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SVEIRD Epidemiological Model to Predict the COVID-19 Transmission in Indian States

Swagata Mandal, International Institute for Population Sciences (IIPS)
Sayeed Unisa, international Institute for Population Sciences

As the second wave of covid-19 has hit India, it becomes very important to study its transmission dynamics, so that effective vaccination can be carried out, along with intervention measures. We have used an SVEIRD mathematical model to understand the transmission dynamics of the Indian states of Kerala, Delhi, and Maharashtra. As there is a lot of heterogeneity in the Indian demography, we have made our analysis state-wise to maintain the individual homogeneity. The model considers the proportion of the population which is Susceptible, Vaccinated, Exposed, Infected, Recovered, and Died. The model captures the intervention measures like partial and complete lockdown measures taken by the respective state governments into consideration. From the successful simulation of the model, we find that the intervention measures can be effective. Increasing the vaccination to 50% of the population can effectively reduce the number of infections, thus not burdening the healthcare systems.

Keywords: COVID-19, Mathematical demography, Health and morbidity

See paper.

  Presented in Session 12. COVID-19 and Consequences of Lockdowns on Health Outcomes