A prediction risk score for HIV among adolescent girls and young women in South Africa: identifying those in need of HIV pre-exposure prophylaxis

References

• Children’s UN. Aldolescent HIV prevention. http://data unicef/topic/hivaids/adolescents-youth-Accessed on 19/10/2020. Published online 2020.
   Google Scholar
• W. Maternal, Newborn Child and Adolescent Health.
   Google Scholar
• National Department of Health (NDoH), Statistics South Africa (Stats SA), South African Medical Research Council (SAMRC), and ICF. Pretoria, South Africa, and Rockville, Maryland, USA: NDoH, Stats SA, SAMRC and ICF. South Africa Demographic and Health Survey 2016, 2019.
   Google Scholar
• SAMRC. Evaluation of a South African Combination HIV prevention programme for adolescent girls and young women. 2020 August; 128.
   Google Scholar
• Saul J, Bachman G, Allen S, Toiv NF, Cooney C, Beamon T. The DREAMS core package of interventions: A comprehensive approach to preventing HIV among adolescent girls and young women. PLoS One. 2018;13(12):e0208167.
   PubMed Web of Science ®Google Scholar
• Lakew Y, Benedict S, Haile D. Social determinants of HIV infection, hotspot areas and subpopulation groups in Ethiopia: evidence from the National Demographic and Health Survey in 2011. BMJ Open. 2015;5(11):e008669.
   PubMed Web of Science ®Google Scholar
• Chersich MF, Rees HV. Vulnerability of women in southern Africa to infection with HIV: Biological determinants and priority health sector interventions. Aids. 2008;22(Suppl. 4):S27–S40.
   PubMed Web of Science ®Google Scholar
• Skovdal M, Belton S. The Social Determinants of Health as they relate to children and youth growing up with HIV infection in sub-Saharan Africa. Child Youth Serv Rev. 2014;45(C):1–8.
   Google Scholar
• Underwood C, Skinner J, Osman N, Schwandt H. Structural determinants of adolescent girls’ vulnerability to HIV: Views from community members in Botswana, Malawi, and Mozambique. Soc Sci Med. 2011;73(2):343–350.
   PubMed Web of Science ®Google Scholar
• Buot MLG, Docena JP, Ratemo BK, et al. Beyond race and place: Distal sociological determinants of HIV disparities. PLoS One. 2014;9(4):e91711.
   PubMed Web of Science ®Google Scholar
• Asaolu IO, Gunn JK, Center KE, Koss MP, Iwelunmor JI, Ehiri JE. Predictors of HIV testing among youth in sub-Saharan Africa: A cross-sectional study. PLoS One. 2016;11(10):e0164052.
   PubMed Web of Science ®Google Scholar
• Ijumba N. Impact of HIV/AIDS on education and poverty About the author.
   Google Scholar
• Fotso AS, Banjo O, Akinyemi JO. Article HIV and adolescents’ educational attainment in South Africa: Disentangling the effect of infection in children and household members. SAJCH 2018;12(2):1512.
   Google Scholar
• Impact THE, HIV OF, Girls AON, Globally YW. IWHC the impact of HIV and AIDS on girls.
   Google Scholar
• SANAC. South Africa’s National Strategic Plan on HIV/Aids, TB and STI’s 2017-2022. South African National AIDS Council. 2017, v.1. Pretoria, South Africa.
   Google Scholar
• Frescuraid L, Godfrey-Faussett P, Feizzadeh A, El-Sadr W, Syarif O, Ghys PD. Achieving the 95 95 95 targets for all: A pathway to ending AIDS. 2022;17(8):e0272405.
   Google Scholar
• Programa Conjunto de las Naciones Unidas sobre el VIH/SIDA. An ambitious treatment target to help end the AIDS epidemic. Unaids. 2016;1–40.
   Google Scholar
• Hill LM, Maseko B, Chagomerana M, et al. HIV risk, risk perception, and PrEP interest among adolescent girls and young women in Lilongwe, Malawi: operationalizing the PrEP cascade. J Intern AIDS Soc. 2020;23(S3):40–47.
   Google Scholar
• Celum CL, Delany-Moretlwe S, McConnell M, et al. Rethinking HIV prevention to prepare for oral PrEP implementation for young African women. J Int AIDS Soc. 2015;18(Suppl 3):20227.
   PubMedGoogle Scholar
• PrePWatch SA. A snapshot of PrEP scale-up. Registration and Resources for South Africa. 2021.
   Google Scholar
• South Africa – PrEPWatch. https://www.prepwatch.org/countries/south-africa/. Accessed May 4, 2023.
   Google Scholar
• South Africa to begin piloting injectable PrEP in early 2023 | aidsmap. https://www.aidsmap.com/news/nov-2022/south-africa-begin-piloting-injectable-prep-early-2023. Accessed May 4, 2023.
   Google Scholar
• Price JT, Rosenberg NE, Vansia D, et al. Predictors of HIV, HIV risk perception, and HIV worry among adolescent girls and young women in Lilongwe, Malawi. J Acquir Immune Defic Syndr. 2018;77(1):53–63.
   PubMed Web of Science ®Google Scholar
• Maughan-Brown B, Venkataramani AS. Accuracy and determinants of perceived HIV risk among young women in South Africa. BMC Public Health. 2018;18(1):1–9.
   Google Scholar
• Wilton J, Kain T, Fowler S, et al. Use of an HIV-risk screening tool to identify optimal candidates for PrEP scale-up among men who have sex with men in Toronto, Canada: Disconnect between objective and subjective HIV risk. J Int AIDS Soc. 2016;19(1):20777.
   PubMed Web of Science ®Google Scholar
• Muhumuza R, Ssemata AS, Kakande A, et al. Exploring perceived barriers and facilitators of PrEP uptake among young people in Uganda, Zimbabwe, and South Africa. Arch Sex Behav. 2021;50(4):1729–1742.
   PubMed Web of Science ®Google Scholar
• Ranganathan M, Heise L, Pettifor A, et al. Transactional sex among young women in rural South Africa: Prevalence, mediators and association with HIV infection. J Int AIDS Soc. 2016;19(1):20749.
   PubMedGoogle Scholar
• Pettit AC, Bian A, Schember CO, et al. Development and validation of a multivariable prediction model for missed HIV health care provider visits in a large US Clinical Cohort. Open Forum Infect Dis. 2021;8(7):1–9.
   Web of Science ®Google Scholar
• Rosenberg NE, Kudowa E, Price JT, et al. Identifying adolescent girls and young women at high risk for HIV acquisition: A risk assessment tool fromthe girl power-malawi study. Sex Transm Dis. 2020;47(11):760–766.
   PubMed Web of Science ®Google Scholar
• Pasteur L, Koch R. Introduction. Introduction. 1934;74:535–546.
   Google Scholar
• Mutai CK, McSharry PE, Ngaruye I, Musabanganji E. Use of machine learning techniques to identify HIV predictors for screening in sub-Saharan Africa. BMC Med Res Methodol. 2021;21(1):1–11.
   PubMed Web of Science ®Google Scholar
• Jia KM, Eilerts H, Edun O, et al. Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis. J Int AIDS Soc. 2022;25(1):e25861.
   PubMed Web of Science ®Google Scholar
• Su TL, Jaki TF, Hickey G, et al. A review of statistical updating methods for clinical prediction models. Stat Methods Med Res. 2018;27(1):185–197.
   PubMed Web of Science ®Google Scholar
• Jenkins DA, Martin GP, Sperrin M, et al. Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems? Diagn Progn Res. 2021;5(1):1–7.
   PubMedGoogle Scholar
• Luo Q, Huang X, Li L, et al. External validation of a prediction tool to estimate the risk of human immunodeficiency virus infection amongst men who have sex with men. Medicine (United States). 2019;98(29):e16375.
   Google Scholar