Operationalizing International Regulatory Standards in a Limited-Resource Setting During an Epidemic: The Sierra Leone Trial to Introduce a Vaccine Against Ebola (STRIVE) Experience

Kabineh, Abdul Karim; Carr, Wendy; Motevalli, Mahnaz; Legardy-Williams, Jennifer; Vincent, W S Wong; Mahon, Barbara E.; Samai, Mohamed

doi:10.1093/infdis/jiy111

Cited by 4 publications

(2 citation statements)

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“…Many sites across multiple countries also require considerable logistical effort to communicate among sites. These challenges have been noted in a previous Ebola vaccine trial [47]. Ultimately, selecting suitable sites for chikungunya vaccine efficacy trials is a multifaceted problem and the modeling framework we proposed here can act as a screening tool so that the sites it recommends can be further scrutinized according to other criteria, as well.…”

Section: Discussionmentioning

confidence: 96%

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

Tran

Soda

Siraj

et al. 2022

Preprint

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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.

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Section: Discussionmentioning

confidence: 96%

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

Tran

Soda

Siraj

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Practical considerations include the availability of technical support, records maintenance, cold chain storage, and commitment from regulatory authorities to a speedy and high quality review. 17 Model projected incidence is thus viewable as one factor among a larger set that must be weighed together. One strategy is to use models as a first step to screen sites that is then followed by site visits to explore logistical capacity, collect additional surveillance data, or conduct a baseline serosurvey to better understand risk.…”

Section: Discussionmentioning

confidence: 99%

Using simulated infectious disease outbreaks to inform site selection and sample size for individually randomized vaccine trials during an ongoing epidemic

et al. 2021

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Background: Novel strategies are needed to make vaccine efficacy trials more robust given uncertain epidemiology of infectious disease outbreaks, such as arboviruses like Zika. Spatially resolved mathematical and statistical models can help investigators identify sites at highest risk of future transmission and prioritize these for inclusion in trials. Models can also characterize uncertainty in whether transmission will occur at a site, and how nearby or connected sites may have correlated outcomes. A structure is needed for how trials can use models to address key design questions, including how to prioritize sites, the optimal number of sites, and how to allocate participants across sites. Methods: We illustrate the added value of models using the motivating example of Zika vaccine trial planning during the 2015–2017 Zika epidemic. We used a stochastic, spatially resolved, transmission model (the Global Epidemic and Mobility model) to simulate epidemics and site-level incidence at 100 high-risk sites in the Americas. We considered several strategies for prioritizing sites (average site-level incidence of infection across epidemics, median incidence, probability of exceeding 1% incidence), selecting the number of sites, and allocating sample size across sites (equal enrollment, proportional to average incidence, proportional to rank). To evaluate each design, we stochastically simulated trials in each hypothetical epidemic by drawing observed cases from site-level incidence data. Results: When constraining overall trial size, the optimal number of sites represents a balance between prioritizing highest-risk sites and having enough sites to reduce the chance of observing too few endpoints. The optimal number of sites remained roughly constant regardless of the targeted number of events, although it is necessary to increase the sample size to achieve the desired power. Though different ranking strategies returned different site orders, they performed similarly with respect to trial power. Instead of enrolling participants equally from each site, investigators can allocate participants proportional to projected incidence, though this did not provide an advantage in our example because the top sites had similar risk profiles. Sites from the same geographic region may have similar outcomes, so optimal combinations of sites may be geographically dispersed, even when these are not the highest ranked sites. Conclusion: Mathematical and statistical models may assist in designing successful vaccination trials by capturing uncertainty and correlation in future transmission. Although many factors affect site selection, such as logistical feasibility, models can help investigators optimize site selection and the number and size of participating sites. Although our study focused on trial design for an emerging arbovirus, a similar approach can be made for any infectious disease with the appropriate model for the particular disease.

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Dynamics of a non-smooth epidemic model with three thresholds

2019

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Operationalizing International Regulatory Standards in a Limited-Resource Setting During an Epidemic: The Sierra Leone Trial to Introduce a Vaccine Against Ebola (STRIVE) Experience

Abstract: ClinicalTrials.gov [NCT02378753] and Pan African Clinical Trials Registry [PACTR201502001037220].

Cited by 4 publications

References 6 publications

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

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

Using simulated infectious disease outbreaks to inform site selection and sample size for individually randomized vaccine trials during an ongoing epidemic

Dynamics of a non-smooth epidemic model with three thresholds

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