown (18th May 2020 to 24th May 2020) to the week, after one continuous week of unlock (8th June 2020 to 14th June 2020), the change in weekly-average numbers of new confirmed cases, active cases, and deaths respectively showed increases from 6369 to 11170 (1.75-fold), from 3153 to 4048 (1.28-fold), and from 144 to 340 (2.35-fold) (analysis not shown). India reported the maximum number of daily new cases on 16th September 2020 (around 98,000) and maximum active cases on 17th September 2020 (1018454), which was marked as the peak of the wave. Subsequently, both the figures of daily and active cases started to drop steadily in the following weeks, till the end of January 2021, when the number of daily cases reduced to around 10,000 cases/day; marking the trough of the wave. Among the 10758629 cases reported during the first wave, the highest number of cases was reported from the SR (3933360) which contributed to 36.5% of the total cases. The top contributor state from the SR was Karnataka (about 8.7%), followed by others (Table-1). Lakshadweep islands, which happened to be the last area of SI to report its first infection have contributed minimum to the nation’s total cases (0.0008%). The WR comes next, which contributed 21.6% of the nation’s total cases, where the top contributor state was Maharashtra (reported 2026399 cases, ~ 18.8%). States of the NR, coming next, accounted for about 16.4% of total cases were the highest contributor was the national capital, Delhi (5.9%). The ER shared 11.8% of the nation’s total cases, where West Bengal contributed mostly (~ 5.3%). The CR of India produced 10.7% of the total cases, where Uttar Pradesh (5.5%) was a major contributor. The NER was the lowest contributor of cases and deaths and accounted for only 3% of the total cases of the first wave where Assam shared for the majority of cases (2%), whereas the other 7 states altogether accounted only for 1% of the cases (Table-1). The dates, representing the peaks of active COVID-19 cases, varied for the states and UTs (Table-1). The CCR (number of cases/1 lakh of the population) was found to be highest in Ladakh (3352 cases/1 lakh) followed by Delhi (3175) and Chandigarh (1773) from the NR. The other states and union territories which reported a case/1 lakh ratio of more than 1000 are Uttar Pradesh (2668) and Chattisgarh (1053) from the CR, Goa (3468) and Maharashtra (1661) from the WR, and Andhra Pradesh (1707), Karnataka (1423), Kerala (2655), Telangana (1103), and Puducherry (2605) from the SR (Table-1). In addition to contributing the second-highest number of COVID-19 cases, states of the WR also contributed the maximum number of deaths (accounted for 36.4% of the total deaths of the country) during the first wave out of a total of 154428 deaths nationwide. The state of Maharashtra accounted for the most number of deaths in the region (33%), followed by Gujarat (2.8%) and Goa (0.5%). The trend remained similar for the SR, which in line with its highest contribution to the number of cases, also accounted for 24.4% of the total deaths of the nation, where Karnataka (8%) and Tamil Nadu (8%) were the two major contributors (Table-1). Contribution from the Northern states were about 17.7% to the total number of fatalities of where Delhi was the major contributor (7%), followed by other states (Table-1). The CR, in this regard, accounted for 10.5% of the total deaths, where Uttar Pradesh (5.6%) reported the maximum number of deaths (Table-1). Among the 9.5% of the total deaths, contributed by the ER, West Bengal (6.6%) was the major contributor (Table-1). The NER states reported the least mortality and contributed only about 1.51% of the total deaths of the nation (Table-1). The highest CDR was however reported by the national capital, Delhi (54 per 100000 population), followed by Goa (50), Ladakh (45), and Maharashtra (42) (Table-1). The CFR was found to be highest in the state of Punjab (3.24) in the NR, followed by Maharashtra (2.5) in the WR with Sikkim (2.18) stands next from the NER. The state of West Bengal (1.785) accounted for the highest CFR from the ER, followed by Uttarakhand (1.71), Delhi (1.71) and Himachal Pradesh (1.69) from the NR. Among the states of Southern India, Puducherry (1.66) recorded the highest CFR (Table-1). Regarding the testing of cases, until the end of January 2021, more than 22.84 crores (1 crore = 10 million) COVID-19 tests were performed all over India, of which the national capital, Delhi (4.81%) recorded the highest percentage from the NR, Uttar Pradesh (12.26%)tops the list from the CR, Maharashtra (6.57%) from the WR, Bihar (9.19%)from the ER, Andhra Pradesh (7.88%) from the SR, and Assam (2.83%) from the NER. The WHO has recommended an optimum of 30, test per case ratio (T: C), as standard; however apart from the states, like Jammu and Kashmir (36.5), Uttar Pradesh (46.6), Gujarat (42.1), Bihar (80.5), Jharkhand (44), Mizoram (48), and Andaman and Nicobar islands (44), all other states and union territories had a T: C ratio less than the WHO recommended mark of 30 tests/case 18 . (Table-1). The second wave of COVID-19 in India – A detailed analysis The period between the end of February, 2021 and early March, 2021, marked the rising phase of the catastrophic second wave of the COVID-19 pandemic in India. During this period, the country reported more than 3 lakhs new cases/day in April that soared to over 4 lakhs cases/day and over 4000 daily deaths in the first week of May, 2021, overburdening the healthcare system of the country. On 6th May, India reported its highest number of over 414280 new cases, which marked the peak of the wave until now. Thereafter, the daily cases started to dip gradually, however the fatality rate remained high. Starting from 1st February till the 29th May, 2021, India reported a total number of 17134975 cases and over 1.7 lakh deaths. Until 29th May, 2021, the SR remained the top contributor of cases (32%) and the third major contributor of fatalities (22%), where the state of Karnataka (9.5%) and Kerala (9.1%) together accounted for more than half of the total cases of theregion, and again Karnataka (9.3%) and Tamil Nadu (6.3%), like in the first wave, were also the major contributors to the nation’s fatalities (Table-2). Until 29th May, the WR contributed over 25% and 29% of the COVID-19 related cases and fatalities respectively, where Maharashtra was major contributor (21% and 25% of the cases and deaths). The NR contributed about 16% and 27% of the total cases and fatalities respectively, where Delhi, was the major contributor (4.6% and7.7% of cases and fatality respectively). The CR accounted for about 13% and 14.5% of cases and deaths respectively, where Uttar Pradesh was major contributor (6.3% and 6.7% of cases and fatalities respectively). The ER contributed around 10.8% and 7.7 % cases and fatalities of the country respectively where West Bengal is the highest contributor (10.8% and 7.7% of total cases and fatalities respectively). The NER reported the least number of cases (1.63%) and fatalities (2%) in the country, where the major contributor was Assam (over 1% and 1.2% of the cases and fatalities respectively) (Table-2). Until 29th May, 2021, the highest CFR was reported by Andaman and Nicobar Islands (2.59) where 51 deaths were reported out of 1970 cases, followed by Punjab (2.23) from the NR and Nagaland (2.22) from the NER. The highest number of CDR was found for Goa (118 deaths/1 lakh), followed by Uttar Pradesh (51), and Lakshadweep islands (45). Lakshadweep was also found to contribute highest to the CCR (11084 cases/1lakh), followed by Uttar Pradesh (4835) and Chandigarh (3289). It is noteworthy that apart from Andaman and Nicobar Islands (86 tests/case), Himachal Pradesh (49), and Ladakh (29), the other states and union territories were lagging behind the recommended WHO level 18 . One of the major contrast between the first and second wave is the evolution of new variants of the novel SARS-CoV-2 virus during the second wave which triggered a sudden surge in cases in most regions of the country. The three imported viral variants of concern that have been identified in India are the UK (B.1.1.7) variant, the South African (B.1.351) variant and the Brazilian (P1) variant, among which the B.1.1.7 variant was predominantly present in Delhi and Punjab in April, 2021. Among the two novel variants of India, the highly contagious B.1.617 variant from Maharashtra has started evolving rapidly and overtook the B.1.618 variant in West Bengal, and eventually became the major variant in most of the states. The WHO has already designated the B.1.617 variant as ‘variant of concern’ in May, 2021. This variant has spread in all states across the nation and is identified as one of the major causes of the calamity associated with the second wave of COVID-19 in India (especially in Delhi, Andhra Pradesh, Gujarat, Maharashtra and Odisha), as per the study conducted by the Indian SARS-CoV-2 Genomics Consortium (INSACOG), which was launched by the Ministry of Health and Family Welfare, Govt. of India, on 30th December, 2020. 19 , 20 Roles of some major mass-scale public gatherings in the second wave Mass scale public gatherings like Kumbh Mela 2021 (9 million participants), state elections (covering 243 million residents) have contributed in faster and elevated spreading of the second wave. 21 , 22 A 117-foldincrease in the number of weekly-average new cases and a 266-fold increase in the weekly-average new deaths were found for the state of Uttarakhand when we compared the data between before and after the festival. Uttar Pradesh, like Uttarakhand also showed a sharp jump in the weekly-average new cases and deaths – respectively a 240-fold and 201-fold increase in the numbers of weekly-average new cases and deaths (Table S1 and Fig. S1). These numbers are much higher than the fold-increase found for the cases (20.9-fold) and deaths (35.4-fold) for the entire nation (except these two states) between the mentioned weeks. Five states Assam, Kerala, Puducherry (UT), Tamil Nadu, and West Bengal that witnessed their ‘legislative assembly elections’ (LAE) from late March to end of April 2021 also reported a substantial increase in the average daily cases after the elections compared to some of the states with no LAE or major public gatherings (Fig-S2, Table S2); mainly attributed to the election-related rallies and mass-scale public meetings organized by the local political parties 23 . However, it is noteworthy that dissecting out the exact contributions of such gatherings from the general increase in the numbers of cases and deaths due to aggravation of the pandemic itself is out of scope. Discussion The second wave of COVID-19 pandemic resulted in total disarrays in all states of the country; an escalation of the infections in such a large magnitude was never expected. While the first wave caused a little over 1.08 crore infections and over 1.5 lakhs fatality in the whole country within a period of 11 months, the ongoing second wave resulted in over 1.7 crore infections and nearly 2 lakhs fatalities in a span of merely 4 months resulting in an unprecedented chaos in the supplies of life-saving drugs and oxygen together with non-availability of hospital beds in most of the parts of the country 24 . The average daily new cases during April 2021 was around 2.31 lakhs cases/day which soared to about 3.01 lakhs cases/day in May 2021, which is nearly 2.7 and 3.5 times of the average daily cases (87,000 cases/day) of September 2020 (when India reported its peak of the first wave). The CCR and CDR for the second wave were also found to elevate substantially in comparison to the first wave (Fig. 2 A and 2 B), which comprehend the high rate of infection and fatalities in the country. However, the CFR for both the waves did not show significant variation for the majority of the states to date (Table-1 and 2), which is most likely due to the similar death rates of all existing variants of the SARS-CoV-2 virus in India. Thus, the total numbers of infection and death have together increased during the second wave without changing the CFR. The advent of new and more infectious variants of the virus, inaccuracy in diagnosis, lack of testing, non-transparency in data sharing, low rate of vaccination, decreased rate of genome sequencing of the COVID-19 positive samples along with unchecked social, religious (like Kumbh Mela 2021), and political gatherings (legislative assembly general elections) towards the beginning of the year, and the serious lack of COVID-19 mitigation measures, despite previous warnings, were held responsible for this unprecedented escalation of the pandemic in the country by many reports 25 , 26 , 27 . Despite an increase in daily test numbers, the test/case ratio has dropped in the majority of the states in the second wave. Thus, the need of the hour is to accelerate the testing rates both in the rural and urban regions of the nation to get a clear picture of the infection scenario 28 that may aid to avert the nucleation of another catastrophic wave of the pandemic 29 . A comprehensive evaluation of the available data specifically reveals that the SR and WR were the major hotspots of the pandemic in both waves. The states of Karnataka and Tamil Nadu from the SR and Maharashtra from the WR showed consistently high numbers of infections and fatalities in both waves. Irrespective of the presence of the highly infectious B.1.617 Indian variant of the SARS-CoV-2 in these states during the second wave, these results are indicative of shortfalls in the health systems and/or deficits in implementations of COVID-19 restriction protocols in the populations. Although the data on demographical differences in infection are not made available to the public by the Ministry of Health and Family Welfare, Govt. of India, however, many recent reports suggest that a notable difference between the first and second waves in the country are that the second wave affected a large portion of the pediatric group, which was largely asymptomatic in the first wave 30 . As of the first week of April 2021, it was reported that over 79,000 children were affected by the disease from five states that include Maharashtra, Chattisgarh, Karnataka, Uttar Pradesh, and Delhi between 1st March to 4th April 2021, of which over 60,000 cases were from Maharashtra 31 , however, the cases of hospitalization among the children were only a handful. Trends suggests that the average gaps between the peaks of the first and second wave in majority of countries were around 5 months 32 , in India it was about 7.5 months, however, the escalation of the 2nd peak height was far higher in this country. At present, the second wave is on its declining phase for the majority of Indian states; however experts suggests that unless vaccination rate is accelerated, the country is set to face another 3rd wave by the end of this year 33 , 34 which may largely affect the unvaccinated population especially the paediatric group in large numbers 35 , as trends suggests each subsequent waves have been more severe than the previous one in most of the countries that have already faced the third wave 36 , therefore ramping up of the clinical trials of a vaccine for the paediatric group, rapid vaccination of the adults 37 together with the strengthening of the health infrastructure of the nation, wide-scale genomic sequencing of positive samples, monitoring weekly trends in the test positivity rates’ strict implementation of COVID-19 appropriate restrictions and behaviour in public, are the urgent needs of the hour to protect the future of the country and its people from another COVID-19 tsunami. Declarations Conflict of interests The authors declare no conflict of interests Acknowledgement SD (CSIR-RA) is thankful to Council of Scientific and Industrial Research, Government of India for Post-doctoral Research Associateship fellowship [award no. 09/677(0055)/2020-EMR-I]. KA and DC are thankful to TIET-VT-CEEMS for research fellowship respectively. NKC is thankful to Thapar School of Liberal Arts & Sciences for the Director’s Discretionary fellowship. References COVID Live Update: 172,963,233 Cases and 3,718,849 Deaths from the Coronavirus - Worldometer. https://www.worldometers.info/coronavirus/ (accessed June 4, 2021). Andrews MA, Areekal B, Rajesh K, et al. First confirmed case of COVID-19 infection in India: A case report. Indian J. Med. Res. 2020; 151 : 490–2. PM Modi announces 21-day lockdown as COVID-19 toll touches 12 - The Hindu. https://www.thehindu.com/news/national/pm-announces-21-day-lockdown-as-covid-19-toll-touches-10/article31156691.ece (accessed June 4, 2021). Coronavirus Outbreak in India - covid19india.org. https://www.covid19india.org/ (accessed June 4, 2021). Coronavirus live | Consistent fall in India’s active caseload due to decline in daily infections: Health ministry - The Hindu. https://www.thehindu.com/news/national/coronavirus-updates-january-4-2021/article33490697.ece (accessed June 4, 2021). Coronavirus: WHO says religious, political gatherings contributed to India’s surge in cases. https://scroll.in/latest/994785/covid-19-religious-and-political-gatherings-contributed-to-surge-in-cases-in-india-says-who (accessed June 4, 2021). Covid-19 surge in India: These states impose complete lockdown to curb spread. Full list here. https://www.livemint.com/news/india/covid19-surge-in-india-these-states-impose-complete-lockdown-to-curb-spread-full-list-here-11620476971862.html (accessed June 4, 2021). The Novel Coronavirus Variants and India’s Uncertain Future - The Wire Science. https://science.thewire.in/health/sars-cov-2-variants-b117-b1617-india-second-wave-uncertain-future/ (accessed June 4, 2021). ‘Two variants responsible for second wave’ - The Sunday Guardian Live. https://www.sundayguardianlive.com/news/two-variants-responsible-second-wave (accessed June 4, 2021). Mastana SS. Unity in diversity: An overview of the genomic anthropology of India. Ann. Hum. Biol. 2014; 41 : 287–99. Majumder PP, Basu A. A genomic view of the peopling and population structure of India. Cold Spring Harb Perspect Biol 2015; 7 . DOI: 10.1101/cshperspect.a008540 . Geography of India. https://www.cs.mcgill.ca/~rwest/wikispeedia/wpcd/wp/g/Geography_of_India.htm (accessed June 4, 2021). - Statistical Year Book India 2016 | Ministry of Statistics and Program Implementation | Government Of India. http://www.mospi.nic.in/statistical-year-book-india/2016/171 ) ( https://en.wikipedia.org/wiki/India (accessed June 4, 2021). Administrative divisions of India - Wikipedia. https://en.wikipedia.org/wiki/Administrative_divisions_of_India (accessed June 4, 2021). States Uts - Know India: National Portal of India. https://knowindia.gov.in/states-uts/ (accessed June 4, 2021). India COVID: 28,574,350 Cases and 340,719 Deaths - Worldometer. https://www.worldometers.info/coronavirus/country/india/ (accessed June 4, 2021). Lockdown Unlock in India COVID19 pandemic guidelines restrictions 2020 coronavirus lockdown series | India News – India TV. https://www.indiatvnews.com/news/india/lockdown-unlock-in-india-covid19-pandemic-guidelines-restrictions-2020-coronavirus-lockdown-series-674925 (accessed June 12, 2021). (No Title). https://www.who.int/docs/default-source/coronaviruse/transcripts/who-audio-emergencies-coronavirus-press-conference-full-30mar2020 .pdf?sfvrsn=6b68bc4a_2 (accessed June 4, 2021). Indian SARS-CoV-2 Genomics Consortium (INSACOG).. (No Title). https://media.nature.com/original/magazine-assets/d41586-021-01274-7/d41586-021-01274-7.pdf (accessed June 12, 2021). Kumbh Mela and election rallies: How two super spreader events have contributed to India’s massive second wave of COVID-19 cases-India News, Firstpost. https://www.firstpost.com/india/kumbh-mela-and-election-rallies-how-two-super-spreader-events-have-contributed-to-indias-massive-second-wave-of-covid-19-cases-9539551.html (accessed June 12, 2021). 9.1 million thronged Mahakumbh despite Covid-19 surge: Govt data - Hindustan Times. https://www.hindustantimes.com/cities/dehradun-news/91-million-thronged-mahakumbh-despite-covid-19-surge-govt-data-101619729096750.html (accessed June 12, 2021). India Covid crisis: Did election rallies help spread virus? - BBC News. https://www.bbc.com/news/56858980 (accessed June 12, 2021). The Oxygen Crisis in Second Wave Covid-19 Pandemic in India and “We the People” | Vivekananda International Foundation. https://www.vifindia.org/article/2021/may/03/the-oxygen-crisis-in-second-wave-covid-19-pandemic-in-india-and-we-the-people (accessed June 4, 2021). Fukase K, Kato M, Kikuchi S, et al. Effect of eradication of Helicobacter pylori on incidence of metachronous gastric carcinoma after endoscopic resection of early gastric cancer: an open-label, randomised controlled trial. Lancet 2008; 372 : 392–7. India wasted its early successes in managing Covid-19, PM Modi’s actions ‘inexcusable’: Lancet - Coronavirus Outbreak News. https://www.indiatoday.in/coronavirus-outbreak/story/india-wasted-early-successes-in-managing-covid19-pm-modi-actions-inexcusable-vaccination-drive-botched-lancet-1800465 -2021-05-09 (accessed June 4, 2021). India Covid: Kumbh Mela pilgrims turn into super-spreaders - BBC News. https://www.bbc.com/news/world-asia-india-57005563 (accessed June 12, 2021). Fewer Tests Could Be Why India’s COVID-19 Numbers Have Declined Since May 1 - The Wire Science. https://science.thewire.in/health/testing-covid-19-india-numbers-may-1-vaccine-decline/ (accessed June 4, 2021). India’s COVID-19 Testing Capacity Must Grow by a Factor of 10: Here’s How That Can Happen | Center For Global Development. https://www.cgdev.org/publication/indias-covid-19-testing-capacity-must-grow-factor-10-heres-how-can-happen (accessed June 4, 2021). More children infected in second wave, but no need for panic: Experts | Business Standard News. https://www.business-standard.com/article/current-affairs/more-children-infected-in-second-wave-but-no-need-for-panic-experts-121052500934_1.html (accessed June 4, 2021). Coronavirus second wave affecting children more; over 79,000 tested positive since March. https://scroll.in/latest/991698/coronavirus-over-79000-children-tested-positive-since-march-as-india-grapples-with-second-wave ). (accessed June 4, 2021). COVID Live Update: 177,419,908 Cases and 3,838,675 Deaths from the Coronavirus - Worldometer. https://www.worldometers.info/coronavirus/ (accessed June 16, 2021). Coronavirus in India: Is Coronavirus 3rd wave 100% inevitable? - The Financial Express. https://www.financialexpress.com/lifestyle/health/coronavirus-in-india-is-coronavirus-3rd-wave-100-inevitable/2255542/ (accessed June 12, 2021). Explained: Will India witness a ‘dreaded’ third wave after its Covid tsunami? | India News - Times of India. https://timesofindia.indiatimes.com/india/explained-will-india-witness-a-dreaded-third-wave-after-covid-tsunami/articleshow/82801387.cms (accessed June 16, 2021). Maharashtra Preps For 3rd Wave As Covid Hits 8,000 Children In 1 District. https://www.ndtv.com/india-news/maharashtra-preps-for-3rd-wave-as-covid-hits-8-000-children-in-1-district-2452564 (accessed June 4, 2021). covid-19: Covid-19 crisis far from over; 3rd wave to be more dangerous: CSIR official, Health News, ET HealthWorld. https://health.economictimes.indiatimes.com/news/diagnostics/covid-19-crisis-far-from-over-3rd-wave-to-be-more-dangerous-csir-official/81265213 (accessed June 16, 2021). More severe third wave of COVID on its way to India, vaccination may ensure lower mortality, claims SBI report-India News, Firstpost. https://www.firstpost.com/india/more-severe-third-wave-of-covid-on-its-way-to-india-vaccination-may-ensure-lower-mortality-finds-sbi-report-9679531.html (accessed June 4, 2021). Abbreviations COVID-19:corona virus disease 19;NR:northern region; CR: Central Region; WR: Western Region; ER: Eastern Region; NER: North Eastern Region; SR: Southern Region; UT: Union Territory; CCR: Cumulative case rate; CDR: Cumulative Death rate; CFR: Case fatality ratio; SARS CoV-2: severe acute respiratory syndrome coronavirus 2;LAE:Legislative Assembly Elections Tables Tables 1-2 are available in the Supplementary Files. Supplementary Files Tables.docx Tables 1 and 2 S1Supplementaryfigure1.tif Fig. S1: A comparison of fold change in the weekly-average numbers of new cases and deaths between the entire India and the states of Uttarakhand and Utter Pradesh. The fold changes were calculated between the week, before the first Shahi Snan (auspicious bath) of the Kumbh Mela 2021, i.e. from 1st March to 7th March, 2021 and the week after the festival ended with the last Shahi Snan on 27th April, 20201. i.e. from 3rd May to 9th May, 2021 for the nation (Cases: 20.9-fold, Deaths: 35.4-fold) and for Uttarakhand (Cases: 117.2-fold, Deaths: 266-fold), and Utter Pradesh (Cases: 240-fold, Deaths: 201.7-fold). Drastic increase in the weekly-new cases and deaths were found for the two states, which organized the festival, compared to the entire nation, except these two states. No statistical test was performed in this comparison FigS2supplementaryFigure2.tif Fig S2: A comparison of fold change in average daily case numbers in the 4 states (Assam, Kerala, Tamil Nadu, West Bengal) and 1 UT (Puducherry) before, during and after their Legislative Assembly Elections (LAE), with 4 other states (Karnataka, Maharashtra, Andhra Pradesh, Chattisgarh) and 1 UT (Delhi) (major case contributors) that observed no LAE. TableS1Supplementary.xlsx A comparison of fold change in the weekly-averaged numbers of new cases and deaths between the entire India between the week, before the first Shahi Snan and just after Shahi snan of the Kumbh Mela 2021 Supplementarytable2S2.xls An account of the fold change in average daily cases before ,during and after elections in5 states/UT that observed Legislative Assembly Elections (LAE) along with 5 other states/UT(Major case contributors) that had no reported major public gatherings Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-666506","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":36237673,"identity":"930a06b6-36f4-47a8-a0dd-d2768039477c","order_by":0,"name":"Satabdi Datta","email":"","orcid":"","institution":"Thapar Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Satabdi","middleName":"","lastName":"Datta","suffix":""},{"id":36237674,"identity":"45cea488-e3b0-4516-886f-7f5edd6d0d90","order_by":1,"name":"Neloy Kumar Chakroborty","email":"","orcid":"https://orcid.org/0000-0001-8616-955X","institution":"Thapar Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Neloy","middleName":"Kumar","lastName":"Chakroborty","suffix":""},{"id":36237675,"identity":"37653fa4-d8f0-4c1b-b9a9-31f036ac17b7","order_by":2,"name":"Deepinder Sharda","email":"","orcid":"","institution":"Thapar Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Deepinder","middleName":"","lastName":"Sharda","suffix":""},{"id":36237676,"identity":"592c4505-d0e5-4da3-82ab-9c532a6c0d35","order_by":3,"name":"Komal Attri","email":"","orcid":"","institution":"Thapar Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Komal","middleName":"","lastName":"Attri","suffix":""},{"id":36237677,"identity":"bc41a9b8-a366-4b55-ac4f-430237f14164","order_by":4,"name":"Diptiman Choudhury","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDCCw0CcAMT8DDwwoQSCWhgbQGok24jWcgCoBUQbHCNWC99x3uMPHubY5Rnf7z34uaDmHgM/e44BXi2Sh/kSGxK3JRebHeNLlp5xrJhBsucNfi0Gh3kMgVqYE7cd4zGQ5mFLYDC4QcAWqJb6xM1tPMa/ef4lMNgTqeVw4gY2HjNp3jagLRJE+GVG4rbjiTOO5ZhZz+xL4JE486wArxa+82cPfPy5rTqxv/mM8e2Cbwly/O3JG/BqYUBEOgMDMyqXWC2jYBSMglEwCjAAALmBR+fQbPdOAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-1080-4558","institution":"Thapar Institute of Engineering and Technology","correspondingAuthor":true,"prefix":"","firstName":"Diptiman","middleName":"","lastName":"Choudhury","suffix":""}],"badges":[],"createdAt":"2021-06-28 09:38:53","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-666506/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-666506/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":10964196,"identity":"34304fc7-927d-48d1-a65b-82ec076cce6e","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"tif","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":375765,"visible":true,"origin":"","legend":"Chronological variations of cases and deaths during first and second COVID 19 wave in India: Variation in daily case numbers (A) and daily deaths (B) during the first and second wave (from 30th January 2020 to 29th May 2021) in India. Chronological variations in contributions of different regions of India towards total COVID-19 cases(C) and deaths (D) in the country. A comparison of the contribution of different regions of India towards total cases(E) and deaths(F) during the first and second wave of COVID-19 in the country","description":"","filename":"FIGURE1.tif","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/d53b179a6cc9a2d4ee6d0cbb.tif"},{"id":10963972,"identity":"11e4bd6a-9dbe-42e9-b967-d4699be6619e","added_by":"auto","created_at":"2021-06-30 15:29:26","extension":"tif","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":183580,"visible":true,"origin":"","legend":"Covid-19 cumulative cases and deaths in India: Different states and union territories (UT) of India reporting COVID-19 cases by cases/1 lakh population during first (A) and second wave (B) of the pandemic; deaths/1lakh population in different states and UT’s in first (C) and second wave(D)","description":"","filename":"FIGURE2.tif","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/d08dd9a1c6d7da3eba5c339f.tif"},{"id":10964194,"identity":"70cd2035-13b1-4212-a60f-f9b26c57d072","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"tif","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":186548,"visible":true,"origin":"","legend":"COVID-19 CFR and tests in India: The case fatality ratio (CFR) in different states and UT’s during first (A) and second wave(B); tests per case ratio during first(C) and second(D) wave of the pandemic in different states and UT’s.","description":"","filename":"FIGURE3.tif","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/6c3848f6308e7270a8ba6faf.tif"},{"id":13702028,"identity":"283e626b-70f6-4285-9e91-cd57fd58fffd","added_by":"auto","created_at":"2021-09-17 13:33:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":956218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/56be971b-7ea5-4a7f-a941-7c5e8c31d7a2.pdf"},{"id":10964198,"identity":"dae8a470-cb2d-46bb-a519-74f7349bd031","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2469196,"visible":true,"origin":"","legend":"Tables 1 and 2","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/2773f705126130d834d11bd0.docx"},{"id":10964192,"identity":"7d55ac4d-b6ca-47c5-b302-edd900fc3b95","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":236248,"visible":true,"origin":"","legend":"Fig. S1: A comparison of fold change in the weekly-average numbers of new cases and deaths between the entire India and the states of Uttarakhand and Utter Pradesh. The fold changes were calculated between the week, before the first Shahi Snan (auspicious bath) of the Kumbh Mela 2021, i.e. from 1st March to 7th March, 2021 and the week after the festival ended with the last Shahi Snan on 27th April, 20201. i.e. from 3rd May to 9th May, 2021 for the nation (Cases: 20.9-fold, Deaths: 35.4-fold) and for Uttarakhand (Cases: 117.2-fold, Deaths: 266-fold), and Utter Pradesh (Cases: 240-fold, Deaths: 201.7-fold). Drastic increase in the weekly-new cases and deaths were found for the two states, which organized the festival, compared to the entire nation, except these two states. No statistical test was performed in this comparison","description":"","filename":"S1Supplementaryfigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/f04374ad5a8c837dbfa747e4.tif"},{"id":10964193,"identity":"49398d5e-d1c3-4f35-97e1-75a7ca445570","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":235366,"visible":true,"origin":"","legend":"Fig S2: A comparison of fold change in average daily case numbers in the 4 states (Assam, Kerala, Tamil Nadu, West Bengal) and 1 UT (Puducherry) before, during and after their Legislative Assembly Elections (LAE), with 4 other states (Karnataka, Maharashtra, Andhra Pradesh, Chattisgarh) and 1 UT (Delhi) (major case contributors) that observed no LAE.\n","description":"","filename":"FigS2supplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/a2ba49f5b0fbabbd94d7c35a.tif"},{"id":10964191,"identity":"3d7ce584-eb68-4d86-9244-791c59dd50a6","added_by":"auto","created_at":"2021-06-30 15:32:26","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11587,"visible":true,"origin":"","legend":"A comparison of fold change in the weekly-averaged numbers of new cases and deaths between the entire India between the week, before the first Shahi Snan and just after Shahi snan of the Kumbh Mela 2021","description":"","filename":"TableS1Supplementary.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/0bf4c0954ddd40e3e5b07e4c.xlsx"},{"id":10964337,"identity":"fccb51a4-ff21-469c-9fe3-f510e75c4a9e","added_by":"auto","created_at":"2021-06-30 15:35:26","extension":"xls","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":19968,"visible":true,"origin":"","legend":"An account of the fold change in average daily cases before ,during and after elections in5 states/UT that observed Legislative Assembly Elections (LAE) along with 5 other states/UT(Major case contributors) that had no reported major public gatherings","description":"","filename":"Supplementarytable2S2.xls","url":"https://assets-eu.researchsquare.com/files/rs-666506/v2/ef64d9cd3c996003d7adc415.xls"}],"financialInterests":"","formattedTitle":"\u003cp\u003eCOVID-19 pandemic in India: Chronological comparison of the regional heterogeneity in the pandemic progression and gaps in mitigation strategies\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eIndia is currently the second-largest contributor of total COVID-19 cases of the world, accounting for about 16% of the total cases and around 9% of deaths worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The Indian subcontinent reported its first case of COVID-19 on January 30th, 2020\u003csup\u003e2\u003c/sup\u003e from Kasargod district in the state of Kerala. However, most of the other states reported their first cases in March 2020, and during this period the number of active cases started to amplify at a rapid pace. Amid this crisis, the government of India announced a nationwide lockdown with implementations of public health and social measures\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, but in spite of such stringent measures, the cases in India showed a steady acceleration in numbers, particularly aggravated after the unlock phase 1 from 31st May, 2020. In most of the states, the surges in cases were visualized from the beginning of June 2020, which reached their respective maxima in the middle of September, 2020\u003csup\u003e4\u003c/sup\u003e. The first wave however subsided towards the end of January 2021 with only about 1.5 lakhs active cases and a much lower test positivity rate in the whole subcontinent\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This led to the withdrawal of many restrictions on social and political gatherings, albeit the consequence of these measures turned out to be catastrophic soon afterward \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Towards the beginning of March 2021, the number of infections began to soar, which marked the beginning of the catastrophic second wave of COVID-19 pandemic that overwhelmed the medical facilities of most of the states and compelled the state governments to implement lockdown-like restrictions\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The emergence of new indigenous mutants of the SARS-CoV-2 virus along with other international mutants was accessed as one of the major reasons for such a surge in cases\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and fatalities in the second wave of the pandemic.\u003c/p\u003e \u003cp\u003eThe Indian subcontinent is characterized by diverse geographical and demographical regions, populated by heterogeneous cultural, political, linguistic, and ethnic groups of people\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, covering an area of 3.28\u0026nbsp;million square kilometers with a total population of about 138 cores \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Thus the progression pattern of the pandemic was also turned out to be heterogeneous in each region of the country, which therefore demands the analysis of chronological heterogeneity in the regional and state-specific infection rates, death rates, wave patterns, and testing capacities for a clear interpretation of the progression patterns of the wave across the country. In this study, we did a comprehensive analysis of the chronological changes in the first and the second-wave patterns of the pandemic in each region of the country and its respective states. India comprises 28 states and 8 unions territories\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, divided along 6 administrative subdivisions,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e the Northern region(NR), Central region(CR), Western Region (WR), Eastern (ER), North Eastern Region (NER) and Southern region (SR), Indian states (Table-1,2). The analyses of the progression patterns of the two waves across these different subdivisions and their respective states are a significant step forward to evaluate the real scenario of the COVID-19 situation across the nation as well as the pandemic mitigation strategies.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and data sources\u003c/h2\u003e \u003cp\u003eA detailed study of the COVID-19 infections and their related statistics in India was done between January 2020 to May 29th, 2021. The days of first reported infection, rising(10% consistent increase in active cases) and declining phases of the two respective pandemic waves, wave\u0026rsquo;s peak, numbers of new infections, death, recoveries along with the testing and demographical data for all the 6 administrative regions comprising of 28 states and 8 union territories of the country, were obtained from the online monitoring official website of the Government of India\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and other government and international websites.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The pandemic wave or phase was defined as a rising number of COVID-19 cases with a definite peak, which was followed by a declining number of cases, or the trough period, where the rates of new infections and active cases have declined significantly. The day reporting the highest number of active cases was defined as the peak of the wave. The number of monthly new cases, recoveries, and deaths for each state were calculated, the chronological (monthly) contribution of new cases, deaths, and recoveries of each administrative region of the subcontinent, was calculated by summing up the respective values of the aforesaid parameters of all the states and union territories of the concerned region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eCCR, cases per 1 lakh or 100000 populations; CDR, deaths per 100000 populations], CFR; the number of deaths reported per number of cases reported \u0026times; 100), tests per case (total tests: total case) ratio for both the first (30th January 2020\u0026ndash;31st January 2021) and second waves (early February 2021 till 29th May, 2021) of the pandemic were calculated. The weekly-average numbers of confirmed cases, active cases, and deaths were quantified by estimating the changes in numbers from one day to the other day average over the span of a week. The fold changes, for the Kumbh Mela 2021, were calculated by dividing the weekly-average numbers of the later week (3rd May \u0026ndash; 9th May 2021) by the earlier week (1st March \u0026ndash; 7th March, 2021). The fold changes in average daily new cases for each month [before LAE (march-21), during LAE (April-21), and after LAE (May-21)] for the 5 States which underwent elections were calculated and compared with 5 states (a major contributor of cases) that had no major public gathering events.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003e \u003cb\u003eA chronological overview of the contributions of different regions of India towards the cases and fatalities in the two waves\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe chronological variations in the number of new cases and new deaths in India (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) and the contributions of different regions of the country towards the total cases and fatalities of the nation are noteworthy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). At the beginning of the 1st wave, the SR accounted for nearly 40% of total cases in March 2020 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). From April, 2020 till June 2020, the WR remained the major contributor of COVID-19 cases, (43%, 46%, and 31% of the total cases in the respective months). Subsequently from June 2020, when the first phase of unlocking (unlock-1) started in the country (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), till the end of October 2020, the SR contributed 41%, 40%, 34%, and 41% of the total COVID-19 cases of the country in the respective months (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Only in November 2020, the NR became the highest contributor of new cases (31%), however from December 2020 till February 2021 (in the declining phase of 1st wave), SR contributed 31%, 47% and 43% of the total cases in the subsequent months(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). At the beginning of the rising phase of the second wave, from March 2021 till April, 2021, the WR contributed about 63%, and 30% of the nations\u0026rsquo; total cases respectively. In May 2021, the SR once again turned out to be the major contributor of new cases in the country (42%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eIn terms of fatality, the WR accounted for the highest monthly fatality from March 2020 till October 2020 (contributed nearly 35%, 59%, 62%, 51%, 41%, 37%, 39%, and 31% of total monthly deaths of the nation respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The NR contribute over 33% and 31% of total fatality in November and December 2020. The WR was the highest monthly contributor of COVID-19 related fatality from January 2021 till April, 2021(30%, 40%, 39%, and 33% of total fatality). However, in May 2021, the SR accounted for the maximum proportion of fatality of the country (28%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Thus, it can be inferred from these results that both the Western and Southern Indian states have been the major hotspots of the COVID-19 pandemic in the Indian subcontinent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, F)\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe first wave of COVID-19 in India \u0026ndash; A detailed analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eApart from Kerala, most of the Indian states reported their first infection in March or April 2020. The Government of India has implemented a nationwide complete lockdown protocol from 25th March 2020 to combat the spread, like many other nations. A continuous lockdown was applied, in four phases, until 31st May 2020. The unlock process, implemented in six phases, commenced from 1st June, 2020 to 30th November, 2020.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e The daily-cases though began to surge steadily, especially from the end of May 2020 (just before the beginning of the 1st phase of unlock) to September 2020 in the majority of the states (Table-1). The adverse effects of unlocking can be understood from the following statistics \u0026ndash; from the week, before the last week of lockdown (18th May 2020 to 24th May 2020) to the week, after one continuous week of unlock (8th June 2020 to 14th June 2020), the change in weekly-average numbers of new confirmed cases, active cases, and deaths respectively showed increases from 6369 to 11170 (1.75-fold), from 3153 to 4048 (1.28-fold), and from 144 to 340 (2.35-fold) (analysis not shown).\u003c/p\u003e \u003cp\u003eIndia reported the maximum number of daily new cases on 16th September 2020 (around 98,000) and maximum active cases on 17th September 2020 (1018454), which was marked as the peak of the wave. Subsequently, both the figures of daily and active cases started to drop steadily in the following weeks, till the end of January 2021, when the number of daily cases reduced to around 10,000 cases/day; marking the trough of the wave.\u003c/p\u003e \u003cp\u003eAmong the 10758629 cases reported during the first wave, the highest number of cases was reported from the SR (3933360) which contributed to 36.5% of the total cases. The top contributor state from the SR was Karnataka (about 8.7%), followed by others (Table-1). Lakshadweep islands, which happened to be the last area of SI to report its first infection have contributed minimum to the nation\u0026rsquo;s total cases (0.0008%). The WR comes next, which contributed 21.6% of the nation\u0026rsquo;s total cases, where the top contributor state was Maharashtra (reported 2026399 cases, ~\u0026thinsp;18.8%). States of the NR, coming next, accounted for about 16.4% of total cases were the highest contributor was the national capital, Delhi (5.9%). The ER shared 11.8% of the nation\u0026rsquo;s total cases, where West Bengal contributed mostly (~\u0026thinsp;5.3%). The CR of India produced 10.7% of the total cases, where Uttar Pradesh (5.5%) was a major contributor. The NER was the lowest contributor of cases and deaths and accounted for only 3% of the total cases of the first wave where Assam shared for the majority of cases (2%), whereas the other 7 states altogether accounted only for 1% of the cases (Table-1). The dates, representing the peaks of active COVID-19 cases, varied for the states and UTs (Table-1).\u003c/p\u003e \u003cp\u003eThe CCR (number of cases/1 lakh of the population) was found to be highest in Ladakh (3352 cases/1 lakh) followed by Delhi (3175) and Chandigarh (1773) from the NR. The other states and union territories which reported a case/1 lakh ratio of more than 1000 are Uttar Pradesh (2668) and Chattisgarh (1053) from the CR, Goa (3468) and Maharashtra (1661) from the WR, and Andhra Pradesh (1707), Karnataka (1423), Kerala (2655), Telangana (1103), and Puducherry (2605) from the SR (Table-1).\u003c/p\u003e \u003cp\u003eIn addition to contributing the second-highest number of COVID-19 cases, states of the WR also contributed the maximum number of deaths (accounted for 36.4% of the total deaths of the country) during the first wave out of a total of 154428 deaths nationwide. The state of Maharashtra accounted for the most number of deaths in the region (33%), followed by Gujarat (2.8%) and Goa (0.5%). The trend remained similar for the SR, which in line with its highest contribution to the number of cases, also accounted for 24.4% of the total deaths of the nation, where Karnataka (8%) and Tamil Nadu (8%) were the two major contributors (Table-1). Contribution from the Northern states were about 17.7% to the total number of fatalities of where Delhi was the major contributor (7%), followed by other states (Table-1). The CR, in this regard, accounted for 10.5% of the total deaths, where Uttar Pradesh (5.6%) reported the maximum number of deaths (Table-1). Among the 9.5% of the total deaths, contributed by the ER, West Bengal (6.6%) was the major contributor (Table-1). The NER states reported the least mortality and contributed only about 1.51% of the total deaths of the nation (Table-1). The highest CDR was however reported by the national capital, Delhi (54 per 100000 population), followed by Goa (50), Ladakh (45), and Maharashtra (42) (Table-1).\u003c/p\u003e \u003cp\u003eThe CFR was found to be highest in the state of Punjab (3.24) in the NR, followed by Maharashtra (2.5) in the WR with Sikkim (2.18) stands next from the NER. The state of West Bengal (1.785) accounted for the highest CFR from the ER, followed by Uttarakhand (1.71), Delhi (1.71) and Himachal Pradesh (1.69) from the NR. Among the states of Southern India, Puducherry (1.66) recorded the highest CFR (Table-1).\u003c/p\u003e \u003cp\u003eRegarding the testing of cases, until the end of January 2021, more than 22.84 crores (1 crore\u0026thinsp;=\u0026thinsp;10\u0026nbsp;million) COVID-19 tests were performed all over India, of which the national capital, Delhi (4.81%) recorded the highest percentage from the NR, Uttar Pradesh (12.26%)tops the list from the CR, Maharashtra (6.57%) from the WR, Bihar (9.19%)from the ER, Andhra Pradesh (7.88%) from the SR, and Assam (2.83%) from the NER. The WHO has recommended an optimum of 30, test per case ratio (T: C), as standard; however apart from the states, like Jammu and Kashmir (36.5), Uttar Pradesh (46.6), Gujarat (42.1), Bihar (80.5), Jharkhand (44), Mizoram (48), and Andaman and Nicobar islands (44), all other states and union territories had a T: C ratio less than the WHO recommended mark of 30 tests/case\u003csup\u003e18\u003c/sup\u003e. (Table-1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe second wave of COVID-19 in India \u0026ndash; A detailed analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe period between the end of February, 2021 and early March, 2021, marked the rising phase of the catastrophic second wave of the COVID-19 pandemic in India. During this period, the country reported more than 3 lakhs new cases/day in April that soared to over 4 lakhs cases/day and over 4000 daily deaths in the first week of May, 2021, overburdening the healthcare system of the country. On 6th May, India reported its highest number of over 414280 new cases, which marked the peak of the wave until now. Thereafter, the daily cases started to dip gradually, however the fatality rate remained high.\u003c/p\u003e \u003cp\u003eStarting from 1st February till the 29th May, 2021, India reported a total number of 17134975 cases and over 1.7 lakh deaths. Until 29th May, 2021, the SR remained the top contributor of cases (32%) and the third major contributor of fatalities (22%), where the state of Karnataka (9.5%) and Kerala (9.1%) together accounted for more than half of the total cases of theregion, and again Karnataka (9.3%) and Tamil Nadu (6.3%), like in the first wave, were also the major contributors to the nation\u0026rsquo;s fatalities (Table-2). Until 29th May, the WR contributed over 25% and 29% of the COVID-19 related cases and fatalities respectively, where Maharashtra was major contributor (21% and 25% of the cases and deaths). The NR contributed about 16% and 27% of the total cases and fatalities respectively, where Delhi, was the major contributor (4.6% and7.7% of cases and fatality respectively). The CR accounted for about 13% and 14.5% of cases and deaths respectively, where Uttar Pradesh was major contributor (6.3% and 6.7% of cases and fatalities respectively). The ER contributed around 10.8% and 7.7 % cases and fatalities of the country respectively where West Bengal is the highest contributor (10.8% and 7.7% of total cases and fatalities respectively). The NER reported the least number of cases (1.63%) and fatalities (2%) in the country, where the major contributor was Assam (over 1% and 1.2% of the cases and fatalities respectively) (Table-2).\u003c/p\u003e \u003cp\u003eUntil 29th May, 2021, the highest CFR was reported by Andaman and Nicobar Islands (2.59) where 51 deaths were reported out of 1970 cases, followed by Punjab (2.23) from the NR and Nagaland (2.22) from the NER. The highest number of CDR was found for Goa (118 deaths/1 lakh), followed by Uttar Pradesh (51), and Lakshadweep islands (45). Lakshadweep was also found to contribute highest to the CCR (11084 cases/1lakh), followed by Uttar Pradesh (4835) and Chandigarh (3289). It is noteworthy that apart from Andaman and Nicobar Islands (86 tests/case), Himachal Pradesh (49), and Ladakh (29), the other states and union territories were lagging behind the recommended WHO level\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOne of the major contrast between the first and second wave is the evolution of new variants of the novel SARS-CoV-2 virus during the second wave which triggered a sudden surge in cases in most regions of the country. The three imported viral variants of concern that have been identified in India are the UK (B.1.1.7) variant, the South African (B.1.351) variant and the Brazilian (P1) variant, among which the B.1.1.7 variant was predominantly present in Delhi and Punjab in April, 2021. Among the two novel variants of India, the highly contagious B.1.617 variant from Maharashtra has started evolving rapidly and overtook the B.1.618 variant in West Bengal, and eventually became the major variant in most of the states. The WHO has already designated the B.1.617 variant as \u0026lsquo;variant of concern\u0026rsquo; in May, 2021. This variant has spread in all states across the nation and is identified as one of the major causes of the calamity associated with the second wave of COVID-19 in India (especially in Delhi, Andhra Pradesh, Gujarat, Maharashtra and Odisha), as per the study conducted by the Indian SARS-CoV-2 Genomics Consortium (INSACOG), which was launched by the Ministry of Health and Family Welfare, Govt. of India, on 30th December, 2020.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eRoles of some major mass-scale public gatherings in the second wave\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMass scale public gatherings like Kumbh Mela 2021 (9\u0026nbsp;million participants), state elections (covering 243\u0026nbsp;million residents) have contributed in faster and elevated spreading of the second wave.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e A 117-foldincrease in the number of weekly-average new cases and a 266-fold increase in the weekly-average new deaths were found for the state of Uttarakhand when we compared the data between before and after the festival. Uttar Pradesh, like Uttarakhand also showed a sharp jump in the weekly-average new cases and deaths \u0026ndash; respectively a 240-fold and 201-fold increase in the numbers of weekly-average new cases and deaths (Table S1 and Fig. S1). These numbers are much higher than the fold-increase found for the cases (20.9-fold) and deaths (35.4-fold) for the entire nation (except these two states) between the mentioned weeks. Five states Assam, Kerala, Puducherry (UT), Tamil Nadu, and West Bengal that witnessed their \u0026lsquo;legislative assembly elections\u0026rsquo; (LAE) from late March to end of April 2021 also reported a substantial increase in the average daily cases after the elections compared to some of the states with no LAE or major public gatherings (Fig-S2, Table S2); mainly attributed to the election-related rallies and mass-scale public meetings organized by the local political parties\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. However, it is noteworthy that dissecting out the exact contributions of such gatherings from the general increase in the numbers of cases and deaths due to aggravation of the pandemic itself is out of scope.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThe second wave of COVID-19 pandemic resulted in total disarrays in all states of the country; an escalation of the infections in such a large magnitude was never expected. While the first wave caused a little over 1.08 crore infections and over 1.5 lakhs fatality in the whole country within a period of 11 months, the ongoing second wave resulted in over 1.7 crore infections and nearly 2 lakhs fatalities in a span of merely 4 months resulting in an unprecedented chaos in the supplies of life-saving drugs and oxygen together with non-availability of hospital beds in most of the parts of the country\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The average daily new cases during April 2021 was around 2.31 lakhs cases/day which soared to about 3.01 lakhs cases/day in May 2021, which is nearly 2.7 and 3.5 times of the average daily cases (87,000 cases/day) of September 2020 (when India reported its peak of the first wave). The CCR and CDR for the second wave were also found to elevate substantially in comparison to the first wave (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), which comprehend the high rate of infection and fatalities in the country. However, the CFR for both the waves did not show significant variation for the majority of the states to date (Table-1 and 2), which is most likely due to the similar death rates of all existing variants of the SARS-CoV-2 virus in India. Thus, the total numbers of infection and death have together increased during the second wave without changing the CFR. The advent of new and more infectious variants of the virus, inaccuracy in diagnosis, lack of testing, non-transparency in data sharing, low rate of vaccination, decreased rate of genome sequencing of the COVID-19 positive samples along with unchecked social, religious (like Kumbh Mela 2021), and political gatherings (legislative assembly general elections) towards the beginning of the year, and the serious lack of COVID-19 mitigation measures, despite previous warnings, were held responsible for this unprecedented escalation of the pandemic in the country by many reports\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Despite an increase in daily test numbers, the test/case ratio has dropped in the majority of the states in the second wave. Thus, the need of the hour is to accelerate the testing rates both in the rural and urban regions of the nation to get a clear picture of the infection scenario\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e that may aid to avert the nucleation of another catastrophic wave of the pandemic\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA comprehensive evaluation of the available data specifically reveals that the SR and WR were the major hotspots of the pandemic in both waves. The states of Karnataka and Tamil Nadu from the SR and Maharashtra from the WR showed consistently high numbers of infections and fatalities in both waves. Irrespective of the presence of the highly infectious B.1.617 Indian variant of the SARS-CoV-2 in these states during the second wave, these results are indicative of shortfalls in the health systems and/or deficits in implementations of COVID-19 restriction protocols in the populations.\u003c/p\u003e \u003cp\u003eAlthough the data on demographical differences in infection are not made available to the public by the Ministry of Health and Family Welfare, Govt. of India, however, many recent reports suggest that a notable difference between the first and second waves in the country are that the second wave affected a large portion of the pediatric group, which was largely asymptomatic in the first wave\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. As of the first week of April 2021, it was reported that over 79,000 children were affected by the disease from five states that include Maharashtra, Chattisgarh, Karnataka, Uttar Pradesh, and Delhi between 1st March to 4th April 2021, of which over 60,000 cases were from Maharashtra\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, however, the cases of hospitalization among the children were only a handful. Trends suggests that the average gaps between the peaks of the first and second wave in majority of countries were around 5 months\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, in India it was about 7.5 months, however, the escalation of the 2nd peak height was far higher in this country. At present, the second wave is on its declining phase for the majority of Indian states; however experts suggests that unless vaccination rate is accelerated, the country is set to face another 3rd wave by the end of this year\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e which may largely affect the unvaccinated population especially the paediatric group in large numbers\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, as trends suggests each subsequent waves have been more severe than the previous one in most of the countries that have already faced the third wave\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, therefore ramping up of the clinical trials of a vaccine for the paediatric group, rapid vaccination of the adults\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e together with the strengthening of the health infrastructure of the nation, wide-scale genomic sequencing of positive samples, monitoring weekly trends in the test positivity rates\u0026rsquo; strict implementation of COVID-19 appropriate restrictions and behaviour in public, are the urgent needs of the hour to protect the future of the country and its people from another COVID-19 tsunami.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eConflict of interests\u003c/h2\u003e \u003cp\u003e The authors declare no conflict of interests\u003c/p\u003e \u003c/p\u003e \u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eSD (CSIR-RA) is thankful to Council of Scientific and Industrial Research, Government of India for Post-doctoral Research Associateship fellowship [award no. 09/677(0055)/2020-EMR-I]. KA and DC are thankful to TIET-VT-CEEMS for research fellowship respectively. NKC is thankful to Thapar School of Liberal Arts \u0026amp; Sciences for the Director\u0026rsquo;s Discretionary fellowship.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCOVID Live Update: 172,963,233 Cases and 3,718,849 Deaths from the Coronavirus - Worldometer. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldometers.info/coronavirus/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrews MA, Areekal B, Rajesh K, \u003cem\u003eet al.\u003c/em\u003e First confirmed case of COVID-19 infection in India: A case report. Indian J. Med. Res. 2020; \u003cb\u003e151\u003c/b\u003e: 490\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePM Modi announces 21-day lockdown as COVID-19 toll touches 12 - The Hindu. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thehindu.com/news/national/pm-announces-21-day-lockdown-as-covid-19-toll-touches-10/article31156691.ece\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoronavirus Outbreak in India - covid19india.org. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.covid19india.org/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoronavirus live | Consistent fall in India\u0026rsquo;s active caseload due to decline in daily infections: Health ministry - The Hindu. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thehindu.com/news/national/coronavirus-updates-january-4-2021/article33490697.ece\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoronavirus: WHO says religious, political gatherings contributed to India\u0026rsquo;s surge in cases. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://scroll.in/latest/994785/covid-19-religious-and-political-gatherings-contributed-to-surge-in-cases-in-india-says-who\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCovid-19 surge in India: These states impose complete lockdown to curb spread. Full list here. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.livemint.com/news/india/covid19-surge-in-india-these-states-impose-complete-lockdown-to-curb-spread-full-list-here-11620476971862.html\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Novel Coronavirus Variants and India\u0026rsquo;s Uncertain Future - The Wire Science. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://science.thewire.in/health/sars-cov-2-variants-b117-b1617-india-second-wave-uncertain-future/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026lsquo;Two variants responsible for second wave\u0026rsquo; - The Sunday Guardian Live. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sundayguardianlive.com/news/two-variants-responsible-second-wave\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMastana SS. Unity in diversity: An overview of the genomic anthropology of India. Ann. Hum. Biol. 2014; \u003cb\u003e41\u003c/b\u003e: 287\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajumder PP, Basu A. A genomic view of the peopling and population structure of India. \u003cem\u003eCold Spring Harb Perspect Biol\u003c/em\u003e 2015; \u003cb\u003e7\u003c/b\u003e. DOI:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/cshperspect.a008540\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeography of India. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cs.mcgill.ca/~rwest/wikispeedia/wpcd/wp/g/Geography_of_India.htm\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Statistical Year Book India 2016 | Ministry of Statistics and Program Implementation | Government Of India. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mospi.nic.in/statistical-year-book-india/2016/171\u003c/span\u003e\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.wikipedia.org/wiki/India\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdministrative divisions of India - Wikipedia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.wikipedia.org/wiki/Administrative_divisions_of_India\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStates Uts - Know India: National Portal of India. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://knowindia.gov.in/states-uts/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndia COVID: 28,574,350 Cases and 340,719 Deaths - Worldometer. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldometers.info/coronavirus/country/india/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLockdown Unlock in India COVID19 pandemic guidelines restrictions 2020 coronavirus lockdown series | India News \u0026ndash; India TV. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.indiatvnews.com/news/india/lockdown-unlock-in-india-covid19-pandemic-guidelines-restrictions-2020-coronavirus-lockdown-series-674925\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e(No Title). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/docs/default-source/coronaviruse/transcripts/who-audio-emergencies-coronavirus-press-conference-full-30mar2020\u003c/span\u003e\u003c/span\u003e.pdf?sfvrsn=6b68bc4a_2 (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndian SARS-CoV-2 Genomics Consortium (INSACOG)..\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e(No Title). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://media.nature.com/original/magazine-assets/d41586-021-01274-7/d41586-021-01274-7.pdf\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumbh Mela and election rallies: How two super spreader events have contributed to India\u0026rsquo;s massive second wave of COVID-19 cases-India News, Firstpost. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.firstpost.com/india/kumbh-mela-and-election-rallies-how-two-super-spreader-events-have-contributed-to-indias-massive-second-wave-of-covid-19-cases-9539551.html\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e9.1 million thronged Mahakumbh despite Covid-19 surge: Govt data - Hindustan Times. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.hindustantimes.com/cities/dehradun-news/91-million-thronged-mahakumbh-despite-covid-19-surge-govt-data-101619729096750.html\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndia Covid crisis: Did election rallies help spread virus? - BBC News. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/56858980\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Oxygen Crisis in Second Wave Covid-19 Pandemic in India and \u0026ldquo;We the People\u0026rdquo; | Vivekananda International Foundation. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.vifindia.org/article/2021/may/03/the-oxygen-crisis-in-second-wave-covid-19-pandemic-in-india-and-we-the-people\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukase K, Kato M, Kikuchi S, \u003cem\u003eet al.\u003c/em\u003e Effect of eradication of Helicobacter pylori on incidence of metachronous gastric carcinoma after endoscopic resection of early gastric cancer: an open-label, randomised controlled trial. \u003cem\u003eLancet\u003c/em\u003e 2008; \u003cb\u003e372\u003c/b\u003e: 392\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndia wasted its early successes in managing Covid-19, PM Modi\u0026rsquo;s actions \u0026lsquo;inexcusable\u0026rsquo;: Lancet - Coronavirus Outbreak News. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.indiatoday.in/coronavirus-outbreak/story/india-wasted-early-successes-in-managing-covid19-pm-modi-actions-inexcusable-vaccination-drive-botched-lancet-1800465\u003c/span\u003e\u003c/span\u003e-2021-05-09 (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndia Covid: Kumbh Mela pilgrims turn into super-spreaders - BBC News. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/world-asia-india-57005563\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFewer Tests Could Be Why India\u0026rsquo;s COVID-19 Numbers Have Declined Since May 1 - The Wire Science. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://science.thewire.in/health/testing-covid-19-india-numbers-may-1-vaccine-decline/\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndia\u0026rsquo;s COVID-19 Testing Capacity Must Grow by a Factor of 10: Here\u0026rsquo;s How That Can Happen | Center For Global Development. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cgdev.org/publication/indias-covid-19-testing-capacity-must-grow-factor-10-heres-how-can-happen\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMore children infected in second wave, but no need for panic: Experts | Business Standard News. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.business-standard.com/article/current-affairs/more-children-infected-in-second-wave-but-no-need-for-panic-experts-121052500934_1.html\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoronavirus second wave affecting children more; over 79,000 tested positive since March. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://scroll.in/latest/991698/coronavirus-over-79000-children-tested-positive-since-march-as-india-grapples-with-second-wave\u003c/span\u003e\u003c/span\u003e). (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVID Live Update: 177,419,908 Cases and 3,838,675 Deaths from the Coronavirus - Worldometer. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldometers.info/coronavirus/\u003c/span\u003e\u003c/span\u003e (accessed June 16, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoronavirus in India: Is Coronavirus 3rd wave 100% inevitable? - The Financial Express. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.financialexpress.com/lifestyle/health/coronavirus-in-india-is-coronavirus-3rd-wave-100-inevitable/2255542/\u003c/span\u003e\u003c/span\u003e (accessed June 12, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eExplained: Will India witness a \u0026lsquo;dreaded\u0026rsquo; third wave after its Covid tsunami? | India News - Times of India. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://timesofindia.indiatimes.com/india/explained-will-india-witness-a-dreaded-third-wave-after-covid-tsunami/articleshow/82801387.cms\u003c/span\u003e\u003c/span\u003e (accessed June 16, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaharashtra Preps For 3rd Wave As Covid Hits 8,000 Children In 1 District. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ndtv.com/india-news/maharashtra-preps-for-3rd-wave-as-covid-hits-8-000-children-in-1-district-2452564\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ecovid-19: Covid-19 crisis far from over; 3rd wave to be more dangerous: CSIR official, Health News, ET HealthWorld. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://health.economictimes.indiatimes.com/news/diagnostics/covid-19-crisis-far-from-over-3rd-wave-to-be-more-dangerous-csir-official/81265213\u003c/span\u003e\u003c/span\u003e (accessed June 16, 2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMore severe third wave of COVID on its way to India, vaccination may ensure lower mortality, claims SBI report-India News, Firstpost. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.firstpost.com/india/more-severe-third-wave-of-covid-on-its-way-to-india-vaccination-may-ensure-lower-mortality-finds-sbi-report-9679531.html\u003c/span\u003e\u003c/span\u003e (accessed June 4, 2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e COVID-19:corona virus disease 19;NR:northern region; CR: Central Region; WR: Western Region; ER: Eastern Region; NER: North Eastern Region; SR: Southern Region; UT: Union Territory; CCR: Cumulative case rate; CDR: Cumulative Death rate; CFR: Case fatality ratio; SARS CoV-2: severe acute respiratory syndrome coronavirus 2;LAE:Legislative Assembly Elections\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1-2 are available in the Supplementary Files.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Thapar Institute of Engineering and Technology, Patiala, Punjab, India","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, first wave, second wave, India, regional heterogeneity, cases, fatality, hotspots, mitigation strategies","lastPublishedDoi":"10.21203/rs.3.rs-666506/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-666506/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe second wave of COVID-19 exerted more catastrophe in India than the first. The progressions of both waves were heterogeneous in the six different regions involving 28 states and 8 union territories. An analysis of the temporal variations in new cases and fatalities in all the states of India was done for both the 1st (30th January 2020 to 31st January 2021) and 2nd wave (1st February 2021 to 29th May 2021), which showed that India accounted for over 16% and 9% of the cases and fatalities of the world respectively. The Southern and Western regions remained the top contributor of cases and fatalities in both waves. The state of Punjab and Maharashtra reported the highest CFR (3.24 and 2.5 respectively) in the country during the 1st wave, and in the second wave, Andaman \u0026amp; Nicobar Islands (2.6), and Punjab (2.25) reported the highest CFR. The states of Goa and Delhi showed the highest CCR and CDR during the 1st wave respectively, whereas Lakshadweep and Goa reported the highest CCR and CDR respectively in the 2nd wave. The study comprehends the severity of the second wave over all the states of the country and highlights the major hotspots regions and some gaps in mitigation strategies.\u003c/p\u003e","manuscriptTitle":"COVID-19 pandemic in India: Chronological comparison of the regional heterogeneity in the pandemic progression and gaps in mitigation strategies","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2021-06-30 15:29:24","doi":"10.21203/rs.3.rs-666506/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2021-06-29 15:07:07","doi":"10.21203/rs.3.rs-666506/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e462fa5-9b39-41df-b5af-457c15bf0923","owner":[],"postedDate":"June 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":5374400,"name":"Epidemiology"}],"tags":[],"updatedAt":"2021-06-29T15:07:07+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-30 15:29:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-666506","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-666506","identity":"rs-666506","version":["v2"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}