Selected article for: "data set and effect size"

Author: Andrea Torneri; Amin Azmon; Christel Faes; Eben Kenah; Gianpaolo Scalia Tomba; Jacco Wallinga; Niel Hens
Title: Realized generation times: contraction and impact of infectious period, reproduction number and population size
  • Document date: 2019_3_8
  • ID: ag9mzwkx_8
    Snippet: Baseline scenario 116 We start the investigation of the causes that affect the generation time setting a baseline 117 scenario that representing the dynamic of a stochastic SIR model. In the baseline 118 scenario, we look at the impact of the infectious period, the reproduction number and 119 the population size on the mean backward and forward generation interval using the 120 two aforementioned algorithms. In the forward scheme, the mean genera.....
    Document: Baseline scenario 116 We start the investigation of the causes that affect the generation time setting a baseline 117 scenario that representing the dynamic of a stochastic SIR model. In the baseline 118 scenario, we look at the impact of the infectious period, the reproduction number and 119 the population size on the mean backward and forward generation interval using the 120 two aforementioned algorithms. In the forward scheme, the mean generation interval is 121 calculated within each infector's set of generation times and then used as a single data 122 point per infector to avoid the size biased sampling effect [5] whereas in the backward 123 observation scheme, we attribute the unique generation time to each single infectee. 124 We simulate different epidemics by varying:

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