Evidence map›Paper›PMID 37648446›Full record

ArticleSexually transmitted infections2023

Using infection prevalence, seroprevalence and case report data to estimate chlamydial infection incidence.

Patrick A Clay, Emily D Pollock, Casey E Copen, E Gloria Anyalechi, Damien C Danavall, Jaeyoung Hong, Christine M Khosropour, Eboni Galloway, Ian H Spicknall

Abstract readCase Reports
In one paragraph

Article in Sexually transmitted infections, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Patrick A ClayDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA ruq9@cdc.gov.ORCID 0000-0002-3491-9985
Emily D PollockDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Casey E CopenDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.ORCID 0000-0001-8354-0464
E Gloria AnyalechiDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.ORCID 0000-0002-7911-1701
Damien C DanavallDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Jaeyoung HongDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.ORCID 0000-0002-7962-2819
Christine M KhosropourDepartment of Epidemiology, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-9743-0829
Eboni GallowayDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Ian H SpicknallDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

objectivesTo measure the effectiveness of chlamydia control strategies, we must estimate infection incidence over time. Available data, including survey-based infection prevalence and case reports, have limitations as proxies for infection incidence. We therefore developed a novel method for estimating chlamydial incidence.

methodsWe linked a susceptible infectious mathematical model to serodynamics data from the National Health and Nutritional Examination Survey, as well as to annual case reports. We created four iterations of this model, varying assumptions about how the method of infection clearance (via treatment seeking, routine screening or natural clearance) relates to long-term seropositivity. Using these models, we estimated annual infection incidence for women aged 18-24 and 25-37 years in 2014. To assess model plausibility, we also estimated natural clearance for the same groups.

resultsOf the four models we analysed, the model that best explained the empirical data was the one in which longer-lasting infections, natural clearance and symptomatic infections all increased the probability of long-term seroconversion. Using this model, we estimated 5910 (quartile (Q)1, 5330; Q3, 6500) incident infections per 100 000 women aged 18-24 years and 2790 (Q1, 2500; Q3, 3090) incident infections per 100 000 women aged 25-37 years in 2014. Furthermore, we estimated that natural clearance rates increased with age.

conclusionsOur method can be used to estimate the number of chlamydia infections each year, and thus whether infection incidence increases or decreases over time and after policy changes. Furthermore, our results suggest that clearance via medical intervention may lead to short-term or no seroconversion, and the duration of untreated chlamydial infection may vary with age, underlining the complexity of chlamydial infection dynamics.

Indexed as

Chlamydia InfectionsHIV SeropositivityChlamydia trachomatisFemaleHumansIncidencePrevalenceSeroepidemiologic Studieschlamydia infectionsepidemiologymodels, theoretical

Identifiers

PMID37648446
PMCPMC11323310

What OpenQuestion holds

Textmetadata
LicenceTDM
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.