Selected article for: "data set and parameter estimation"
Author: Chandra, S. K.; Singh, A.; Bajpai, M. K.
Title: Mathematical Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread
  • Cord-id: 31jszjzo
  • Document date: 2020_5_5
    • ID: 31jszjzo
    Snippet: COVID-19 is well known to everyone in the world. It has spread around the world. No vaccine or antiviral treatment is available till now. COVID-19 patients are increasing day by day. All countries have adopted social distancing as a preventive measure to reduce spread. It becomes necessary to estimate the number of peoples going to be affected with COVID-19 in advance so that necessary arrangements can be done. Mathematical models are used to provide early disease estimation based on limited par
    Document: COVID-19 is well known to everyone in the world. It has spread around the world. No vaccine or antiviral treatment is available till now. COVID-19 patients are increasing day by day. All countries have adopted social distancing as a preventive measure to reduce spread. It becomes necessary to estimate the number of peoples going to be affected with COVID-19 in advance so that necessary arrangements can be done. Mathematical models are used to provide early disease estimation based on limited parameters. In the present manuscript, a novel mathematical model with a social distancing parameter has been proposed to provide early COVID-19 spread estimation. The model has been validated with real data set. It has been observed that the proposed model is more accurate in spread estimation.

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