Layne Dylla, Beau Abar, Anna-Lise Williamson, Tracy L Meiring, Linda-Gail Bekker, David H Adler
{"title":"南非感染艾滋病毒和未感染艾滋病毒的青春期女性的人乳头瘤病毒聚集模式。","authors":"Layne Dylla, Beau Abar, Anna-Lise Williamson, Tracy L Meiring, Linda-Gail Bekker, David H Adler","doi":"10.5897/JAHR2017.0445","DOIUrl":null,"url":null,"abstract":"<p><p>The global burden of disease caused by both human immunodeficiency virus (HIV) and human papillomavirus (HPV) is the greatest in the developing world, with the highest rates in sub-Saharan Africa. South African women not only have high rates of infection with HPV, but also have high rates of multiple concurrent infections with two or more HPV genotypes, and are among the world's most vulnerable to developing invasive cervical cancer. HIV co-infection increases these risks. Understanding clustering patterns of concurrent HPV infections in this population has important implications for HPV screening and will help define vaccination strategies in the future as vaccines continue to be developed to target more HPV genotypes. Latent class analysis was used to identify four distinct patterns of HPV co-infection: individuals with at least one low risk HPV genotype, but no high-risk HPV (HR-HPV) infections; individuals with a disperse pattern of HR-HPV infections; individuals infected with members of the alpha-7 group, but not HPV-18; and individuals infected with HPV-16, but not HPV-18. In this analysis, although alpha-7 HPV infections were more prevalent among HIV-infected adolescents than their HIV-uninfected counterparts, overall clustering patterns were not different based on HIV status.</p>","PeriodicalId":73590,"journal":{"name":"Journal of AIDS and HIV research (Online)","volume":"9 10","pages":"202-206"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5897/JAHR2017.0445","citationCount":"5","resultStr":"{\"title\":\"Human papillomavirus clustering patterns among HIV-infected and HIV-uninfected adolescent females in South Africa.\",\"authors\":\"Layne Dylla, Beau Abar, Anna-Lise Williamson, Tracy L Meiring, Linda-Gail Bekker, David H Adler\",\"doi\":\"10.5897/JAHR2017.0445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The global burden of disease caused by both human immunodeficiency virus (HIV) and human papillomavirus (HPV) is the greatest in the developing world, with the highest rates in sub-Saharan Africa. South African women not only have high rates of infection with HPV, but also have high rates of multiple concurrent infections with two or more HPV genotypes, and are among the world's most vulnerable to developing invasive cervical cancer. HIV co-infection increases these risks. Understanding clustering patterns of concurrent HPV infections in this population has important implications for HPV screening and will help define vaccination strategies in the future as vaccines continue to be developed to target more HPV genotypes. Latent class analysis was used to identify four distinct patterns of HPV co-infection: individuals with at least one low risk HPV genotype, but no high-risk HPV (HR-HPV) infections; individuals with a disperse pattern of HR-HPV infections; individuals infected with members of the alpha-7 group, but not HPV-18; and individuals infected with HPV-16, but not HPV-18. In this analysis, although alpha-7 HPV infections were more prevalent among HIV-infected adolescents than their HIV-uninfected counterparts, overall clustering patterns were not different based on HIV status.</p>\",\"PeriodicalId\":73590,\"journal\":{\"name\":\"Journal of AIDS and HIV research (Online)\",\"volume\":\"9 10\",\"pages\":\"202-206\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.5897/JAHR2017.0445\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of AIDS and HIV research (Online)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5897/JAHR2017.0445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/10/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of AIDS and HIV research (Online)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5897/JAHR2017.0445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/10/31 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Human papillomavirus clustering patterns among HIV-infected and HIV-uninfected adolescent females in South Africa.
The global burden of disease caused by both human immunodeficiency virus (HIV) and human papillomavirus (HPV) is the greatest in the developing world, with the highest rates in sub-Saharan Africa. South African women not only have high rates of infection with HPV, but also have high rates of multiple concurrent infections with two or more HPV genotypes, and are among the world's most vulnerable to developing invasive cervical cancer. HIV co-infection increases these risks. Understanding clustering patterns of concurrent HPV infections in this population has important implications for HPV screening and will help define vaccination strategies in the future as vaccines continue to be developed to target more HPV genotypes. Latent class analysis was used to identify four distinct patterns of HPV co-infection: individuals with at least one low risk HPV genotype, but no high-risk HPV (HR-HPV) infections; individuals with a disperse pattern of HR-HPV infections; individuals infected with members of the alpha-7 group, but not HPV-18; and individuals infected with HPV-16, but not HPV-18. In this analysis, although alpha-7 HPV infections were more prevalent among HIV-infected adolescents than their HIV-uninfected counterparts, overall clustering patterns were not different based on HIV status.