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Proposal 1374

Title of the Proposed Research

A novel representation of vaccine efficacy trial datasets for use in computer simulation of vaccination policy

Lead Researcher

Michael M. Wagner

Affiliation

University of Pittsburgh

Funding Source

NIH, MIDAS Informatics Services Group (ISG)

Potential Conflicts of Interest

None

Data Sharing Agreement Date

25 May 2016

Lay Summary

BACKGROUND

Computer simulation is important in vaccination policy analysis. It is really the only method available for diseases that are rare (e.g., Brouwers’ 2006 study of smallpox vaccination) or urgent (e.g., Lee’s 2010 study of vaccination policies for 2009 H1N1).

This proposal focuses on a particular method of computer simulation called ‘agent-based simulation’ (ABS), which is the most realistic method for computer simulation of vaccination policy. Briefly, when using ABS to analyze a vaccination policy P, we first create a population of ‘agents’ whose sociodemographic and disease characteristics match those of a population of interest. We then program the simulator to emulate policy P. In particular, we use published data about vaccine efficacy (VE) as the probability that an agent develops immunity as a result of being vaccinated.

A limitation of ABS analysis of vaccination policy is that published results of VE trials typically report a single overall VE, or VE conditioned on one covariate (e.g., age). Thus, ABS’s potential to realistically simulate the effects of co-existing diseases, medications, age, gender and other socio-demographic characteristics of a population is under-used. Thus, the BROAD OBJECTIVE OF THE PROPOSED RESEARCH is to improve the information available about VE for use in ABS analysis of vaccination policy.

IMPACT

We expect that an improvement in information about VE needed for vaccination policy analysis will lead to more effective use of vaccines, and ultimately improvements in health.

OBJECTIVE

The objective of the proposed research is to develop and evaluate using Bayesian Networks (BNs) as a more complete statistical representation of the results of VE trials. Our planned evaluation will study how the more complete statistical information changes the results of ABS simulation of policy.

METHOD

Bayesian Networks: We will use a BN to represent the statistical information in each VE trial dataset. A BN is a compact mathematical representation of the full-joint probability distribution over a set of variables.

Machine learning: We will use standard machine learning algorithms to infer the BN representation of a VE trial dataset.

Probability that an agent become immune during ABS: We will use a standard BN inference algorithm to obtain the VE for each vaccinated agent, conditioned on the agent’s gender and other covariates of VE.

STUDY DESIGN

The study is a comparison of the existing method for releasing results of VE trials (i.e., tables in publications) with a new method that uses a BN representation of a VE trial dataset. As proof of concept, we will compare the number of infections predicted by an ABS vaccination policy analysis that uses published results with that of an analysis that uses the BN representation of the VE trial dataset.

PUBLICATION

We will communicate the results of this research via scientific publication in the field of medical informatics.

Study Data Provided

Study GSK-444563/024: A multi-country & multi-center study to assess the efficacy, immunogenicity & safety of two doses of GSK Biologicals' oral live attenuated HRV vaccine given concomitantly with routine EPI vaccinations including OPV in healthy infants
Study GSK-102247: A multi-country & multi-center study to assess the efficacy, safety & immunogenicity of 2 doses of GSK Biologicals’ oral live attenuated human rotavirus (HRV) vaccine in healthy infants in co-administration with specific childhood vaccines
Study GSK-109810: To assess long-term efficacy & safety of subjects approximately 3 years after priming with 2 doses of GlaxoSmithKline (GSK) Biologicals’ oral live attenuated human rotavirus (HRV) vaccine (Rotarix) in the primary vaccination study (102247).
Study GSK-102248: Multi-Center Study to Assess the Efficacy, Safety and Immunogenicity of 2 or 3 Doses of GSK Biologicals' Oral Live Attenuated Human Rotavirus (HRV) Vaccine Given Concomitantly With Routine EPI Vaccinations in Healthy Infants
Study GSK-104438: A randomized, double-blind, placebo-controlled, post-marketing phase III Study to evaluate the efficacy of GSK Biologicals’ influenza vaccine (Fluarix™) administered intramuscularly in adults.
Study GSK-108134: A study to demonstrate the efficacy of GSK Biologicals’ influenza vaccine (Fluarix™) administered intramuscularly in adults

Statistical Analysis Plan

Publication Citation

The publication citation will be added after the research is published.

Summary Results

Results summary or link will be posted when available.