Selected article for: "bayesian framework and population size"
Author: Eifan, Saleh A.; Nour, Islam; Hanif, Atif; Zamzam, Abdelrahman M.M.; AlJohani, Sameera Mohammed
Title: A pandemic risk assessment of middle east respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia
  • Document date: 2017_6_6
    • ID: sk2n2gxw_12
    Snippet: S is the average number of susceptibles at time t, I is the average number of infections, N is the size of the population, which decreases due to disease-induced deaths, b is the contact rate (Bettencourt and Ribeiro, 2008) . After an average residence time c À1 , infectious individuals recover or die. The Bayesian procedure is engaged to convert time series of case numbers to a probability distribution. The proposed algorithm, described in a Ba.....
    Document: S is the average number of susceptibles at time t, I is the average number of infections, N is the size of the population, which decreases due to disease-induced deaths, b is the contact rate (Bettencourt and Ribeiro, 2008) . After an average residence time c À1 , infectious individuals recover or die. The Bayesian procedure is engaged to convert time series of case numbers to a probability distribution. The proposed algorithm, described in a Bayesian framework, started with a non-informative prior on the distribution of the reproduction number R ( fig. 1) .

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