Selected article for: "compartmental model and infection reproduction number"

Author: Shah, Parth Vipul
Title: Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India
  • Cord-id: z0jttclz
  • Document date: 2020_9_9
  • ID: z0jttclz
    Snippet: OBJECTIVES: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity. METHODS: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number. RESULTS: The infection rate is estimated to be 0.270 and the reproduction number to be
    Document: OBJECTIVES: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity. METHODS: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number. RESULTS: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 d for a 1-mo intervention period. The total infected individuals in India will be 9% of the total population. CONCLUSIONS: The predictions are sensitive to changes in the behavior of people and their practice of social distancing.

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