factors regarding distribution to townships in south africa joernal

We found that residing in informal dwellings and not having post-secondary education increased the odds of HIV (aOR, 89% CrI: 1.34, 1.07–1.68 and 1.82, 1.29–2.61, respectively), after controlling for subdistrict of residence, individual, and behavioural factors.

We controlled for individual factors (age, sex, marital status, testing history, HIV exposure, comorbidities, and tuberculosis infection) and behavioural factors (unprotected sex, sex with multiple partners, with sex workers, with a partner living with HIV, under the influence of alcohol or drugs), and accounted for the uncertainty due to missing data through multiple imputation. Using Bayesian logistic regression, we analysed secondary data from a quasi-randomised trial which recruited participants (N = 3095) from townships located across three subdistricts of Cape Town. Our objective was to estimate the extent to which socioeconomic factors (dwelling situation, education, employment status, and monthly income) explain the risk of HIV in South African township populations, after controlling for behavioural and individual risk factors. Yet, it remains unclear how socioeconomic factors impact the risk of HIV infection within township populations. With a prevalence almost twice as high as the national average, people living in South African townships are particularly impacted by the HIV epidemic.

Factors regarding distribution to townships in south africa joernal