Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis
Abstract 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 preg...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-01-01
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| Series: | BMC Women's Health |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12905-018-0703-0 |
| _version_ | 1828871789537656832 |
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| author | Chris R. Kenyon Wim Delva Rebecca M. Brotman |
| author_facet | Chris R. Kenyon Wim Delva Rebecca M. Brotman |
| author_sort | Chris R. Kenyon |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-13T06:39:12Z |
| format | Article |
| id | doaj.art-ee3ac4ab365d456cb2d38d4aa9609fa7 |
| institution | Directory Open Access Journal |
| issn | 1472-6874 |
| language | English |
| last_indexed | 2024-12-13T06:39:12Z |
| publishDate | 2019-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Women's Health |
| spelling | doaj.art-ee3ac4ab365d456cb2d38d4aa9609fa72022-12-21T23:56:27ZengBMCBMC Women's Health1472-68742019-01-011911910.1186/s12905-018-0703-0Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesisChris R. Kenyon0Wim Delva1Rebecca M. Brotman2STI Unit, Institute of Tropical MedicineThe South African DST-NRF Centre of Excellence in Epidemiological, Modelling and Analysis (SACEMA)Department of Epidemiology and Public Health, Institute for Genome Sciences, University of Maryland School of MedicineAbstract 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.http://link.springer.com/article/10.1186/s12905-018-0703-0Bacterial vaginosisMicrobiomeSexual network connectivityConcurrencySTIHIV |
| spellingShingle | Chris R. Kenyon Wim Delva Rebecca M. Brotman Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis BMC Women's Health Bacterial vaginosis Microbiome Sexual network connectivity Concurrency STI HIV |
| title | Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis |
| title_full | Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis |
| title_fullStr | Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis |
| title_full_unstemmed | Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis |
| title_short | Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis |
| title_sort | differential sexual network connectivity offers a parsimonious explanation for population level variations in the prevalence of bacterial vaginosis a data driven model supported hypothesis |
| topic | Bacterial vaginosis Microbiome Sexual network connectivity Concurrency STI HIV |
| url | http://link.springer.com/article/10.1186/s12905-018-0703-0 |
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