Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era

Background Mathematical models are widely used to simulate the eff ects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. Methods We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15–49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey. Findings All models projected lower prevalence estimates for 2012 than the survey estimate (18·8%), with eight models’ central projections being below the survey 95% CI (17·5–20·3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16·9% in 2008 to 18·8% in 2012 (diff erence 1·9, 95% CI –0·1 to 3·9). Model projections accurately predicted the 1·6 percentage point prevalence decline (95% CI –0·3 to 3·5) in young adults aged 15–24 years, and the 2·2 percentage point (0·5 to 3·9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1·54–2·12 million. However, the diff erential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2·22 (95% CI 1·73–2·71). Interpretation Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections

Assessment of epidemic projections using recent HIV survey data in South Africa: A validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era

Background: Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. Methods: We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15-49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey. Findings: All models projected lower prevalence estimates for 2012 than the survey estimate (18·8%), with eight models' central projections being below the survey 95% CI (17·5-20·3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16·9% in 2008 to 18·8% in 2012 (difference 1·9, 95% CI -0·1 to 3·9). Model projections accurately predicted the 1·6 percentage point prevalence decline (95% CI -0·3 to 3·5) in young adults aged 15-24 years, and the 2·2 percentage point (0·5 to 3·9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1·54-2·12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2·22 (95% CI 1·73-2·71). Interpretation: Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections. Funding: Bill & Melinda Gates Foundation

Bidirectional links between HIV and intimate partner violence in pregnancy: implications for prevention of mother-to-child transmission.

INTRODUCTION: Prevention of mother-to-child transmission (PMTCT) has the potential to eliminate new HIV infections among infants. Yet in many parts of sub-Saharan Africa, PMTCT coverage remains low, leading to unacceptably high rates of morbidity among mothers and new infections among infants. Intimate partner violence (IPV) may be a structural driver of poor PMTCT uptake, but has received little attention in the literature to date. METHODS: We conducted qualitative research in three Johannesburg antenatal clinics to understand the links between IPV and HIV-related health of pregnant women. We held focus group discussions with pregnant women (n=13) alongside qualitative interviews with health care providers (n=10), district health managers (n=10) and pregnant abused women (n=5). Data were analysed in Nvivo10 using a team-based approach to thematic coding. FINDINGS: We found qualitative evidence of strong bidirectional links between IPV and HIV among pregnant women. HIV diagnosis during pregnancy, and subsequent partner disclosure, were noted as a common trigger of IPV. Disclosure leads to violence because it causes relationship conflict, usually related to perceived infidelity and the notion that women are "bringing" the disease into the relationship. IPV worsened HIV-related health through poor PMTCT adherence, since taking medication or accessing health services might unintentionally alert male partners of the women's HIV status. IPV also impacted on HIV-related health via mental health, as women described feeling depressed and anxious due to the violence. IPV led to secondary HIV risk as women experienced forced sex, often with little power to negotiate condom use. Pregnant women described staying silent about condom negotiation in order to stay physically safe during pregnancy. CONCLUSIONS: IPV is a crucial issue in the lives of pregnant women and has bidirectional links with HIV-related health. IPV may worsen access to PMTCT and secondary prevention behaviours, thereby posing a risk of secondary transmission. IPV should be urgently addressed in antenatal care settings to improve uptake of PMTCT and ensure that goals of maternal and child health are met in sub-Saharan African settings

Health benefits, costs, and cost-effectiveness of earlier eligibility for adult antiretroviral therapy and expanded treatment coverage: a combined analysis of 12 mathematical models.

BACKGROUND: New WHO guidelines recommend ART initiation for HIV-positive persons with CD4 cell counts ≤500 cells/µL, a higher threshold than was previously recommended. Country decision makers must consider whether to further expand ART eligibility accordingly. METHODS: We used multiple independent mathematical models in four settings-South Africa, Zambia, India, and Vietnam-to evaluate the potential health impact, costs, and cost-effectiveness of different adult ART eligibility criteria under scenarios of current and expanded treatment coverage, with results projected over 20 years. Analyses considered extending eligibility to include individuals with CD4 ≤500 cells/µL or all HIV-positive adults, compared to the previous recommendation of initiation with CD4 ≤350 cells/µL. We assessed costs from a health system perspective, and calculated the incremental cost per DALY averted ($/DALY) to compare competing strategies. Strategies were considered 'very cost-effective' if the$/DALY was less than the country's per capita gross domestic product (GDP; South Africa: $8040, Zambia:$1425, India: $1489, Vietnam:$1407) and 'cost-effective' if $/DALY was less than three times per capita GDP. FINDINGS: In South Africa, the cost per DALY averted of extending ART eligibility to CD4 ≤500 cells/µL ranged from$237 to $1691/DALY compared to 2010 guidelines; in Zambia, expanded eligibility ranged from improving health outcomes while reducing costs (i.e. dominating current guidelines) to$749/DALY. Results were similar in scenarios with substantially expanded treatment access and for expanding eligibility to all HIV-positive adults. Expanding treatment coverage in the general population was therefore found to be cost-effective. In India, eligibility for all HIV-positive persons ranged from $131 to$241/DALY and in Vietnam eligibility for CD4 ≤500 cells/µL cost $290/DALY. In concentrated epidemics, expanded access among key populations was also cost-effective. INTERPRETATION: Earlier ART eligibility is estimated to be very cost-effective in low- and middle-income settings, although these questions should be revisited as further information becomes available. Scaling-up ART should be considered among other high-priority health interventions competing for health budgets. FUNDING: The Bill and Melinda Gates Foundation and World Health Organization

The core of social network modeling: Industrial Engineering.

Networks are abound in our everyday lives, from disaster response networks to cellular networks to social networks. In this workshop, we will introduce the different types of networks and how Industrial Engineering is used to model these networks. Next, we will describe current social network modeling research done at UMass. Finally, we will delve into hands-on activities that include social network analysis, such as the clustering of people into groups, and modeling of the spread of ideas in a social network, such as how tweets spread on Twitter

Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era

Contains fulltext : 154578.pdf (publisher's version ) (Open Access)BACKGROUND: Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. METHODS: We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15-49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey. FINDINGS: All models projected lower prevalence estimates for 2012 than the survey estimate (18.8%), with eight models' central projections being below the survey 95% CI (17.5-20.3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16.9% in 2008 to 18.8% in 2012 (difference 1.9, 95% CI -0.1 to 3.9). Model projections accurately predicted the 1.6 percentage point prevalence decline (95% CI -0.3 to 3.5) in young adults aged 15-24 years, and the 2.2 percentage point (0.5 to 3.9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1.54-2.12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2.22 (95% CI 1.73-2.71). INTERPRETATION: Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections. FUNDING: Bill & Melinda Gates Foundation

Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era

Background Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. Methods We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15-49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey. Findings All models projected lower prevalence estimates for 2012 than the survey estimate (18.8%), with eight models' central projections being below the survey 95% CI (17.5-20.3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16.9% in 2008 to 18.8% in 2012 (difference 1.9, 95% CI -0.1 to 3.9). Model projections accurately predicted the 1.6 percentage point prevalence decline (95% CI -0.3 to 3.5) in young adults aged 15-24 years, and the 2.2 percentage point (0.5 to 3.9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1.54-2.12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2.22 (95% CI 1.73-2.71). Interpretation Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections

Somatic Mutations in TSC1 and TSC2 Cause Focal Cortical Dysplasia

Focal cortical dysplasia (FCD) is a major cause of the sporadic form of intractable focal epilepsies that require surgical treatment. It has recently been reported that brain somatic mutations in MTOR account for 15%–25% of FCD type II (FCDII), characterized by cortical dyslamination and dysmorphic neurons. However, the genetic etiologies of FCDII-affected individuals who lack the MTOR mutation remain unclear. Here, we performed deep hybrid capture and amplicon sequencing (read depth of 100×–20,012×) of five important mTOR pathway genes—PIK3CA, PIK3R2, AKT3, TSC1, and TSC2—by using paired brain and saliva samples from 40 FCDII individuals negative for MTOR mutations. We found that 5 of 40 individuals (12.5%) had brain somatic mutations in TSC1 (c.64C>T [p.Arg22Trp] and c.610C>T [p.Arg204Cys]) and TSC2 (c.4639G>A [p.Val1547Ile]), and these results were reproducible on two different sequencing platforms. All identified mutations induced hyperactivation of the mTOR pathway by disrupting the formation or function of the TSC1-TSC2 complex. Furthermore, in utero CRISPR-Cas9-mediated genome editing of Tsc1 or Tsc2 induced the development of spontaneous behavioral seizures, as well as cytomegalic neurons and cortical dyslamination. These results show that brain somatic mutations in TSC1 and TSC2 cause FCD and that in utero application of the CRISPR-Cas9 system is useful for generating neurodevelopmental disease models of somatic mutations in the brain. © 2017 American Society of Human Genetic113141sciescopu