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Coronavirus Human Infection Challenge Studies: Assessing Potential Benefits and Risks
Euzebiusz Jamrozik1,2, George S Heriot3, Michael J Selgelid4
1Monash Bioethics Centre, Monash University, Melbourne, Australia. zeb.jamrozik@monash.edu.
Journal of Bioethical Inquiry
|August 26, 2020
Summary
Human infection challenge studies (HCS) for SARS-CoV-2 accelerate vaccine development. Ethical review requires systematic risk-benefit analysis, considering public health and participant safety.
Area of Science:
- Infectious Diseases
- Vaccinology
- Bioethics
Background:
- Human infection challenge studies (HCS) are proposed to expedite SARS-CoV-2 vaccine development.
- Ethical acceptability of SARS-CoV-2 HCS hinges on a favorable risk-benefit balance.
- Systematic risk-benefit assessments are crucial for public trust in research and vaccines.
Purpose of the Study:
- To explore considerations for systematic risk-benefit assessments of SARS-CoV-2 HCS.
- To detail potential benefits of SARS-CoV-2 HCS, including accelerated vaccine development.
- To identify the need for modeling in ethical evaluations of HCS.
Main Methods:
- Review of ethical considerations for human infection challenge studies.
- Identification of key benefits associated with SARS-CoV-2 HCS.
- Exploration of modeling applications for risk-benefit analysis in HCS.
Main Results:
- Potential benefits of SARS-CoV-2 HCS, particularly in accelerating vaccine development, are detailed.
- Modeling is identified as essential for comparing HCS with field trials and estimating participant risks.
- Interactions between public health policy and research priorities are highlighted.
Conclusions:
- Systematic risk-benefit assessments are vital for the ethical conduct of SARS-CoV-2 HCS.
- Modeling can enhance ethical evaluations by comparing study types and quantifying risks.
- Balancing competing ethical considerations is necessary for research ethics review.
Keywords:
Background riskCOVID-19Controlled human infection modelCoronavirusHuman challenge studiesInfectious diseaseModellingResearch EthicsRisk
