COVID-19 Transmission Dynamics in India with Extended SEIR Model

  1. Brahmatheja Reddy Mali Reddy
  2. Anuj Singh
  3. Pradeep Srivastava

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Abstract

India is one of the most harshly affected countries due to COVID epidemic. Early implementation of lockdown protocols were useful to control certain parameters of transmission dynamics, but the numbers are consistently increasing in later months. India’s population is divided into different clusters on the basis of population density and population mobility, even varying resource availability and since the recent cases are coming from throughout the country, it allows us to model an overall average of the country. In this study, we try to prove the efficiency of using the SEIR epidemiological model for different rate study analysis for COVID epidemic in India. Along with it we derived newer components for better forecast of the pandemic in India. We found that there is a decrease in R 0 value, but still the epidemic is not under control. The percentage of infected patients being admitted into ICU for critical care is around 9.986%, while the chances of recovery of critical patients being admitted to the ICU seem to be slim at 79.9% of the admitted being dead.

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    SciScore for 10.1101/2020.08.15.20175703: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

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  2. Version published to 10.1101/2020.08.15.20175703v1 on medRxiv