Selected article for: "mean binomial distribution and negative mean binomial distribution"
Author: Worden, Lee; Wannier, Rae; Hoff, Nicole A.; Musene, Kamy; Selo, Bernice; Mossoko, Mathias; Okitolonda-Wemakoy, Emile; Muyembe Tamfum, Jean Jacques; Rutherford, George W.; Lietman, Thomas M.; Rimoin, Anne W.; Porco, Travis C.; Kelly, J. Daniel
Title: Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019
  • Document date: 2019_8_5
    • ID: 1lg2203q_19
    Snippet: We simulated EBOV transmission using a stochastic branching process model, in which the number of secondary cases caused by any given primary case is drawn from a negative binomial distribution, whose mean is the reproduction number R as a function of day of the outbreak, and variance is controlled by a dispersion parameter k [32, 33] . All transmission events were assumed to be independent. The interval between date of detection of each primary .....
    Document: We simulated EBOV transmission using a stochastic branching process model, in which the number of secondary cases caused by any given primary case is drawn from a negative binomial distribution, whose mean is the reproduction number R as a function of day of the outbreak, and variance is controlled by a dispersion parameter k [32, 33] . All transmission events were assumed to be independent. The interval between date of detection of each primary case and that of each of its secondary cases is assumed gamma distributed with mean 14.5 days and standard deviation 5 days, rounded to the nearest whole number of days, as above.

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