Human challenge trials (HCTs) are a potential method to accelerate development of vaccines and therapeutics. However, HCTs for COVID‐19 pose ethical and practical challenges, in part due to the unclear and developing risks. In this article , we introduce an interactive model for exploring some risks of a severe acute respiratory syndrome coronavirus‐2 (SARS‐COV‐2) dosing study, a prerequisite for any COVID‐19 challenge trials. The risk estimates we use are based on a Bayesian evidence synthesis model which can incorporate new data on infection fatality risks (IFRs) to patients, and infer rates of hospitalization. The model estimates individual risk, which we then extrapolate to overall mortality and hospitalization risk in a dosing study. We provide a web tool to explore risk under different study designs. Based on the Bayesian model, IFR for someone between 20 and 30 years of age is 15.1 in 100,000, with a 95% uncertainty interval from 11.8 to 19.2, while risk of hospitalization is 130 per 100,000 (100–160). However, risk will be reduced in an HCT via screening for comorbidities, selecting lower‐risk population, and providing treatment. Accounting for this with stronger assumptions, we project the fatality risk to be as low as 2.5 per 100,000 (1.6–3.9) and the hospitalization risk to be 22.0 per 100,000 (14.0–33.7). We therefore find a 50‐person dosing trial has a 99.74% (99.8–99.9%) chance of no fatalities, and a 98.9% (98.3–99.3%) probability of no cases requiring hospitalization.
Human Challenge Trials (HCTs) are a potential method to accelerate development of vaccines and therapeutics. However, HCTs for COVID-19 pose ethical and practical challenges, in part due to the unclear and developing risks. In this paper, we introduce an interactive model for exploring some risks of a SARS-COV-2 dosing study, a prerequisite for any COVID-19 challenge trials. The risk estimates we use are based on a Bayesian evidence synthesis model which can incorporate new data on infection fatality rates (IFRs) to patients, and infer rates of hospitalization. We have also created a web tool to explore risk under different study design parameters and participant scenarios. Finally, we use our model to estimate individual risk, as well as the overall mortality and hospitalization risk in a dosing study.Based on the Bayesian model we expect IFR for someone between 20 and 30 years of age to be 17.5 in 100,000, with 95% uncertainty interval from 12.8 to 23.6. Using this estimate, we find that a simple 50-person dosing trial using younger individuals has a 99.1% (95% CI: 98.8% to 99.4%) probability of no fatalities, and a 92.8% (95% CI: 90.3% to 94.6%) probability of no cases requiring hospitalization. However, this IFR will be reduced in an HCT via screening for comorbidities, as well as providing medical care and aggressive treatment for any cases which occur, so that with stronger assumptions, we project the risk to be as low as 3.1 per 100,000, with a 99.85% (95% CI: 99.7% to 99.9%) chance of no fatalities, and a 98.7% (95% CI: 97.4% to 99.3%) probability of no cases requiring hospitalization.
In human challenge trials, volunteers are deliberately infected with a pathogen to accelerate vaccine development and answer key scientific questions. In the U.S., preparations for challenge trials with the novel coronavirus are complete, and in the U.K., challenge trials have recently begun. However, ethical concerns have been raised about the potential for invalid consent or exploitation. These concerns largely reflect worries that challenge trial volunteers may be unusually risk-seeking or too economically vulnerable to refuse the payments these trials provide, rather than being motivated primarily by altruistic goals. We conducted the first large-scale survey of intended human challenge trial volunteers and found that SARS-CoV-2 challenge trial volunteers exhibit high levels of altruistic motivations without any special indication of poor risk perception or economic vulnerability. Findings indicate that challenge trials with the novel coronavirus can attract volunteers with background conditions, attitudes, and motivations that should allay key ethical concerns.
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