Evidence map›Paper›PMID 33535889›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2021

The Use and Misuse of Mathematical Modeling for Infectious Disease Policymaking: Lessons for the COVID-19 Pandemic.

Lyndon P James, Joshua A Salomon, Caroline O Buckee, Nicolas A Menzies

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 4 pooled it
–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

58 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. 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 · 2024
    Pooled it
  2. Impact of Structural Differences on the Modeled Cost-Effectiveness of Noninvasive Prenatal Testing.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Pooled it
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  9. Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers' perspective, 2020 to 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
  10. Cross-validation-based sequential design for stochastic models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  11. Challenges and opportunities in uncertainty quantification for healthcare and biological systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
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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

4 authors.

Lyndon P JamesHarvard University, Cambridge, MA, USA.ORCID 0000-0002-8933-2188
Joshua A SalomonCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.
Caroline O BuckeeCenter for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Nicolas A MenziesDepartment of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA.

Funding

Optimal targeting for individual and population-level TB preventionR01AI146555 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI MENZIES, NICOLAS A · 2020 to 2024
$2.5M
NIAID NIH HHS R01 AI146555
6 · The paper itself

Abstract

Mathematical modeling has played a prominent and necessary role in the current coronavirus disease 2019 (COVID-19) pandemic, with an increasing number of models being developed to track and project the spread of the disease, as well as major decisions being made based on the results of these studies. A proliferation of models, often diverging widely in their projections, has been accompanied by criticism of the validity of modeled analyses and uncertainty as to when and to what extent results can be trusted. Drawing on examples from COVID-19 and other infectious diseases of global importance, we review key limitations of mathematical modeling as a tool for interpreting empirical data and informing individual and public decision making. We present several approaches that have been used to strengthen the validity of inferences drawn from these analyses, approaches that will enable better decision making in the current COVID-19 crisis and beyond.

Indexed as

Communicable DiseasesCOVID-19Models, TheoreticalPandemicsPolicyPolicy MakingPublic HealthCommunicable Disease ControlDecision MakingForecastingHumansSARS-CoV-2UncertaintyCOVID-19infectious diseasesmathematical modelinguncertaintyvalidation

Identifiers

PMID33535889
PMCPMC7862917

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.