Expected endpoints from future chikungunya vaccine trial sites informed by serological data and modeling

Vaccine. 2023 Jan 4;41(1):182-192. doi: 10.1016/j.vaccine.2022.11.028. Epub 2022 Nov 21.

Abstract

In recent decades, there has been an increased interest in developing a vaccine for chikungunya. However, due to its unpredictable transmission, planning for a chikungunya vaccine trial is challenging. To inform decision making on the selection of sites for a vaccine efficacy trial, we developed a new framework for projecting the expected number of endpoint events at a given site. In this framework, we first accounted for population immunity using serological data collated from a systematic review and used it to estimate parameters related to the timing and size of past outbreaks, as predicted by an SIR transmission model. Then, we used that model to project the infection attack rate of a hypothetical future outbreak, in the event that one were to occur at the time of a future trial. This informed projections of how many endpoint events could be expected if a trial were to take place at that site. Our results suggest that some sites may have sufficient transmission potential and susceptibility to support future vaccine trials, in the event that an outbreak were to occur at those sites. In general, we conclude that sites that have experienced outbreaks within the past 10 years may be poorer targets for chikungunya vaccine efficacy trials in the near future. Our framework also generates projections of the numbers of endpoint events by age, which could inform study participant recruitment efforts.

Keywords: Age-stratified serological data; Hypothetical trial; Mathematical model; Phase-III vaccine trial; Selecting target population; Site selection.

Publication types

  • Systematic Review
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Chikungunya Fever* / epidemiology
  • Chikungunya Fever* / prevention & control
  • Disease Outbreaks / prevention & control
  • Forecasting
  • Humans
  • Vaccines*

Substances

  • Vaccines