Abstract #301124

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JSM 2003 Abstract #301124
Activity Number: 369
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #301124
Title: New Methods for the Estimation of Influenza Antiviral Agent Efficacy
Author(s): Yang Yang*+
Companies: Emory University
Address: 1423 Druid Valley Dr., Atlanta, GA, 30329,
Keywords: efficacy ; randomization ; maximum likelihood ; log-linear model ; EM algorithm
Abstract:

The typical randomized trial design for influenza antiviral agents is as follows: Households are enrolled and followed prospectively. When the first case of influenza appears in the household, then either the drug or placebo is randomly assigned to that index case and the other exposed members. The antiviral efficacy is then measured from the resulting data. Currently, it is unclear if randomization should be on a household or individual level, and whether we need to use information on all the initially enrolled households or just those with one or more cases. Maximum likelihood and log-linear models are applied to estimate both antiviral efficacy for susceptibility and antiviral efficacy for infectiousness, while taking the different designs and misclassification into account. For the log-linear modeling approach, we develop an EM algorithm competitive with the maximum likelihood approach but easier to implement. We find that only using households with one or more cases is almost as efficient as using all households in the study. In addition, individual-level randomization is more efficient than household-level randomization regardless of how households are ascertained.

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