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Activity Number: 70
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #319252
Title: Falsification of Epidemiological Models from Ongoing Clinical Trials
Author(s): Sayan Dasgupta* and Jim P. Hughes
Companies: Fred Hutchinson Cancer Research Center and University of Washington
Keywords: Falsification ; Validation ; Epidemiological Model ; HIV

Complex, dynamic models of infectious diseases can be used to understand the transmission dynamics of the disease, project the course of an epidemic, predict the effect of interventions and/or provide information for power calculations of community level intervention studies. However, there have been relatively few opportunities to rigorously evaluate (and validate) the predictions of such models till now, due to the lack of high quality population-level disease incidence data. Recently, several community level randomized trials of combination HIV intervention have been planned and/or initiated. In each case, significant epidemic modeling efforts were conducted during trial planning and were integral to the design of these trials. Each of these models has been designed to predict trial results for a specific setting, and these provide a unique opportunity to evaluate the usefulness of these models for their specific goals. In this project, we pursue to build a framework for evaluating the predictions of complex epidemiological models and describe experiments that can be used to test this framework, prior to the completion of the ongoing trials such as the HPTN 071 (PopART) study.

Authors who are presenting talks have a * after their name.

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