Evidence map›Paper›PMID 23690585›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Identifying dynamic tuberculosis case-finding policies for HIV/TB coepidemics.

Reza Yaesoubi, Ted Cohen

Registry-linked trialAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04094350 (Effect of Community Active Case Finding Strategies for Detection of Tuberculosis in Cambodia), which is not on this map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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.

NCT04094350 nacompletednot on this mapstarted 2019, after this paper: background citation

Effect of Community Active Case Finding Strategies for Detection of Tuberculosis in Cambodia: Study Protocol for a Pragmatic Cluster Randomized Controlled Trial

TypeinterventionalSponsorNational University of SingaporeRan2019 to 2022Enrolled2,004ConditionsTuberculosisArmsACF with a seed-and-recruit model, ACF targeting household and neighborhood contacts, ACF targeting the older population using mobile screening units, Passive case finding
3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Adaptive Policies to Balance Health Benefits and Economic Costs of Physical Distancing Interventions during the COVID-19 Pandemic.Medical decision making : an international journal of the Society for Medical Decision Making · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Permutations of time and place in tuberculosis.The Lancet. Infectious diseases · 2015
    Review
  17. Article
  18. Article
  19. 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

2 authors.

Reza YaesoubiDepartment of Epidemiology and the Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA 02115, USA. reza.yaesoubi@gmail.com
Ted Cohen

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Prevalence, risk factors and consequences of complex M. Tuberculosis infectionsDP2OD006663 · OD · BRIGHAM AND WOMEN'S HOSPITAL · PI COHEN, THEODORE H · 2010 to 2010
$2.7M
NIGMS NIH HHS U54 GM088558NIGMS NIH HHS U54GM088558NIH HHS DP2 OD006663NIH HHS DP2OD006663
6 · The paper itself

Abstract

The global tuberculosis (TB) control plan has historically emphasized passive case finding (PCF) as the most practical approach for identifying TB suspects in high burden settings. The success of this approach in controlling TB depends on infectious individuals recognizing their symptoms and voluntarily seeking diagnosis rapidly enough to reduce onward transmission. It now appears, at least in some settings, that more intensified case-finding (ICF) approaches may be needed to control TB transmission; these more aggressive approaches for detecting as-yet undiagnosed cases obviously require additional resources to implement. Given that TB control programs are resource constrained and that the incremental yield of ICF is expected to wane over time as the pool of undiagnosed cases is depleted, a tool that can help policymakers to identify when to implement or suspend an ICF intervention would be valuable. In this article, we propose dynamic case-finding policies that allow policymakers to use existing observations about the epidemic and resource availability to determine when to switch between PCF and ICF to efficiently use resources to optimize population health. Using mathematical models of TB/HIV coepidemics, we show that dynamic policies strictly dominate static policies that prespecify a frequency and duration of rounds of ICF. We also find that the use of a diagnostic tool with better sensitivity for detecting smear-negative cases (e.g., Xpert MTB/RIF) further improves the incremental benefit of these dynamic case-finding policies.

Indexed as

Decision Support TechniquesEpidemicsEpidemiological MonitoringHIV InfectionsHumansModels, TheoreticalPrevalencePublic HealthPublic PolicyTuberculosisapproximate dynamic programmingcost-effectivenessdynamic resource allocationmathematical modelscreening

Identifiers

PMID23690585
PMCPMC3677479

What OpenQuestion holds

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Registered trials

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.