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_122
Snippet: For higher β, more people must get infected (immune) before stability is achieved, and the benefit obtained is proportionately a little lower. For example, for the same τ , γ and p, if β = 1.1 is held fixed, then the final uninfected population is 82.4%. In contrast, upon switching down to β = 1.05 for an extended period before returning to β = 1.1, the final uninfected population is 90.2%, i.e., the number of infected people decreases by 4.....
Document: For higher β, more people must get infected (immune) before stability is achieved, and the benefit obtained is proportionately a little lower. For example, for the same τ , γ and p, if β = 1.1 is held fixed, then the final uninfected population is 82.4%. In contrast, upon switching down to β = 1.05 for an extended period before returning to β = 1.1, the final uninfected population is 90.2%, i.e., the number of infected people decreases by 46%. The tradeoffs between T c and T o are similar to those observed in figure 9 , except that the dynamics is about two times faster (graphical results omitted for reasons of space).
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