Sexual behaviour patterns in South Africa and their association with the spread of HIV: insights from a mathematical model

Johnson, Leigh F.; Dorrington, Rob; Bradshaw, Debbie; Wyk, Victoria Pillay-van; Rehle, T.

doi:10.4054/demres.2009.21.11

Cited by 70 publications

(75 citation statements)

References 110 publications

(135 reference statements)

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“…The likelihood was specified as a normal distribution around the logit-transformed prevalence estimates with the error variance estimated by the survey SE, accounting for the complex survey design of the ANC and household seroprevalence surveys (58). The influence of the existing ART scale-up in South Africa on prevalence and incidence was incorporated in the model calibration by simulating the percentage of adults (age 15+ years) on ART at midyear from 2005 through 2010 reported by the South African Department of Health (59) (Fig.…”

Section: Methodsmentioning

confidence: 99%

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Eaton

Hallett

2014

Proc. Natl. Acad. Sci. U.S.A.

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Antiretroviral therapy (ART) reduces the infectiousness of HIVinfected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection ("early transmission") is perceived as a threat to the impact of HIV "treatment-as-prevention" strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate-consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R 0 ) are consistent with observed epidemic growth, and R 0 was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.HIV incidence | antiretroviral therapy | early infection | HIV prevention intervention | mathematical model R ecent studies have confirmed that effective antiretroviral therapy (ART) reduces the transmission of HIV among stable heterosexual couples (1-3). This finding has generated interest in understanding the population-level impact of HIV treatment on reducing the rate of new HIV infections in generalized epidemic settings (4). Research, including mathematical modeling (5-10), implementation research (11), and major randomized controlled trials (12)(13)(14), are focused on how ART provision might be expanded strategically to maximize its public health benefits (15, 16).One concern is that if a large fraction of HIV transmission occurs shortly after a person becomes infected, before the person can be diagnosed and initiated on ART, this will limit the potential impact of HIV treatment on reducing HIV incidence (9,17,18). Data suggest that persons are more infectious during a short period of "early infection" after becoming infected with HIV (19-22), although there is debate about the extent, duration, and determinants of elevated infectiousness (18, 23). The amount of transmission that occurs also will depend on patterns of sexual behavior and sexual networks (17,(24)(25)(26)(27). There have been estimates for the contribution of early infection to transmission from math...

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Section: Methodsmentioning

confidence: 99%

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Eaton

Hallett

2014

Proc. Natl. Acad. Sci. U.S.A.

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“…Two deterministic models of the South African HIV/ AIDS epidemic are assessed: the STI (sexually transmitted infection) -HIV Interaction model [12] and the ASSA2003 AIDS and Demographic model [22,23]. Both models have been adapted for the purpose of the current analysis, and full details of the adapted models are included in electronic supplementary material, appendices A and B, respectively.…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…The ASSA2003 model is also fitted to reported death data over the 1997 -2004 period [32], as it is a more demographically detailed model. Being more behaviourally detailed, the STI -HIV model is also fitted to data on numbers of sexual partners from the 2005 HSRC survey [12].…”

Section: Data Sourcesmentioning

confidence: 99%

“…Because this analysis of the ASSA2003 model allows for uncertainty in the extent of the under-reporting of deaths and in the extent of the antenatal bias, the calibration of the model to the death data and the antenatal data differs from that in the previously published ASSA2003 model [23]. Finally, the likelihood in respect of the reported number of partners makes allowance for social desirability bias, which differs according to individuals' sex and marital status [12].…”

Section: Model Fittingmentioning

confidence: 99%

See 1 more Smart Citation

The effect of changes in condom usage and antiretroviral treatment coverage on human immunodeficiency virus incidence in South Africa: a model-based analysis

Johnson

Hallett

Rehle

et al. 2012

J. R. Soc. Interface.

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This study aims to assess trends in human immunodeficiency virus (HIV) incidence in South Africa, and to assess the extent to which prevention and treatment programmes have reduced HIV incidence. Two models of the South African HIV epidemic, the STI (sexually transmitted infection) -HIV Interaction model and the ASSA2003 AIDS and Demographic model, were adapted. Both models were fitted to age-specific HIV prevalence data from antenatal clinic surveys and household surveys, using a Bayesian approach. Both models suggest that HIV incidence in 15 -49 year olds declined significantly between the start of 2000 and the start of 2008: by 27 per cent (95% CI: 21-32%) in the STI -HIV model and by 31 per cent (95% CI: 23-39%) in the ASSA2003 model, when expressed as a percentage of incidence rates in 2000. By 2008, the percentage reduction in incidence owing to increased condom use was 37 per cent (95% CI: 34 -41%) in the STI-HIV model and 23 per cent (95% CI: 14-34%) in the ASSA2003 model. Both models also estimated a small reduction in incidence owing to antiretroviral treatment by 2008. Increased condom use therefore appears to be the most significant factor explaining the recent South African HIV incidence decline.

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“…Concurrency. Where selective mixing relates to connectivity of subpopulations and disease transmission between subpopulations, concurrency relates to connectivity of individuals and disease spread between individuals, and a number of studies have claimed that concurrency is important in explaining disparities in STI prevalence and the speed with which STIs propagate through a population [Watts and May (1992), Hudson (1993), Morris and Kretzschmar (1995, Kretzschmar and Morris (1996), Ghani, Swinton and Garnett (1997), Chick, Adams and Koopman (2000), Ghani and Garnett (2000), Koopman et al (2000), Schoenbach (2002, 2005), Doherty (2006, 2007), Doherty et al (2006), Morris, Goodreau and Moody (2007), Morris et al (2009), Johnson et al (2009), Mah and Halperin (2010, Eaton, Hallett and Garnett (2011), Goodreau (2011), Goodreau et al (2012, Kretzschmar and Caraël (2012), Hamilton and Morris (2015)]. If we consider a population under serial monogamy, current relationships must end before infected individuals place other noninfected individuals at risk.…”

Section: Selective Mixingmentioning

confidence: 99%

Modeling concurrency and selective mixing in heterosexual partnership networks with applications to sexually transmitted diseases

Admiraal¹,

Handcock²

2016

Ann. Appl. Stat.

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Network-based models for sexually transmitted disease transmission rely on initial partnership networks incorporating structures that may be related to risk of infection. In particular, initial networks should reflect the level of concurrency and attribute-based selective mixing observed in the population of interest. We consider momentary degree distributions as measures of concurrency and propensities for people of certain types to form partnerships with each other as a measure of attribute-based selective mixing. Estimation of momentary degree distributions and mixing patterns typically relies on cross-sectional survey data, and, in the context of heterosexual networks, we describe how this results in two sets of reports that need not be consistent with each other. The reported momentary degree distributions and mixing totals are related through a series of constraints, however. We provide a method to incorporate those in jointly estimating momentary degree distributions and mixing totals. We develop a method to simulate heterosexual networks consistent with these momentary degree distributions and mixing totals, applying it to data obtained from the National Longitudinal Study of Adolescent Health. We first use the momentary degree distributions and mixing totals as mean value parameters to estimate the natural parameters for an exponential-family random graph model and then use a Markov chain Monte Carlo algorithm to simulate person-level heterosexual partnership networks.

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Sexual behaviour patterns in South Africa and their association with the spread of HIV: insights from a mathematical model

Cited by 70 publications

References 110 publications

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

The effect of changes in condom usage and antiretroviral treatment coverage on human immunodeficiency virus incidence in South Africa: a model-based analysis

Modeling concurrency and selective mixing in heterosexual partnership networks with applications to sexually transmitted diseases

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