Evidence map›Paper›PMID 26546234›Full record

ReviewInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2016

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.

Gwenan M Knight, Nila J Dharan, Gregory J Fox, Natalie Stennis, Alice Zwerling, Renuka Khurana, David W Dowdy

Abstract readReview
In one paragraph

Review in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Effects of the COVID-19 Pandemic on Tuberculosis Outcomes in the United States: A Bayesian Analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Potential Effects of the Coronavirus Disease 2019 (COVID-19) Pandemic on Human Immunodeficiency Virus (HIV) Transmission: A Modeling Study in 32 US Cities.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  18. Article
  19. Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions.Ecological applications : a publication of the Ecological Society of America · 2021
    Article
  20. 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

7 authors.

Gwenan M KnightNational Institute for Health Research Health Protection Research Unit in Healthcare Associated Infection and Antimicrobial Resistance, Imperial College London, 8(th) floor Commonwealth Building, Hammersmith Hospital Campus, Du Cane Road, London, W12 0HS, UK; TB Modelling Group, TB Centre, Centre for Mathematical Modelling, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. Electronic address: g.knight@imperial.ac.uk.
Nila J DharanNew Jersey Medical School - Rutgers, the State University of New Jersey, Newark, New Jersey, USA.
Gregory J FoxRespiratory Epidemiology Clinical Research Unit, McGill University, Montreal, Quebec, Canada.
Natalie StennisNew York City Department of Health and Mental Hygiene, Bureau of Tuberculosis Control, New York, New York, USA.
Alice ZwerlingDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Renuka KhuranaMaricopa County Department of Public Health, Clinical Services, Phoenix, Arizona, USA.
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

Funding

A User-Friendly Epidemic-Economic Model of Diagnostic Tests for TuberculosisR21AI101152 · NIAID · JOHNS HOPKINS UNIVERSITY · PI DOWDY, DAVID WESLEY · 2012 to 2013
$433k
NIAID NIH HHS R21 AI101152
6 · The paper itself

Abstract

The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions.

Indexed as

Decision MakingPublic HealthCommunicable DiseasesHumansModels, TheoreticalModelsPublic health practicetheoreticalTuberculosis

Identifiers

PMID26546234
PMCPMC4996966

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.