Evidence map›Paper›PMID 32840856›Full record

ArticleJournal of bioethical inquiry2020

Coronavirus Human Infection Challenge Studies: Assessing Potential Benefits and Risks.

Euzebiusz Jamrozik, George S Heriot, Michael J Selgelid

Abstract read
In one paragraph

Article in Journal of bioethical inquiry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Euzebiusz JamrozikMonash Bioethics Centre, Monash University, Melbourne, Australia. zeb.jamrozik@monash.edu.ORCID http://orcid.org/0000-0001-5940-602X
George S HeriotSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Michael J SelgelidMonash Bioethics Centre, Monash University, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human infection challenge studies (HCS) have been proposed as a means to accelerate SARS-CoV2 vaccine development and thereby help to mitigate a prolonged global public health crisis. A key criterion for the ethical acceptability of SARS-CoV2 HCS is that potential benefits outweigh risks. Although the assessment of risks and benefits is meant to be a standard part of research ethics review, systematic comparisons are particularly important in the context of SARS-CoV2 HCS in light of the significant potential benefits and harms at stake as well as the need to preserve public trust in research and vaccines. In this paper we explore several considerations that should inform systematic assessment of SARS-CoV-2 HCS. First, we detail key potential benefits of SARS-CoV-2 HCS including, but not limited to, those related to the acceleration of vaccine development. Second, we identify where modelling is needed to inform risk-benefit (and thus ethical) assessments. Modelling will be particularly useful in (i) comparing potential benefits and risks of HCS with those of vaccine field trials under different epidemiological conditions and (ii) estimating marginal risks to HCS participants in light of the background probabilities of infection in their local community. We highlight interactions between public health policy and research priorities, including situations in which research ethics assessments may need to strike a balance between competing considerations.

Indexed as

COVID-19Viral VaccinesDrug DevelopmentHumansPandemicsPublic HealthResearch DesignRisk AssessmentSARS-CoV-2Viral VaccinesBackground riskControlled human infection modelCoronavirusCOVID-19Human challenge studiesInfectious diseaseModellingResearch EthicsRisk

Identifiers

PMID32840856
PMCPMC7445815

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.