ArticleJournal of evaluation in clinical practice2020
The first casualty of an epidemic is evidence.
Article in Journal of evaluation in clinical practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- The failure of drug repurposing for COVID-19 as an effect of excessive hypothesis testing and weak mechanistic evidence.History and philosophy of the life sciences · 2022Article
- COVID-19 Mitigation: Individual Freedom Should Not Impede Public Health.American journal of public health · 2021Article
- Back to WHAT? The role of research ethics in pandemic times.Medicine, health care, and philosophy · 2021Article
- Vaccine-enhanced disease: case studies and ethical implications for research and public health.Wellcome open research · 2021Article
- The first casualty of an epidemic is evidence.Journal of evaluation in clinical practice · 2020Article
- SARS-CoV-2 challenge studies: ethics and risk minimisation.Journal of medical ethics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe COVID-19 has posed a wide range of urgent questions: about the disease, testing, immunity, treatments, and outcomes. Extreme situations, such as pandemics, call for exceptional measures. However, this threatens the production and application of evidence.
methodsThis article applies standard categories in epistemology to analyse the pandemic in terms of four kinds of uncertainty: Risk, Fundamental uncertainty, Ignorance, and Ambiguity.
resultsMapping the uncertainties of the pandemic onto the four types of uncertainty directs evidence production towards specific tasks in order to address the challenges of the pandemic: Eliminating ambiguity, being alert to the unknown, and gathering data to estimate risks are crucial to preserve evidence and save lives.
conclusionIn order to avoid fake facts and to provide sustainable solutions, we need to pay attention to the various kinds of uncertainty. Producing high-quality evidence is the solution, not the problem.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.