Selected article for: "good model and reproduction number"
Author: Singh, Pushpendra; Gupta, Anubha
Title: Generalized SIR (GSIR) epidemic model: An improved framework for the predictive monitoring of COVID-19 pandemic
  • Cord-id: 727zc3cu
  • Document date: 2021_2_15
    • ID: 727zc3cu
    Snippet: Novel coronavirus respiratory disease COVID-19 has caused havoc in many countries across the globe. In order to contain infection of this highly contagious disease, most of the world population is constrained to live in a complete or partial lockdown for months together with a minimal human-to-human interaction having far reaching consequences on countries’ economy and mental well-being of their citizens. Hence, there is a need for a good predictive model for the health advisory bodies and dec
    Document: Novel coronavirus respiratory disease COVID-19 has caused havoc in many countries across the globe. In order to contain infection of this highly contagious disease, most of the world population is constrained to live in a complete or partial lockdown for months together with a minimal human-to-human interaction having far reaching consequences on countries’ economy and mental well-being of their citizens. Hence, there is a need for a good predictive model for the health advisory bodies and decision makers for taking calculated proactive measures to contain the pandemic and maintain a healthy economy. This paper extends the mathematical theory of the classical Susceptible–Infected–Removed (SIR) epidemic model and proposes a Generalized SIR (GSIR) model that is an integrative model encompassing multiple waves of daily reported cases. Existing growth function models of epidemic have been shown as the special cases of the GSIR model. Dynamic modeling of the parameters reflect the impact of policy decisions, social awareness, and the availability of medication during the pandemic. GSIR framework can be utilized to find a good fit or predictive model for any pandemic. The study is performed on the COVID-19 data for various countries with detailed results for India, Brazil, United States of America (USA), and World. The peak infection, total expected number of COVID-19 cases and thereof deaths, time-varying reproduction number, and various other parameters are estimated from the available data using the proposed methodology. The proposed GSIR model advances the existing theory and yields promising results for continuous predictive monitoring of COVID-19 pandemic.

    Search related documents:
    Co phrase search for related documents
    • lockdown period and logistic model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
    • lockdown period and long lstm short term memory: 1, 2, 3
    • lockdown period and long lstm short term memory model: 1
    • lockdown period and low number: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    • lockdown period and lstm network: 1
    • lockdown period and lstm short term memory: 1, 2, 3
    • lockdown relaxation and logistic growth model: 1
    • lockdown relaxation and logistic model: 1
    • lockdown relaxation and logistic model parameter: 1
    • lockdown relaxation and low number: 1
    • logistic growth model and low number: 1
    • logistic model and long lstm short term memory: 1, 2
    • logistic model and long lstm short term memory model: 1
    • logistic model and low number: 1, 2, 3, 4, 5
    • logistic model and lstm network: 1
    • logistic model and lstm short term memory: 1, 2
    • long lstm short term memory and lstm network: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • long lstm short term memory and lstm short term memory: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • long lstm short term memory model and lstm network: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22