Use of Simulation to Aid Design of Clinical Trials During Infectious Disease Outbreaks
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Hitchings, Matthew
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Clinical trials for infectious diseases conducted during epidemics are complicated by the unpredictable nature of outbreaks and dynamic effects arising from disease transmission. Mathematical models can be used to understand how trials carried out under different circumstances will perform, and the findings can be incorporated into future trial design. One challenge is making sample size calculations based on incidence within the trial, direct and indirect vaccine effects, and intracluster correlation. These parameters determine the relative efficiency of individually randomized (iRCTs) and cluster-randomized controlled trials (cRCTs) in the same population, as well as the efficiency of cRCTs with varying size and number of clusters. Modeling can be used to supplement trial results and explore the intervention beyond the scope of the trial.Firstly, I present a model for a delayed-arm ring vaccination cRCT. Secondly, I simulate trials conducted in a collection of small communities to assess how indirect protection and clustering affect the power of cRCTs and iRCTs during an epidemic. Finally, I simulate antibiotic prophylaxis strategies using data from a meningitis outbreak in Niger, and estimate the power of trials conducted during this outbreak.
The measured vaccine effect and power of the ring vaccination trial is sensitive to properties of the vaccine, to setting-specific parameters, and to parameters determined by the study design. Across diverse parameters, within the same trial population, cRCTs are never more powerful than iRCTs, although the difference can be small. I identify two effects that attenuate the loss of cRCT power associated with increased cluster size. First, if enrollment of fewer, larger clusters is performed to achieve higher vaccine coverage within vaccinated communities, this increases the effect to be measured and, consequently, power. Second, the greater rate of imported transmission in larger communities may increase the attack rate and similarly mitigate loss of power relative to a trial in many, smaller communities. Finally, household prophylaxis does not reduce the burden of meningitis at the population level, but village-wide prophylaxis can target up to 20% of suspected cases. Trials conducted during the epidemic would have had limited power to detect the effect of prophylaxis on disease incidence.
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