Author: Chandrika Prakash Vyasarayani; Anindya Chatterjee
Title: New approximations, and policy implications, from a delayed dynamic model of a fast pandemic Document date: 2020_4_14
ID: ca92pbvi_2
Snippet: Mathematical models for the spread of disease have almost a century old history. In their seminal paper, Kermack and McKendrick [3] proposed a three-state model (popularly known as SIR) governing the evolution of susceptible (S), infected (I), and recovered (R) populations. In their model, the recovered population is assumed to have developed immunity against the infection. The model contains two free parameters, one for infection rate and one fo.....
Document: Mathematical models for the spread of disease have almost a century old history. In their seminal paper, Kermack and McKendrick [3] proposed a three-state model (popularly known as SIR) governing the evolution of susceptible (S), infected (I), and recovered (R) populations. In their model, the recovered population is assumed to have developed immunity against the infection. The model contains two free parameters, one for infection rate and one for recovery rate. The SIR model is widely used to predict the number of infected people in closed populations. The model has an analytical solution. Over time, the 1 "The fact that orbits starting from near (1, 0, 0, 0, 0) will approach an endemic equilibrium is difficult to prove; this part of our prediction is supported by numerical simulations."
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