Evidence map›Paper›PMID 41011777›Full record

ReviewPathogens (Basel, Switzerland)2025

A Flurry of Infectious Disease Modeling Tools During the COVID-19 Pandemic, Considerations for Future Selection.

Jennifer Corbin, Audrey Cerles, Peyton Tebon, Michael Haverkate, Susan Campbell, John Hurst, Rachel Woodul, John Hunzeker, Kierstyn Schwartz-Watjen, Akeisha Owens and 1 more

Abstract readReview
In one paragraph

Review in Pathogens (Basel, Switzerland), 2025. 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

11 authors.

Jennifer CorbinAeris, LLC, Louisville, CO 80027, USA.ORCID 0009-0003-3184-5452
Audrey CerlesGryphon Scientific, Takoma Park, MD 20912, USA.ORCID 0000-0002-7936-4418
Peyton TebonAeris, LLC, Louisville, CO 80027, USA.ORCID 0000-0002-4673-1760
Michael HaverkateGryphon Scientific, Takoma Park, MD 20912, USA.
Susan CampbellGryphon Scientific, Takoma Park, MD 20912, USA.
John HurstGryphon Scientific, Takoma Park, MD 20912, USA.
Rachel WoodulBattelle Memorial Institute, Columbus, OH 43201, USA.
John HunzekerApplied Research Associates (ARA), Albuquerque, NM 87110, USA.
Kierstyn Schwartz-WatjenApplied Research Associates (ARA), Albuquerque, NM 87110, USA.
Akeisha OwensDefense Threat Reduction Agency (DTRA), Fort Belvoir, VA 22060, USA.
Aiguo WuDefense Threat Reduction Agency (DTRA), Fort Belvoir, VA 22060, USA.

Funding

Defense Threat Reduction Agency (DTRA) prime contract HDTRA1-19-D-0007
6 · The paper itself

Abstract

Infectious disease modeling surged during the COVID-19 pandemic, with numerous epidemiological models developed to shape both research and public policy. The abundance of available models-developed with diverse characteristics and modeling objectives-gave users plenty of model selection options; however, little guidance was available for selecting an appropriate epidemiological model. In recognition of this need for guidance, this work describes the development of a decision framework for appropriate model selection. To serve as both an example and a starting point for model users, we walk through the creation and use of a decision framework to evaluate key considerations for selecting a forward-looking epidemiological model intended to inform policy. Our assessment includes 43 models and modeling platforms that have been or could be used to model infectious disease. The framework developed for this assessment focused on assessing each model's strengths and weaknesses in terms of flexibility and customization, the ability to implement pharmaceutical and non-pharmaceutical mitigations, and visualization capabilities. By providing a decision framework and demonstrating its use, we aim to support better decision-making and stronger trust between public health institutions and the constituents they serve.

Indexed as

Communicable DiseasesCOVID-19Epidemiological ModelsHumansPandemicsSARS-CoV-2epidemiological modelsinfectious disease outbreaksmodeling toolsmodel selection

Identifiers

PMID41011777
PMCPMC12472862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.