Evidence map›Paper›PMID 41044103›Full record

ArticleScientific reports2025

Quantifying population-level sexual risk behavior through HSV-2 transmission dynamics in the United States, 1950-2020.

Bechir S Naffeti, Houssein H Ayoub, Laith J Abu-Raddad

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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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
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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.

Bechir S NaffetiMathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar. bechir.naffeti@qu.edu.qa.ORCID http://orcid.org/0000-0002-8782-8788
Houssein H AyoubMathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar. hayoub@qu.edu.qa.ORCID http://orcid.org/0000-0003-2512-6657
Laith J Abu-RaddadInfectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.ORCID http://orcid.org/0000-0003-0790-0506

Funding

Qatar Research Development and Innovation Council ARG01-0524-230321
6 · The paper itself

Abstract

The risk of acquiring a sexually transmitted infection, such as herpes simplex virus type 2 (HSV-2), is shaped by sexual risk behavior-an aggregate measure influenced not only by an individual's sexual behavior but also by the broader sexual network. This study quantified the temporal and age-specific variations in sexual risk behavior for HSV-2 infection in the United States population between 1950 and 2020. A population-level mathematical model was used to describe HSV-2 transmission and was calibrated with ten rounds of nationally representative, population-based data from the National Health and Nutrition Examination Survey (NHANES). The model produced robust fits to the age-specific, sex-specific, and temporal HSV-2 seroprevalence data across the NHANES rounds. Sexual risk behavior gradually increased starting in the early 1960s, peaked in the early 1980s, and then steadily declined through 2020. The decline was particularly pronounced in the 1990s, when sexual risk behavior dropped sharply compared to the elevated levels of the early 1980s. Sexual risk behavior was highest among individuals aged 15-24 years and steadily declined with increasing age. The analysis identified a distinct wave of sexual risk behavior that began in the early 1960s, peaked in the early 1980s, and subsequently declined.

Indexed as

Herpes GenitalisHerpesvirus 2, HumanRisk-TakingSexual BehaviorAdolescentAdultAgedFemaleHumansMaleMiddle AgedModels, TheoreticalNutrition SurveysSeroepidemiologic StudiesUnited StatesYoung AdultGenital herpesHerpes simplex virusMathematical modelSexualitySexually transmitted infection

Identifiers

PMID41044103
PMCPMC12494987

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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.