Exploring Risks of Human Challenge Trials For COVID‐19
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Abstract
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.
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SciScore for 10.1101/2020.11.19.20234658: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:4.2 Limitations: Finally, it is important to note that our model does have limitations. Hospitalization rates and death for 20-30 year olds are rare; our prior knowledge on fatalities for this group are more uncertain due to limited data. Information on long-term damage caused by COVID-19 is similarly incomplete, and though this is discussed further below, our model does not currently account for that risk. Also note that although our …
SciScore for 10.1101/2020.11.19.20234658: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:4.2 Limitations: Finally, it is important to note that our model does have limitations. Hospitalization rates and death for 20-30 year olds are rare; our prior knowledge on fatalities for this group are more uncertain due to limited data. Information on long-term damage caused by COVID-19 is similarly incomplete, and though this is discussed further below, our model does not currently account for that risk. Also note that although our model uses hospitalization as a proxy for the upper bound of serious nonfatal COVID-19 cases, more data is required to see if this is an accurate assumption. Finally, our model may not accurately capture changes in COVID-19 risks over time. It also does not estimate any indirect risks of the study. We stress that our model is not a comprehensive analysis of all available risks, but rather a tool quantifying certain known risks that can be used by trial participants and policymakers. 4.3 Non-modeled Risks: We also note that there are several impacts we do not model in the study, most notably the concern about so-called Long-COVID, which is a catch-all term referring to a combination of persistent symptoms, i.e. slow recovery, and new post-recovery symptoms[7]. It is understood that for some cases, especially severe ones, recovery from COVID-19 can take months. In others, there are longer-term symptoms differing from those experienced during the infection, perhaps similar to Post-SARS syndrome[34, 27]. At the same time, COVID-19 recovery has been ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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