ArticleCanadian journal of public health = Revue canadienne de sante publique2021
Ontario's COVID-19 Modelling Consensus Table: mobilizing scientific expertise to support pandemic response.
Article in Canadian journal of public health = Revue canadienne de sante publique, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled 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.
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
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Formal and informal science-policy interaction during public health emergencies of international concern: a scoping review.BMC global and public health · 2026Pooled it
- Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Pooled it
- The decision uncertainty toolkit: Risk measures and visual outputs to support decision making during public health crises.PloS one · 2025Article
- Lessons learned from COVID-19 modelling efforts for policy decision-making in lower- and middle-income countries.BMJ global health · 2024Article
- Canada's provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses.Canadian journal of public health = Revue canadienne de sante publique · 2024Review
- Mobility changes following COVID-19 stay-at-home policies varied by socioeconomic measures: An observational study in Ontario, Canada.PLOS global public health · 2024Article
- Modelling COVID-19 transmission using IDSIM, an epidemiological-modelling desktop app with multi-level immunization capabilities.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
settingCOVID-19 has highlighted the need for credible epidemiological models to inform pandemic policy. Traditional mechanisms of commissioning research are ill-suited to guide policy during a rapidly evolving pandemic. At the same time, contracting with a single centre of expertise has been criticized for failing to reflect challenges inherent in specific modelling approaches.
interventionThis report describes an alternative approach to mobilizing scientific expertise. Ontario's COVID-19 Modelling Consensus Table (MCT) was created in March 2020 to enable rapid communication of credible estimates of the impact of COVID-19 and to accelerate learning on how the disease is spreading and what could slow its transmission. The MCT is a partnership between the province and academic modellers and consists of multiple groups of experts, health system leaders, and senior decision-makers. Armed with Ministry of Health data, the MCT meets once per week to share results from modelling exercises, generate consensus judgements of the likely future impact of COVID-19, and discuss decision-makers' priorities. OUTCOMES: The MCT has enabled swift access to data for participants, a structure for developing consensus estimates and communicating these to decision-makers, credible models to inform health system planning, and increased transparency in public reporting of COVID-19 data. It has also facilitated the rapid publication of research findings and its incorporation into government policy. IMPLICATIONS: The MCT approach is one way to quickly draw on scientific advice outside of government and public health agencies. Beyond speed, this approach allows for nimbleness as experts from different organizations can be added as needed. It also shows how universities and research institutes have a role to play in crisis situations, and how this expertise can be marshalled to inform policy while respecting academic freedom and confidentiality.
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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.