Author: Rajesh Ranjan
Title: Predictions for COVID-19 outbreak in India using Epidemiological models Document date: 2020_4_6
ID: 3vntjg8d_18
Snippet: where β is the transmission rate, and γ is the average recovery rate. Note that here constant N is not the population of the country but population composed of susceptibles (S), infected (I) and recovered (R). In the present model, at any time the total population N = S + I + R remains constant as dS(t) dt + dI(t) dt + dR(t) dt = 0 Initially, N is approximately equal to S as I is very small. In an outbreak, typically N will increase every day b.....
Document: where β is the transmission rate, and γ is the average recovery rate. Note that here constant N is not the population of the country but population composed of susceptibles (S), infected (I) and recovered (R). In the present model, at any time the total population N = S + I + R remains constant as dS(t) dt + dI(t) dt + dR(t) dt = 0 Initially, N is approximately equal to S as I is very small. In an outbreak, typically N will increase every day because more people may get affected due to local outbreaks. However, with quarantine and isolation, this number will slowly become constant. Hence, this SIR model, where N is assumed constant, is valid provided measures are taken to ensure N does not increase much with time. In the context of India, this model may be useful as rigorous social distancing measure has been introduced at an early stage and thus increase in N may not be significant. This model assumes equally likely recovery of everyone affected and hence does not consider factors like age etc.
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