Development, Calibration and Performance of an HIV Transmission Model Incorporating Natural History and Behavioral Patterns: Application in South Africa

Understanding HIV transmission dynamics is critical to estimating the potential population-wide impact of HIV prevention and treatment interventions. We developed an individual-based simulation model of the heterosexual HIV epidemic in South Africa and linked it to the previously published Cost-Effectiveness of Preventing AIDS Complications (CEPAC) International Model, which simulates the natural history and treatment of HIV. In this new model, the CEPAC Dynamic Model (CDM), the probability of HIV transmission per sexual encounter between short-term, long-term and commercial sex worker partners depends upon the HIV RNA and disease stage of the infected partner, condom use, and the circumcision status of the uninfected male partner. We included behavioral, demographic and biological values in the CDM and calibrated to HIV prevalence in South Africa pre-antiretroviral therapy. Using a multi-step fitting procedure based on Bayesian melding methodology, we performed 264,225 simulations of the HIV epidemic in South Africa and identified 3,750 parameter sets that created an epidemic and had behavioral characteristics representative of a South African population pre-ART. Of these parameter sets, 564 contributed 90% of the likelihood weight to the fit, and closely reproduced the UNAIDS HIV prevalence curve in South Africa from 1990–2002. The calibration was sensitive to changes in the rate of formation of short-duration partnerships and to the partnership acquisition rate among high-risk individuals, both of which impacted concurrency. Runs that closely fit to historical HIV prevalence reflect diverse ranges for individual parameter values and predict a wide range of possible steady-state prevalence in the absence of interventions, illustrating the value of the calibration procedure and utility of the model for evaluating interventions. This model, which includes detailed behavioral patterns and HIV natural history, closely fits HIV prevalence estimates

Validation and Calibration of a Computer Simulation Model of Pediatric HIV Infection

Background: Computer simulation models can project long-term patient outcomes and inform health policy. We internally validated and then calibrated a model of HIV disease in children before initiation of antiretroviral therapy to provide a framework against which to compare the impact of pediatric HIV treatment strategies. Methods: We developed a patient-level (Monte Carlo) model of HIV progression among untreated children 1,300 untreated, HIV-infected African children. Results: In internal validation analyses, model-generated survival curves fit IeDEA data well; modeled and observed survival at 16 months of age were 91.2% and 91.1%, respectively. RMSE varied widely with variations in CD4% parameters; the best fitting parameter set (RMSE = 0.00423) resulted when CD4% was 45% at birth and declined by 6%/month (ages 0-3 months) and 0.3%/month (ages >3 months). In calibration analyses, increases in IeDEA-derived mortality risks were necessary to fit UNAIDS survival data. Conclusions: The CEPAC-Pediatric model performed well in internal validation analyses. Increases in modeled mortality risks required to match UNAIDS data highlight the importance of pre-enrollment mortality in many pediatric cohort studies

The value of confirmatory testing in early infant HIV diagnosis programmes in South Africa: A cost-effectiveness analysis

Background: The specificity of nucleic acid amplification tests (NAATs) used for early infant diagnosis (EID) of HIV infection is <100%, leading some HIV-uninfected infants to be incorrectly identified as HIV-infected. The World Health Organization recommends that infants undergo a second NAAT to confirm any positive test result, but implementation is limited. Our objective was to determine the impact and cost-effectiveness of confirmatory HIV testing for EID programmes in South Africa. Method and findings Using the Cost-effectiveness of Preventing AIDS Complications (CEPAC)–Pediatric model, we simulated EID testing at age 6 weeks for HIV-exposed infants without and with confirmatory testing. We assumed a NAAT cost of US$25, NAAT specificity of 99.6$1,790/infant tested, compared to US$1,830/infant tested without confirmatory testing. Confirmatory testing remained cost-saving unless NAAT cost exceeded US$400 or the HIV-uninfected status of infants incorrectly identified as infected was ascertained and ART stopped within 3 months of starting. Limitations include uncertainty in the data used in the model, which we examined with sensitivity and uncertainty analyses. We also excluded clinical harms to HIV-uninfected infants incorrectly treated with ART after false-positive diagnosis (e.g., medication toxicities); including these outcomes would further increase the value of confirmatory testing. Conclusions: Without confirmatory testing, in settings with MTCT rates similar to that of South Africa, more than 10% of infants who initiate ART may reflect false-positive diagnoses. Confirmatory testing prevents inappropriate HIV diagnosis, is cost-saving, and should be adopted in all EID programmes

The value of confirmatory testing in early infant HIV diagnosis programmes in South Africa: A cost-effectiveness analysis

Background: The specificity of nucleic acid amplification tests (NAATs) used for early infant diagnosis (EID) of HIV infection is <100%, leading some HIV-uninfected infants to be incorrectly identified as HIV-infected. The World Health Organization recommends that infants undergo a second NAAT to confirm any positive test result, but implementation is limited. Our objective was to determine the impact and cost-effectiveness of confirmatory HIV testing for EID programmes in South Africa. Method and findings Using the Cost-effectiveness of Preventing AIDS Complications (CEPAC)–Pediatric model, we simulated EID testing at age 6 weeks for HIV-exposed infants without and with confirmatory testing. We assumed a NAAT cost of US$25, NAAT specificity of 99.6$1,790/infant tested, compared to US$1,830/infant tested without confirmatory testing. Confirmatory testing remained cost-saving unless NAAT cost exceeded US$400 or the HIV-uninfected status of infants incorrectly identified as infected was ascertained and ART stopped within 3 months of starting. Limitations include uncertainty in the data used in the model, which we examined with sensitivity and uncertainty analyses. We also excluded clinical harms to HIV-uninfected infants incorrectly treated with ART after false-positive diagnosis (e.g., medication toxicities); including these outcomes would further increase the value of confirmatory testing. Conclusions: Without confirmatory testing, in settings with MTCT rates similar to that of South Africa, more than 10% of infants who initiate ART may reflect false-positive diagnoses. Confirmatory testing prevents inappropriate HIV diagnosis, is cost-saving, and should be adopted in all EID programmes

Point-of-Care CD4 Testing to Inform Selection of Antiretroviral Medications in South African Antenatal Clinics: A Cost-Effectiveness Analysis

Background: Many prevention of mother-to-child HIV transmission (PMTCT) programs currently prioritize antiretroviral therapy (ART) for women with advanced HIV. Point-of-care (POC) CD4 assays may expedite the selection of three-drug ART instead of zidovudine, but are costlier than traditional laboratory assays. Methods: We used validated models of HIV infection to simulate pregnant, HIV-infected women (mean age 26 years, gestational age 26 weeks) in a general antenatal clinic in South Africa, and their infants. We examined two strategies for CD4 testing after HIV diagnosis: laboratory (test rate: 96%, result-return rate: 87%, cost: $14) and POC (test rate: 99$26). We modeled South African PMTCT guidelines during the study period (WHO “Option A”): antenatal zidovudine (CD4 ≤350/μL) or ART (CD4>350/μL). Outcomes included MTCT risk at weaning (age 6 months), maternal and pediatric life expectancy (LE), maternal and pediatric lifetime healthcare costs (2013 USD), and cost-effectiveness ($/life-year saved). Results: In the base case, laboratory led to projected MTCT risks of 5.7$1,070/infant. POC led to lower modeled MTCT risk (5.3%), greater pediatric LE (53.4 years) and lower PMTCT plus pediatric lifetime costs ($1,040/infant). Maternal outcomes following laboratory were similar to POC (LE: 21.2 years; lifetime costs:$23,860/person). Compared to laboratory, POC improved clinical outcomes and reduced healthcare costs. Conclusions: In antenatal clinics implementing Option A, the higher initial cost of a one-time POC CD4 assay will be offset by cost-savings from prevention of pediatric HIV infection

Selected data parameters for CEPAC–Pediatric model analysis of early infant HIV diagnosis testing in South Africa.

<p>Selected data parameters for CEPAC–Pediatric model analysis of early infant HIV diagnosis testing in South Africa.</p

Univariate sensitivity analyses examining the impact of variation in individual input parameters on the difference in cost per HIV-exposed infant between the without and with confirmatory testing strategies.

<p>Key parameters varied in sensitivity analyses are shown on the left. Values in parentheses indicate the range examined (from the value leading to the lowest difference in cost to the value leading to the greatest difference, with base-case values after the semicolon). The horizontal axis shows the difference in cost between the 2 strategies: without confirmatory testing minus with confirmatory testing. The bounds of the blue bar indicate the cost differences at the extreme parameter values; longer bars therefore indicate parameters to which the model results were more sensitive. Where confidence intervals were available for the primary data estimates used in the base case, we indicate the bounds of these confidence intervals with brackets overlying the blue bars; the distance between brackets therefore indicates the degree to which the base-case estimates are affected by parameter uncertainty. The blue bar reaches the far left axis (indicating a cost difference of 0) at the threshold value for each parameter where confirmatory testing is no longer cost-saving compared to without confirmatory testing. The grey vertical line indicates the value for each parameter at the base-case result: a savings of US$40 per infant with confirmatory testing. ART, antiretroviral therapy; EID, early infant diagnosis; NAAT, nucleic acid amplification test.</p

Total lifetime costs per HIV-exposed infant by EID strategy.

<p>Columns include components of lifetime total costs per HIV-exposed infant tested: routine HIV care, CD4 and HIV viral load monitoring, OIs and end-of-life care, ART, EID costs, and false-positive costs. EID programme costs are shown in blue and comprise 2%–3% of lifetime costs, as shown previously [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002446#pmed.1002446.ref021" target="_blank">21</a>]; false-positive costs are shown in orange and are made up of all component costs acquired for HIV-infected infants other than OI costs. ART, antiretroviral therapy; EID, early infant diagnosis; FP, false-positive; OI, opportunistic infection.</p

Number of infants linked to ART after false-positive diagnosis, per 1,000 ART initiations, by assay specificity and MTCT risk.

<p>Multivariate sensitivity analysis varying specificity of the NAAT and infant HIV prevalence modelled by increasing MTCT risk. The vertical axis shows the number of infants with false-positive diagnosis initiating ART, per 1,000 ART initiations. Groups of coloured bars indicate 3 values for infant HIV prevalence at weaning (12 months of age): purple indicates a low MTCT risk scenario, with 12-month risk of 1.3%; green indicates the base-case value of 4.9%; and blue indicates a high MTCT risk scenario, with risk of 9.6%. Three values of NAAT specificity are shown within each MTCT risk scenario. For each combination of MTCT risk and NAAT specificity, bars indicate those who are truly HIV-uninfected (false-positive diagnosis). The left, dark-coloured bar in each pair reflects the outcome without confirmatory testing, and the right, light-coloured bar reflects the outcome with confirmatory testing. ART, antiretroviral therapy; EID, early infant diagnosis; MTCT, mother-to-child transmission; NAAT, nucleic acid amplification test.</p