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Modelling the spread of SARS-CoV-2 pandemic - Impact of lockdowns & interventions
Manindra Agrawal1, Madhuri Kanitkar2, M. Vidyasagar3
1 Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
2 Deputy Chief Integrated Defence Staff (Medical), HQ Integrated Defense Staff, Ministry of Defence, Government of India, New Delhi, India
3 Department of Artificial Intelligence, Indian Institute of Technology Hyderabad, Hyderabad, Telangana, India
Correspondence Address:
Madhuri Kanitkar,
Deputy Chief Integrated Defence Staff (Medical), HQ Integrated Defense Staff, Ministry of Defence, Government of India, New Delhi 110 011,
India
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/ijmr.IJMR_4051_20 PMID: 33146155
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Background & objectives: To handle the current COVID-19 pandemic in India, multiple strategies have been applied and implemented to slow down the virus transmission. These included clinical management of active cases, rapid development of treatment strategies, vaccines computational modelling and statistical tools to name a few. This article presents a mathematical model for a time series prediction and analyzes the impact of the lockdown.
Methods: Several existing mathematical models were not able to account for asymptomatic patients, with limited testing capability at onset and no data on serosurveillance. In this study, a new model was used which was developed on lines of susceptible-asymptomatic-infected-recovered (SAIR) to assess the impact of the lockdown and make predictions on its future course. Four parameters were used, namely β, γ, η and ε. β measures the likelihood of the susceptible person getting infected, and γ denotes recovery rate of patients. The ratio β/γ is denoted by R0 (basic reproduction number).
Results: The disease spread was reduced due to initial lockdown. An increase in γ reflects healthcare and hospital services, medications and protocols put in place. In Delhi, the predictions from the model were corroborated with July and September serosurveys, which showed antibodies in 23.5 and 33 per cent population, respectively.
Interpretation & conclusions: The SAIR model has helped understand the disease better. If the model is correct, we may have reached herd immunity with about 380 million people already infected. However, personal protective measures remain crucial. If there was no lockdown, the number of active infections would have peaked at close to 14.7 million, resulted in more than 2.6 million deaths, and the peak would have arrived by June 2020. The number of deaths with the current trends may be less than 0.2 million. |
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