Analyses and Forecast for COVID-19 epidemic in India

Banerjee, Rabin; Bhattacharjee, Srijit; Varadwaj, Pritish Kumar

doi:10.1101/2020.06.26.20141077

Cited by 9 publications

(11 citation statements)

References 20 publications

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“…COVID-19 was announced as a global pandemic by World Health Organization (WHO) [1] owing to its highly contagious and pathogenicity that has been rapidly spreading throughout the world since its first reported outbreak in China in December, 2019. The "first wave" of COVID-19 slowed down by September-October,2020 as was correctly predicted by three of the current authors [2]. After going down to as low as 10000 active patient, the "second wave" picked up by the middle of March, 2021 in India.…”

Section: Introductionsupporting

confidence: 70%

“…We have employed a modified version of the standard epidemiological model for infectious disease, i.e. SEIRD model [2] to include effect of repeated infection and vaccination. Let us describe the effect briefly.…”

Section: Methodsmentioning

confidence: 99%

“…S V E I R D Figure 1: Dynamics of SVEIRD model with initial conditions S(0) > 0, E(0) 0, I(0) 0, V (0) 0 and R(0) 0. Constants β, p, γ, σ, ν are defined in section (2). Mortality rate can be calculated from Covid-India data and is related to ν.…”

Section: Sveird Modelmentioning

confidence: 99%

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Will there be a third COVID-19 wave? A SVEIRD model based study of India’s situation

Kannan

Gurusriram

Banerjee

et al. 2021

Preprint

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Since first patient detected in India in late February, 2020, SARS-CoV-II virus is playing havoc on India. After the first wave, India is now riding the 2nd wave. As was in the case of European countries like Italy and UK, the 2nd wave is more contagious and at the time of writing this paper, the per day infection is as high as 400,000. The alarming thing is it is not uncommon that people is getting infected multiple time. On the other hand, mass vaccination has started step by step. There is also growing danger of potential 3rd wave is unavoidable, which can even infect kids and minors. In this situation, an estimation of the dynamics of SARS-CoV-2 is absolutely necessary to combat the pandemic. We have used a modified SEIRD model, that includes vaccination and repeat infection as well. We have studied India and 8 Indian states with varying SARS-CoV-2 infection. We have shown that, Covid-19 wave will be repeated time to time, but the intensity will slow down with time. In most possible situation, our calculation shows COVID-19 will remain as endemic for foreseeable future, unless we are able to increase our vaccination rate manifold.

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Section: Introductionsupporting

confidence: 70%

Section: Methodsmentioning

confidence: 99%

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Will there be a third COVID-19 wave? A SVEIRD model based study of India’s situation

Kannan

Gurusriram

Banerjee

et al. 2021

Preprint

Self Cite

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“…Rajasthan, the largest state in terms of the area, has the same number (eight) of testing labs as the city of Chennai, and that is just double India’s most densely populated state Bihar. Maharashtra has the highest testing centres and the maximum number of Covid-19 cases, on the other in the spectrum, Nagaland has no testing centre and no reported case (Banerjee, 2020). West Bengal experienced the highest death rate from Covid-19, along with the lower testing than major states in India (Basu, 2020b).…”

Section: Genesismentioning

confidence: 99%

Burden of COVID-19 pandemic in India: Perspectives from Health Infrastructure

Sahoo

Mandal

Mishra

et al. 2020

Preprint

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The coronavirus (COVID-19) is spreading rapidly across the country but testing regime of India is far from the global standards. It is important to identify the states where testing needs expansion and the magnitudes of active COVID cases are higher focusing on current health infrastructure to meet the pandemic. The data on COVID-19 was extracted from the Application Programming Interface. Test positive rate, test per confirmed case, recovery rate, case fatality rate, and percent distribution of active cases were computed. Availability of hospitals, hospital beds, intensive care unit and ventilators per lakh population was also computed by public and private sector. The result revealed that, Maharashtra constitutes more than one-third positive cases in the country. More than a quarter of the active cases in India belonged to the Mumbai district of Maharashtra, followed by the Chennai district (9.4%) and Ahmedabad district (9.1%). Further, about 40 percent of the active cases in India belonged to the 11 districts of Maharashtra. The increased test positive rate in Maharashtra and Gujarat to almost double in last one month is a concern. In order to bring the states and the country in right track, the test positive rate need to be brought down to below 2 percent. The procurement of higher number of high throughput machine, the Cobas 6800 testing machine, is need of the hour. Only few states have adequate health infrastructure. The priority should be the laid on expansion of more laboratories and hospitals, storage of PPE kit, testing kit, and indigenously developed vaccines.

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“…Agent based models have provided useful insights, at the level of full cities, into mitigation methods and the effectiveness of non-pharmaceutical interventions [12]. Related references which model COVID-19 in India are [10,[13][14][15][16][17][18][19][20][21][22][23][23][24][25][26][27][28][29][30][31][32][33][34][35][36]. These models are very largely compartmental models of varying degrees of complexity [37].…”

Section: Introductionmentioning

confidence: 99%

The INDSCI-SIM model for COVID-19 in India

Hazra

Pujari

Shekatkar

et al. 2021

Preprint

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Estimating the burden of COVID-19 in India is difficult because the extent to which cases and deaths have been undercounted is hard to assess. The INDSCI-SIM model is a 9-component, age-stratified, contact-structured compartmental model for COVID-19 spread in India. We use INDSCI-SIM, together with Bayesian methods, to obtain optimal fits to reported cases and deaths across the span of the first wave of the Indian pandemic, over the period Jan 30, 2020 to Feb 15, 2021. We account for lock-downs and other non-pharmaceutical interventions, an overall increase in testing as a function of time, the under-counting of cases and deaths, and a range of age-specific infection-fatality ratios. We first use our model to describe data from all individual districts of the state of Karnataka, benchmarking our calculations using data from serological surveys. We then extend this approach to aggregated data for Karnataka state. We model the progress of the pandemic across the cities of Delhi, Mumbai, Pune, Bengaluru and Chennai, and then for India as a whole. We estimate that deaths were undercounted by a factor between 2 and 5 across the span of the first wave, converging on 2.2 as a representative multiplier that accounts for the urban-rural gradient across the country. We also estimate an overall under-counting of cases by a factor of between 20 and 25 towards the end of the first wave. Our estimates of the infection fatality ratio (IFR) are in the range 0.05 - 0.15, broadly consistent with previous estimates but substantially lower than values that have been estimated for other LMIC countries. We find that approximately 40% of India had been infected overall by the end of the first wave, results broadly consistent with those from serosurveys. These results contribute to the understanding of the long-term trajectory of COVID-19 in India.

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Analyses and Forecast for COVID-19 epidemic in India

Cited by 9 publications

References 20 publications

Will there be a third COVID-19 wave? A SVEIRD model based study of India’s situation

Will there be a third COVID-19 wave? A SVEIRD model based study of India’s situation

Burden of COVID-19 pandemic in India: Perspectives from Health Infrastructure

The INDSCI-SIM model for COVID-19 in India

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