Selected article for: "branching process model and reproduction number"

Author: Hellewell, Joel; Abbott, Sam; Gimma, Amy; Bosse, Nikos I; Jarvis, Christopher I; Russell, Timothy W; Munday, James D; Kucharski, Adam J; Edmunds, W John; Funk, Sebastian; Eggo, Rosalind M
Title: Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts
  • Document date: 2020_2_28
  • ID: ueb7mjnv_5
    Snippet: We implemented a branching process model, in which the number of potential secondary cases produced by each individual is drawn from a negative binomial distribution with a mean equal to the reproduction number, and heterogeneity in the number of new infections produced by each individual. 6, 15, [17] [18] [19] Each potential new infection was assigned a time of infection drawn from the serial interval distribution. Secondary cases were only crea.....
    Document: We implemented a branching process model, in which the number of potential secondary cases produced by each individual is drawn from a negative binomial distribution with a mean equal to the reproduction number, and heterogeneity in the number of new infections produced by each individual. 6, 15, [17] [18] [19] Each potential new infection was assigned a time of infection drawn from the serial interval distribution. Secondary cases were only created if the person with the infection had not been isolated by the time of infection. As an example (figure 1), a person infected with the virus could potentially produce three secondary infections (because three is drawn from the negative binomial distribution), but only two transmissions might occur before the case is isolated. Thus, in the model, a reduced delay from onset to isolation would reduce the average number of secondary cases.

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