Evidence map›Paper›PMID 26162374›Full record

ArticleBMC public health2015

Optimizing strategies for population-based chlamydia infection screening among young women: an age-structured system dynamics approach.

Yu Teng, Nan Kong, Wanzhu Tu

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 30% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. A System Dynamics Simulation Applied to Healthcare: A Systematic Review.International journal of environmental research and public health · 2020
    Pooled it
  2. Article
  3. Article
  4. 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

3 authors at 3 institutions in 1 country.

Yu TengFutures Institute, 41-A New London Tpke, Glastonbury, Connecticut, 06033, USA. tengy03@gmail.com.
Nan KongWeldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr, West Lafayette, Indiana, 47907, USA. nkong@purdue.edu.
Wanzhu TuDepartment of Biostatistics, Indiana University School of Medicine, 410 West 10th St, Suite 3000, Indianapolis, Indiana, 46202, USA. wtu1@iu.edu.
Avenir Health · USIndiana University School of MedicinePurdue University West Lafayette · US

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Statistical Tools For Daily STD/HIV Behavioral ReportsR01HD042404 · NICHD · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI TU, WANZHU · 2004 to 2006
$403k
NCATS NIH HHS UL1 TR001108NICHD NIH HHS R01 HD042404NICHD NIH HHS R01HD042404
6 · The paper itself

Abstract

backgroundChlamydia infection (CT) is one of the most commonly reported sexually transmitted diseases. It is often referred to as a "silent" disease with the majority of infected people having no symptoms. Without early detection, it can progress to serious reproductive and other health problems. Economical identification of asymptomatically infected is a key public health challenge. Increasing evidence suggests that CT infection risk varies over the range of adolescence. Hence, age-dependent screening strategies with more frequent testing for certain age groups of higher risk may be cost-saving in controlling the disease.

methodsWe study the optimization of age-dependent screening strategies for population-based chlamydia infection screening among young women. We develop an age-structured compartment model for CT natural progress, screening, and treatment. We apply parameter optimization on the resultant PDE-based system dynamical models with the objective of minimizing the total care spending, including screening and treatment costs during the program period and anticipated costs of treating the sequelae afterwards). For ease of practical implementation, we also search for the best screening initiation age for strategies with a constant screening frequency.

resultsThe optimal age-dependent strategies identified outperform the current CDC recommendations both in terms of total care spending and disease prevalence at the termination of the program. For example, the age-dependent strategy that allows monthly screening rate changes can save about 5% of the total spending. Our results suggest early initiation of CT screening is likely beneficial to the cost saving and prevalence reduction. Finally, our results imply that the strategy design may not be sensitive to accurate quantification of the age-specific CT infection risk if screening initiation age and screening rate are the only decisions to make.

conclusionsOur research demonstrates the potential economic benefit of age-dependent screening strategy design for population-based screening programs. It also showcases the applicability of age-structured system dynamical modeling to infectious disease control with increasing evidence on the age differences in infection risk. The research can be further improved with consideration of the difference between first-time infection and reinfection, as well as population heterogeneity in sexual partnership.

Indexed as

AdolescentAdultAge FactorsChlamydia InfectionsCost-Benefit AnalysisFemaleHumansMass ScreeningPrevalenceSexual PartnersYoung Adult

Identifiers

PMID26162374
PMCPMC4498533
OpenAlexW1602563352

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.