Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis

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dc.contributor.authorKenyon, Chris R.en_ZA
dc.contributor.authorDelva, Wimen_ZA
dc.contributor.authorBrotman, Rebecca M.en_ZA
dc.date.accessioned2019-01-15T13:33:09Z
dc.date.available2019-01-15T13:33:09Z
dc.date.issued2019-01-10
dc.date.updated2019-01-15T11:44:47Z
dc.descriptionCITATION: Kenyon, C. R., Delva, W. & Brotman, R. M. 2019. Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis : a datadriven, model-supported hypothesis. BMC Women's Health, 19:8, doi:10.1186/s12905-018-0703-0.
dc.descriptionThe original publication is available at https://bmcwomenshealth.biomedcentral.com
dc.description.abstractBackground: The 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 highdiversity 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 BVassociated 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. Conclusion: To test this hypothesis, we propose a combination of empirical and simulation-based study designs.en_ZA
dc.description.urihttps://bmcwomenshealth.biomedcentral.com/articles/10.1186/s12905-018-0703-0
dc.description.versionPublisher's version
dc.format.extent9 pages
dc.identifier.citationKenyon, C. R., Delva, W. & Brotman, R. M. 2019. Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis : a datadriven, model-supported hypothesis. BMC Women's Health, 19:8, doi:10.1186/s12905-018-0703-0
dc.identifier.issn1472-6874 (online)
dc.identifier.otherdoi:10.1186/s12905-018-0703-0
dc.identifier.urihttp://hdl.handle.net/10019.1/105313
dc.language.isoen_ZAen_ZA
dc.publisherBMC (part of Springer Nature)
dc.rights.holderAuthors retain copyright
dc.subjectBacterial vaginosisen_ZA
dc.subjectSexual behavioren_ZA
dc.subjectBacterial vaginitis -- Etiologyen_ZA
dc.subjectSexually transmitted diseases -- Microbiologyen_ZA
dc.subjectMultiple sexual partners -- Risk factorsen_ZA
dc.titleDifferential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesisen_ZA
dc.typeArticleen_ZA
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