Author: Sang Woo Park; David Champredon; Joshua S. Weitz; Jonathan Dushoff
Title: A practical generation interval-based approach to inferring the strength of epidemics from their speed Document date: 2018_5_2
ID: jry46itn_24
Snippet: Characterizing the r-R relationship with mean and coefficient of variation also helps explain results based on compartmental models [46, 37] , because the mean and variance of the generation interval is linked to the mean and variance of latent and infectious periods. Shorter mean latent and infectious periods result in shorter generation intervals, and thus smaller R estimates. Less-variable latent periods result in less-variable generation inte.....
Document: Characterizing the r-R relationship with mean and coefficient of variation also helps explain results based on compartmental models [46, 37] , because the mean and variance of the generation interval is linked to the mean and variance of latent and infectious periods. Shorter mean latent and infectious periods result in shorter generation intervals, and thus smaller R estimates. Less-variable latent periods result in less-variable generation intervals, and thus higher R estimates. Less-variable infectious periods have more complicated effects. While they reduce variation in generation interval (which would be expected to increase R estimates), they also reduce the mean generation interval [39] (which would lead to a decrease). This explains the apparent anomaly between earlier results: when mean generation interval is held constant, the effect of less-variable infectious periods is to reduce variation, leading to lower R for a given r [37] ; when mean infectious period is held constant the effect of reducing generation interval will be stronger, leading to higher R [46] .
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