Selected article for: "case detection and overdispersion parameter"
Author: Cauchemez, Simon; Epperson, Scott; Biggerstaff, Matthew; Swerdlow, David; Finelli, Lyn; Ferguson, Neil M.
Title: Using Routine Surveillance Data to Estimate the Epidemic Potential of Emerging Zoonoses: Application to the Emergence of US Swine Origin Influenza A H3N2v Virus
  • Document date: 2013_3_5
    • ID: 16c8dwfq_30
    Snippet: If the detection of a case does not affect detection of other cases from the same cluster (surveillance scenario 1), we find that R can be simply estimated as R = 12G, where G is the proportion of detected cases that are infected by the reservoir. This is a general result that is independent of the case detection rate r and the overdispersion parameter k and that does not require data on clusters. It is valid as long as outbreaks are subcritical .....
    Document: If the detection of a case does not affect detection of other cases from the same cluster (surveillance scenario 1), we find that R can be simply estimated as R = 12G, where G is the proportion of detected cases that are infected by the reservoir. This is a general result that is independent of the case detection rate r and the overdispersion parameter k and that does not require data on clusters. It is valid as long as outbreaks are subcritical (0,R,1).

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