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

BACKGROUND: 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 high-diversity microbiotas associated with BV are implicated in adverse pregnancy ou...

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Detalles Bibliográficos
Autores principales: Kenyon, Chris R., Delva, Wim, Brotman, Rebecca M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327541/
https://www.ncbi.nlm.nih.gov/pubmed/30630481
http://dx.doi.org/10.1186/s12905-018-0703-0
Descripción
Sumario:BACKGROUND: 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 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. CONCLUSION: To test this hypothesis, we propose a combination of empirical and simulation-based study designs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12905-018-0703-0) contains supplementary material, which is available to authorized users.