Exploring Risks of Human Challenge Trials for COVID-19

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.