Selected article for: "binomial distribution and secondary infection"
Author: de Silva, Eric; Ferguson, Neil M.; Fraser, Christophe
Title: Inferring pandemic growth rates from sequence data
  • Document date: 2012_8_7
    • ID: 1piyoafd_17
    Snippet: Following on from Lloyd-Smith et al. [19] and Grassly & Fraser [20] , we introduce the individual reproductive number, n, which is the expected number of secondary cases caused by a specific infected individual. If n is gamma-distributed having a mean R and dispersion parameter k, then the number of secondary infections caused by each infected individual is Poisson distributed with mean n, and thus overall the number of secondary infections gener.....
    Document: Following on from Lloyd-Smith et al. [19] and Grassly & Fraser [20] , we introduce the individual reproductive number, n, which is the expected number of secondary cases caused by a specific infected individual. If n is gamma-distributed having a mean R and dispersion parameter k, then the number of secondary infections caused by each infected individual is Poisson distributed with mean n, and thus overall the number of secondary infections generated by a single infection is given by a negative binomial offspring distribution. The probability p(m) of obtaining m from a negative binomial distribution with parameters p and k is given by:

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