This survey of sexual practices in the United States has been combed by the media for items of interest to the public: monogamous sex is much more widespread in this country than has been thought; infidelity is less frequent than presumed; vaginal intercourse is the defining experience of heterosexual behavior; watching one's partner undress is stimulating to many people; married couples have more sex than single people (unmarried, cohabiting couples have the most sex of all); the majority of couples experience sex twice a week to several times a month; 2.8% of men identify themselves as homosexual and 1.4% of women do so, but a higher percentage of people consider a same-gender experience to have some appeal; 75% of men always experience orgasm compared with 28.6% of women, but more nearly equal numbers of men and women declare themselves satisfied with their sexual experiences. The book is, in fact, a

The Social Organization of Sexuality: Sexual Practices in the United States

https://thelancet.com/pdfs/journals/lanhiv/PIIS2352-3018(16)00008-4.pdf

Retention in care during the first 3 years of antiretroviral therapy for women in Malawi's option B+ programme: an observational cohort study

Background 
Globally, the population of adolescents living with perinatally acquired HIV (APHs) continues to expand. In this study, we pooled data from observational pediatric HIV cohorts and cohort networks, allowing comparisons of adolescents with perinatally acquired HIV in “real-life” settings across multiple regions. We describe the geographic and temporal characteristics and mortality outcomes of APHs across multiple regions, including South America and the Caribbean, North America, Europe, sub-Saharan Africa, and South and Southeast Asia.


Methods and findings 
Through the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER), individual retrospective longitudinal data from 12 cohort networks were pooled. All children infected with HIV who entered care before age 10 years, were not known to have horizontally acquired HIV, and were followed up beyond age 10 years were included in this analysis conducted from May 2016 to January 2017. Our primary analysis describes patient and treatment characteristics of APHs at key time points, including first HIV-associated clinic visit, antiretroviral therapy (ART) start, age 10 years, and last visit, and compares these characteristics by geographic region, country income group (CIG), and birth period. Our secondary analysis describes mortality, transfer out, and lost to follow-up (LTFU) as outcomes at age 15 years, using competing risk analysis. Among the 38,187 APHs included, 51% were female, 79% were from sub-Saharan Africa and 65% lived in low-income countries. APHs from 51 countries were included (Europe: 14 countries and 3,054 APHs; North America: 1 country and 1,032 APHs; South America and the Caribbean: 4 countries and 903 APHs; South and Southeast Asia: 7 countries and 2,902 APHs; sub-Saharan Africa, 25 countries and 30,296 APHs). Observation started as early as 1982 in Europe and 1996 in sub-Saharan Africa, and continued until at least 2014 in all regions. The median (interquartile range [IQR]) duration of adolescent follow-up was 3.1 (1.5–5.2) years for the total cohort and 6.4 (3.6–8.0) years in Europe, 3.7 (2.0–5.4) years in North America, 2.5 (1.2–4.4) years in South and Southeast Asia, 5.0 (2.7–7.5) years in South America and the Caribbean, and 2.1 (0.9–3.8) years in sub-Saharan Africa. Median (IQR) age at first visit differed substantially by region, ranging from 0.7 (0.3–2.1) years in North America to 7.1 (5.3–8.6) years in sub-Saharan Africa. The median age at ART start varied from 0.9 (0.4–2.6) years in North America to 7.9 (6.0–9.3) years in sub-Saharan Africa. The cumulative incidence estimates (95% confidence interval [CI]) at age 15 years for mortality, transfers out, and LTFU for all APHs were 2.6% (2.4%–2.8%), 15.6% (15.1%–16.0%), and 11.3% (10.9%–11.8%), respectively. Mortality was lowest in Europe (0.8% [0.5%–1.1%]) and highest in South America and the Caribbean (4.4% [3.1%–6.1%]). However, LTFU was lowest in South America and the Caribbean (4.8% [3.4%–6.7%]) and highest in sub-Saharan Africa (13.2% [12.6%–13.7%]). Study limitations include the high LTFU rate in sub-Saharan Africa, which could have affected the comparison of mortality across regions; inclusion of data only for APHs receiving ART from some countries; and unavailability of data from high-burden countries such as Nigeria.


Conclusion 
To our knowledge, our study represents the largest multiregional epidemiological analysis of APHs. Despite probable under-ascertained mortality, mortality in APHs remains substantially higher in sub-Saharan Africa, South and Southeast Asia, and South America and the Caribbean than in Europe. Collaborations such as CIPHER enable us to monitor current global temporal trends in outcomes over time to inform appropriate policy responses.

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The epidemiology of adolescents living with perinatally acquired HIV: A cross-region global cohort analysis

Detection of HIV DNA in cervical and vaginal secretions: Prevalence and correlates among women in Nairobi, Kenya

Background The South African national HIV program has increased antiretroviral therapy (ART) coverage over the last decade, supported by policy changes allowing for earlier ART initiation. However, many patients still enter care with advanced (<200 cells/μL) and very advanced (<100 cells/μL) HIV disease. We assessed disease progression at entry to care using nationwide laboratory data. Methods We constructed a national HIV cohort using laboratory records containing HIV RNA loads and CD4 counts from 2004 to 2016 to determine entry into care. We estimated numbers and proportions of adults with the first CD4 count <100 cells/ μL or 100-199 cells/μL. We calculated relative risks of presenting with advanced disease associated with male sex. Results 8.04 million first CD4 results were identified. From 2005 to 2011, the proportion of patients entering into care with CD4 count <200 cells/μL declined from 46.8% to 35.6%. From 2011 onward, the proportion of patients entering ART with advanced HIV disease has remained relatively unchanged. In 2016, we estimated that of 654 868 patients entering care, 32.9% had advanced HIV disease, and 16.8% had very advanced HIV disease. Men were almost twice as likely as women (23.1% vs 12.6% ) to enter care with very advanced HIV disease. Conclusions The proportion of patients presenting with advanced HIV disease in South Africa remains consistently high despite ART scale-up, representing a large and avoidable burden of morbidity. Early HIV diagnosis, rapid linkage to ART and approaches to attract men into early ART initiation should be prioritized.

Persistent High Burden of Advanced HIV Disease Among Patients Seeking Care in South Africa’s National HIV Program: Data From a Nationwide Laboratory Cohort

Background: The UNAIDS targets for 2020 are to achieve a 90% rate of diagnosis in HIVpositive individuals, to provide antiretroviral treatment (ART) to 90% of HIV-diagnosed individuals and to achieve virological suppression in 90% of ART patients. Objectives: To assess South Africa’s progress towards the 2020 targets and variations in performance by province. Methods: A mathematical model was fitted to HIV data for each of South Africa’s provinces, and for the country as a whole. Numbers of HIV tests performed in each province were estimated from routine data over the 2002–2015 period, and numbers of patients receiving ART in each province were estimated by fitting models to reported public and private ART enrolment statistics. Results: By the middle of 2015, 85.5% (95% CI: 84.5% – 86.5%) of HIV-positive South African adults had been diagnosed, with little variation between provinces. However, only 56.9% (95% CI: 55.3% – 58.7%) of HIV-diagnosed adults were on ART, with this proportion varying between 50.8% in North West and 72.7% in Northern Cape. In addition, 78.4% of adults on ART were virally suppressed, with rates ranging from 69.7% in Limpopo to 85.9% in Western Cape. Overall, 3.39 million (95% CI: 3.26–3.52 million) South Africans were on ART by mid- 2015, equivalent to 48.6% (95% CI: 46.0% – 51.2%) of the HIV-positive population. ART coverage varied between 43.0% in Gauteng and 63.0% in Northern Cape. Conclusion: Although South Africa is well on its way to reaching the 90% HIV diagnosis target, most provinces face challenges in reaching the remaining two 90% targets.

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Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa

In several studies of antiretroviral treatment (ART) programs for persons with human immunodeficiency virus infection, investigators have reported that there has been a higher rate of loss to follow-up (LTFU) among patients initiating ART in recent years than among patients who initiated ART during earlier time periods. This finding is frequently interpreted as reflecting deterioration of patient retention in the face of increasing patient loads. However, in this paper we demonstrate by simulation that transient gaps in follow-up could lead to bias when standard survival analysis techniques are applied. We created a simulated cohort of patients with different dates of ART initiation. Rates of ART interruption, ART resumption, and mortality were assumed to remain constant over time, but when we applied a standard definition of LTFU, the simulated probability of being classified LTFU at a particular ART duration was substantially higher in recently enrolled cohorts. This suggests that much of the apparent trend towards increased LTFU may be attributed to bias caused by transient interruptions in care. Alternative statistical techniques need to be used when analyzing predictors of LTFU-for example, using "prospective" definitions of LTFU in place of "retrospective" definitions. Similar considerations may apply when analyzing predictors of LTFU from treatment programs for other chronic diseases.

Do Increasing Rates of Loss to Follow-up in Antiretroviral Treatment Programs Imply Deteriorating Patient Retention?

Background: HIV prevalence differs substantially between South Africa’s provinces, but the factors accounting for this difference are poorly understood. Objectives: To estimate HIV prevalence and incidence trends by province, and to identify the epidemiological factors that account for most of the variation between provinces. Methods: A mathematical model of the South African HIV epidemic was applied to each of the nine provinces, allowing for provincial differences in demography, sexual behaviour, male circumcision, interventions and epidemic timing. The model was calibrated to HIV prevalence data from antenatal and household surveys using a Bayesian approach. Parameters estimated for each province were substituted into the national model to assess sensitivity to provincial variations. Results: HIV incidence in 15–49-year-olds peaked between 1997 and 2003 and has since declined steadily. By mid-2013, HIV prevalence in 15–49-year-olds varied between 9.4% (95% CI: 8.5%–10.2%) in Western Cape and 26.8% (95% CI: 25.8%–27.6%) in KwaZulu-Natal. When standardising parameters across provinces, this prevalence was sensitive to provincial differences in the prevalence of male circumcision (range 12.3%–21.4%) and the level of non-marital sexual activity (range 9.5%–24.1%), but not to provincial differences in condom use (range 17.7%–21.2%), sexual mixing (range 15.9%–19.2%), marriage (range 18.2%–19.4%) or assumed HIV prevalence in 1985 (range 17.0%–19.1%). Conclusion: The provinces of South Africa differ in the timing and magnitude of their HIV epidemics. Most of the heterogeneity in HIV prevalence between South Africa’s provinces is attributable to differences in the prevalence of male circumcision and the frequency of non-marital sexual activity.

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HIV epidemic drivers in South Africa: A model-based evaluation of factors accounting for inter-provincial differences in HIV prevalence and incidence trends

Background: Antiretroviral therapy is often initiated too late to impact early HIV-related infant mortality. Earlier treatment requires an earlier diagnosis, and the currently recommended 6-week HIV polymerase chain reaction (PCR) test needs reconsideration. This study aims to identify (1) optimal testing intervals to maximize the number of perinatal HIV infections diagnosed and (2) programmatic issues that impact diagnosis. Methods: A mathematical model was developed to simulate antiretroviral prophylaxis uptake and health outcomes in 240,000 HIV-exposed South African infants. The model considered routine early testing with 1 PCR (at birth, 6, 10, or 14 weeks of age) and with 2 PCR tests (at birth and at 6, 10, or 14 weeks of age). Results: A single 6-week test would diagnose the same number of perinatal HIV infections as birth testing (P = 0.92) but fewer infections than a 10-week test (P , 0.01). Ten-week testing identifies the highest number of perinatally infected infants (P , 0.01 compared with a single test at all other ages) but does not save additional life years compared with birth testing (P = 0.27). Performing 2 PCR tests (at birth and 10 weeks) would identify the highest number of perinatal infections (P , 0.01 versus a second 6- or 14-week test). However, 25% of perinatal HIV infections would remain undiagnosed, largely because of failure to return PCR test results to caregivers. Conclusions: Six weeks may no longer be the optimal age to diagnose perinatal HIV infections. Two early PCR tests (at birth and 10 weeks) would likely be the ideal diagnostic algorithm, but must be coupled with improved program coverage.

A mathematical model evaluating the timing of early diagnostic testing in HIV-exposed infants in South Africa.

Background: Although many mathematical models have been developed to simulate the likely effect of biomedical HIV interventions, there have been relatively few mathematical models that describe the social and structural drivers of HIV and the factors that account for heterogeneity in HIV risk within populations. This report provides a technical description of MicroCOSM, a model developed to address these issues in the South African context.
Methods: MicroCOSM is an agent-based model, which assigns to each simulated individual a number of demographic characteristics (age, sex and race) and socio-economic characteristics (educational attainment, current schooling, urban-rural location, migrancy and incarceration history). These in turn influence individual access to and uptake of healthcare (condom preference, HIV testing, hormonal contraceptive use, male circumcision, antiretroviral treatment) and sexual behaviour (sexual preference, propensity for concurrent partners and commercial sex, marital status, number of partners). All of these factors affect health outcomes (fertility, mortality, HIV and other sexually transmitted infections), which in turn dynamically influence socio-economic status, healthcare access and sexual behaviour. Individuals are linked to partners in dynamic sexual networks. The model simulates the South African population over the period from 1985 to the present.
Results: The model matches the observed levels of HIV prevalence in South Africa by age and sex, as well as the observed changes in HIV prevalence over time. The model also matches observed patterns of HIV prevalence by educational attainment, by urban-rural location and by history of recent migration. Estimates of HIV prevalence in key populations (sex workers, men who have sex with men and prisoners) are roughly consistent with surveys. The model has also been calibrated to match total numbers of HIV tests and male circumcision operations performed in South Africa, as well as estimates of HIV diagnosis and antiretroviral treatment coverage from other models.
Conclusions: MicroCOSM is a fully-integrated model of the social, biomedical and behavioural factors that drive HIV and other sexually transmitted infections in South Africa. This work lays the foundation for a more quantitative approach to understanding which sub-populations are currently at the greatest HIV risk, and to assessing what interventions are needed to reduce socioeconomic and racial inequality in health outcomes.

/pdf/microcosm-a-model-of-social-and-structural-drivers-of-hiv-3tjkb4s9au.pdf

Haroon Moolla

Papers

Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa

Do Increasing Rates of Loss to Follow-up in Antiretroviral Treatment Programs Imply Deteriorating Patient Retention?

HIV epidemic drivers in South Africa: A model-based evaluation of factors accounting for inter-provincial differences in HIV prevalence and incidence trends

A mathematical model evaluating the timing of early diagnostic testing in HIV-exposed infants in South Africa.

MicroCOSM: a model of social and structural drivers of HIV and interventions to reduce HIV incidence in high-risk populations in South Africa