Geographical-level contributions of risk factors for HIV infections using generalized additive models
Results from a cohort of South African women
Bibliographic Data
| ID | 19440880 |
|---|---|
| Authors | Handan Wand (0000-0002-8279-7652, Kirby Institute, University of New South Wales, Kensington, Australia, corresponding author), Reshmi Dassaye (0000-0003-1710-1556, HIV Prevention Research Unit, South African Medical Research Council, Westville, South Africa), Tarylee Reddy (0000-0002-9521-2692, Biostatistics Unit, South African Medical Research Council, Durban, South Africa), Justin Yssel (HIV Prevention Research Unit, South African Medical Research Council, Westville, South Africa), Gita Ramjee (HIV Prevention Research Unit, South African Medical Research Council, Westville, South Africa) |
| Year | 2019 |
| Volume | 31 |
| Issue | 6 |
| Pages | 714-722 |
| Publication date | 2019-06-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | AIDS Care (JOURNAL) |
| Journal identifiers | ISSN: 0954-0121 • E-ISSN: 1360-0451 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09540121.2018.1556382 |
| PMID | 30537858 |
| OpenAlex | W2905254400 |
| Language | EN |
| Citations received | 2 |
| References cited | 23 |
South Africa has the highest burden of human immunodeficiency virus (HIV) infections in the world with significant geographical variations. We identified the predictors of HIV infections and their sub-geographical-level contributions to the epidemic using a decade long data (2002-2012) from 6484 South African women. Generalized additive models were used to uncover the most significant features of these estimates across the region. In the overall analysis, younger age, not married or cohabiting with a partner, partner has another partner(s) and null/prim parity, using injectable contraceptives and presence of other sexually transmitted infections (STIs) were identified as independent predictors of HIV seroconversions. Overall, the top three highest contributors to infections were women's marital status (PAR% = 73%, 95% CI: 68%, 77%), parity (PAR% = 47%, 95% CI: 42%, 53%) and partnership factors (PAR% = 37%, 95% CI: 30%, 44%). However, their contributions varied remarkably at sub-geographical level. This was mainly due to the substantial localized variations in their prevalence and hazard ratios across the region. Our results will guide policy makers to develop tailored prevention strategies in order to allocate scarce resources by targeting the most significant contributors of HIV infection at sub-geographical level
Cohort · Environmental health · Geography · Marital status · Population · Sociology · Adolescent Sexual and Reproductive Health · Demography · HIV, Drug Use, Sexual Risk · HIV/AIDS Research and Interventions · Medicine · Immunology · Internal Medicine
From work with men and boys to changes of social norms and reduction of inequities in gender relations
Tenofovir-Based Preexposure Prophylaxis for HIV Infection among African Women
Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
Combined Impact of Sexual Risk Behaviors for HIV Seroconversion Among Women in Durban, South Africa
A Simple Risk Prediction Algorithm for HIV Transmission
| Citations per year | 0.33 |
|---|---|
| Citation span | 2020 - 2022 (3) |
| Highly cited | No |