Evidence map›Paper›PMID 24204214›Full record

ArticlePLoS medicine2013

Complexity in mathematical models of public health policies: a guide for consumers of models.

Sanjay Basu, Jason Andrews

Abstract read
In one paragraph

Article in PLoS medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Projecting the Impact and Costs of Near Point-of-Care Tuberculosis Screening Assays in Community-based Active Case Finding.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
    Article
  3. Review
  4. Article
  5. Mathematical modelling for pandemic preparedness in Canada: Learning from COVID-19.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. A Data-informed Public Health Policy-Makers Platform.International journal of environmental research and public health · 2020
    Article
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

2 authors.

Sanjay BasuPrevention Research Center, Stanford University, Stanford, California, United States of America ; Centers for Health Policy, Primary Care and Outcomes Research, Stanford University, Stanford, California, United States of America ; Center for Poverty and Inequality, Stanford University, Stanford, California, United States of America ; Department of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Jason Andrews

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sanjay Basu and colleagues explain how models are increasingly used to inform public health policy yet readers may struggle to evaluate the quality of models. All models require simplifying assumptions, and there are tradeoffs between creating models that are more "realistic" versus those that are grounded in more solid data. Indeed, complex models are not necessarily more accurate or reliable simply because they can more easily fit real-world data than simpler models can. Please see later in the article for the Editors' Summary.

Indexed as

Models, TheoreticalHealth PolicyHumansPublic Health

Identifiers

PMID24204214
PMCPMC3812083

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.