Search bioRxivSearch

bioRxiv · 10.1101/193649

Quantifying ethical tradeoffs for vaccine efficacy trials during severe epidemics

Abstract

BackgroundDuring emerging epidemics of highly fatal diseases, rapid development and testing of new vaccines may be critical to curbing transmission and saving lives. However, the design of vaccine efficacy trials in such contexts may face considerable logistical, epidemiological, or ethical impediments. Three different vaccine efficacy trials were conducted during the 2014-2016 Ebola virus epidemic in West Africa, each with different designs. At the time, there was vigorous debate on the tradeoff between a trials ability to yield information of scientific and societal value versus the perceived ethical dilemma of withholding potentially life-saving vaccines from control participants. Whereas the scientific value of a trial is often estimated in terms of statistical power, speed, and rigor, we lack similar metrics for the ethical costs of withholding interventions.\n\nMethods and FindingsHere, we introduce a conceptual framework that fills this gap and allows quantitative assessment of both the scientific value of a study and the risks incurred by trial participants. We show that even untested vaccines against severe diseases may be probabilistically beneficial--i.e. after accounting for realistic uncertainty in their safety and efficacy, trial participants are expected to be better off vaccinated than not. While accounting for this uncertainty, we estimate trial participant risk under a hypothetical, idealized vaccine rollout scenario and compare it to risk under various candidate trial designs, in order to elucidate specific quantitative tradeoffs between cumulative risk to trial participants and information gained. Through an illustrative simulation example, we highlight specific trial-design modifications that allow for conscientious balance between minimizing participant risk and acquiring information of societal value. These include modifications that affect the speed with which a trial would detect an efficacious vaccine (greater sample size or enrollment rate, interim analyses, or risk-prioritized vaccine rollout), which leads to earlier vaccination of control participants should the vaccine be efficacious, and those that systematically limit the risk \"spent\" by unvaccinated individuals (e.g., providing vaccination to controls after a delay, or presumptive vaccination of subjects above a risk threshold).\n\nConclusionWe advocate this conceptual approach as a means of clarifying the tensions between opposing viewpoints and facilitating transparent discussion to aid ethical and efficient responses to future emerging epidemics.

Explore related subjects

Keep this discovery

BibTeXRIS

Bellan, S. E., Pulliam, J. R. C., van der Graaf, R., Fox, S. J., Dushoff, J., Meyers, L. A.. 2017-09-28. Quantifying ethical tradeoffs for vaccine efficacy trials during severe epidemics. https://doi.org/10.1101/193649

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Translating surveillance data into incidence estimates

Monitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence, i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

epidemiology

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology

Perfect Counterfactuals for Epidemic Simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a single world approach to matching simulations of controlled epidemics to their exact uncontrolled counterfac-tual. Our method borrows concepts from percolation approaches prune out possible epidemic histories and create potential epidemic graph that can be realized to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models, and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids non-sensical inferences.

epidemiology