ArticleBMC women's health2019
Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis.
Article in BMC women's health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Calibration of individual-based models to epidemiological data: A systematic review.PLoS computational biology · 2020Pooled it
- Sexual transmission of urogenital bacteria: whole metagenome sequencing evidence from a sexual network study.mSphere · 2024Article
- Article
- Vaginal and Extra-Vaginal Bacterial Colonization and Risk for Incident Bacterial Vaginosis in a Population of Women Who Have Sex With Men.The Journal of infectious diseases · 2022Article
- Interactions between reproductive biology and microbiomes in wild animal species.Animal microbiome · 2021Review
- It's the network, stupid: a population's sexual network connectivity determines its STI prevalence.F1000Research · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundThe prevalence of bacterial vaginosis (BV) and vaginal microbiota types varies dramatically between different populations around the world. Understanding what underpins these differences is important, as high-diversity microbiotas associated with BV are implicated in adverse pregnancy outcomes and enhanced susceptibility to and transmission of sexually transmitted infections. MAIN TEXT: We hypothesize that these variations in the vaginal microbiota can, in part, be explained by variations in the connectivity of sexual networks. We argue: 1) Couple-level data suggest that BV-associated bacteria can be sexually transmitted and hence high sexual network connectivity would be expected to promote the spread of BV-associated bacteria. Epidemiological studies have found positive associations between indicators of network connectivity and the prevalence of BV; 2) The relationship between BV prevalence and STI incidence/prevalence can be parsimoniously explained by differential network connectivity; 3) Studies from other mammals are generally supportive of the association between network connectivity and high-diversity vaginal microbiota.
conclusionTo test this hypothesis, we propose a combination of empirical and simulation-based study designs.
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Registered trials
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