Evidence map›Paper›PMID 38303993›Full record

ArticleInfectious Disease Modelling2024

Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model.

Ashley N Micuda, Mark R Anderson, Irina Babayan, Erin Bolger, Logan Cantin, Gillian Groth, Ry Pressman-Cyna, Charlotte Z Reed, Noah J Rowe, Mehdi Shafiee and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infectious Disease Modelling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Ashley N MicudaDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Mark R AndersonDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Irina BabayanDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Erin BolgerDepartment of Mathematics and Statistics, Queen's University, Kingston, ON, Canada.
Logan CantinSchool of Computing, Queen's University, Kingston, ON, Canada.
Gillian GrothDepartment of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.
Ry Pressman-CynaDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Charlotte Z ReedDepartment of Mathematics and Statistics, Queen's University, Kingston, ON, Canada.
Noah J RoweDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Mehdi ShafieeDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Benjamin TamDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Marie C VidalDepartment of Physics, Stanford University, Stanford, CA, United States.
Tianai YeDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
Ryan D MartinDepartment of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work introduces the Queen's University Agent-Based Outbreak Outcome Model (QUABOOM). This tool is an agent-based Monte Carlo simulation for modelling epidemics and informing public health policy. We illustrate the use of the model by examining capacity restrictions during a lockdown. We find that public health measures should focus on the few locations where many people interact, such as grocery stores, rather than the many locations where few people interact, such as small businesses. We also discuss a case where the results of the simulation can be scaled to larger population sizes, thereby improving computational efficiency.

Indexed as

Agent-based epidemic modellingBasic reproductive numberCOVID-19Monte-carloPublic healthSmall business capacity restrictions

Identifiers

PMID38303993
PMCPMC10831812

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.