Outbreaks of emerging pathogens have become more frequent, and we will likely face future epidemics for which we are not adequately prepared. Effective vaccines are a critical tool for controlling infectious disease threats, but experimental products must be rigorously evaluated for efficacy and safety before they can be licensed and deployed. Our experience with the 2013-2016 West African Ebola epidemic highlighted the unique challenges of conducting phase III vaccine efficacy trials for emerging pathogens. Besides issues of strained infrastructure in typically resource-limited settings, incidence may be highly heterogeneous in the population and spatiotemporally hard to predict. The outbreak may end before enough cases have accrued to establish efficacy, as occurred in two of the three phase III Ebola vaccine trials. Compared to standard vaccine clinical trials, researchers conducting trials during public health emergencies also generally have less information about the disease and/or vaccine. We supported the design and analysis of a third phase III Ebola vaccine trial in Guinea that used a novel ring vaccination approach. Modeled after the strategy used to eradicate smallpox, clusters were defined as the contacts and contacts of contacts of laboratory-confirmed Ebola virus disease cases and then cluster- randomized to immediate or delayed vaccination. This trial demonstrated high efficacy of the candidate vaccine, and its success was in part attributed to its innovative, responsive strategy that tracked the epidemic as it progressed, precisely targeting individuals at highest risk of exposure. These experiences have motivated an international call for novel methods for vaccine trial design and analysis adapted for emerging infectious disease threats. We propose the development of flexible, adaptive trial design strategies intended to increase the efficiency and likelihood of success when evaluating experimental vaccines in outbreak settings.
Our first aim i s to develop a class of responsive designs and associated tools for sample size calculation and analysis generalized beyond ring vaccination.
Our second aim i s to outline strategies for implementing trials in outbreaks of unpredictable duration, including how to define data monitoring rules and how to aggregate information across outbreaks when any given outbreak is too small to support a trial.
Our third aim i s to design adaptive, multi-arm vaccine trials with or without a control comparator. For each aim, we will describe the designs and the relevant qualitative considerations, develop and validate the supporting statistical methods, and evaluate their robustness using realistic, mathematical and computational disease transmission models. Our research represents a critical first step for evaluating these strategies before they could be implemented in the field.

Public Health Relevance

There are unique and important challenges associated with implementing vaccine efficacy trials for emerging infectious diseases. We propose a series of flexible vaccine trial design strategies tailored to settings with unpredictable spatiotemporal disease incidence, including unknown outbreak duration, and supporting simultaneous evaluation of multiple vaccine candidates. We will describe these approaches, develop the associated statistical methods for trial design and analysis, and evaluate their robustness using data-driven mathematical and computational models.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
1R01AI139761-01
Application #
9576709
Study Section
Infectious Diseases, Reproductive Health, Asthma and Pulmonary Conditions Study Section (IRAP)
Program Officer
Repik, Patricia M
Project Start
2018-08-15
Project End
2023-07-31
Budget Start
2018-08-15
Budget End
2019-07-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Florida
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
969663814
City
Gainesville
State
FL
Country
United States
Zip Code
32611