Empirical validation of the UNAIDS Spectrum model for subnational HIV estimates: case-study of children and adults in Manicaland, Zimbabwe

Estimating HIV incidence over a decade in Zimbabwe: A comparison of the catalytic and Farrington models

Over the years, numerous modelling studies have been proposed to estimate HIV incidence. As a result, this study aimed to evaluate two alternative methods for predicting HIV incidence in Zimbabwe between 2005 and 2015. We estimated HIV incidence from seroprevalence data using the catalytic and Farrington-2-parameter models. Data were obtained from 2005-06, 2010-11, and 2015 Zimbabwe Demographic Health Survey (ZDHS). These models were validated at the micro and macro-level using community-based cohort incidence and empirical estimates from UNAIDS EPP/SPECTRUM, respectively. The HIV incidence for the catalytic model was 0.32% (CI: 0.28%, 0.36%), 0.36% (CI: 0.33%, 0.39%), and 0.28% (CI: 0.26%, 0.30%), for the years 2005-06, 2010-11, and 2015, respectively. The HIV incidence for the Farrington model was 0.21% (CI: 0.16%, 0.26%), 0.22% (CI: 0.20%, 0.25%), and 0.19% (CI: 0.16%, 0.22%), for the years 2005-06, 2010-11, and 2015, respectively. According to these findings, the catalytic model estimated a higher HIV incidence rate than the Farrington model. Compared to cohort estimates, the estimates were within the observed 95% confidence interval, with 88% and 75% agreement for the catalytic and Farrington models, respectively. The limits of agreement observed in the Bland-Altman plot were narrow for all plots, indicating that our model estimates were comparable to cohort estimates. Compared to UNAIDS estimates, the catalytic model predicted a progressive increase in HIV incidence for males throughout all survey years. Without a doubt, HIV incidence declined with each subsequent survey year for all models. To improve programmatic and policy decisions in the national HIV response, we recommend the triangulation of multiple methods for incidence estimation and interpretation of results. Multiple estimating approaches should be considered to reduce uncertainty in the estimations from various models.

Estimating the burden of pediatric HIV in an 'A' category district in India: an epidemiological study

BACKGROUND

India lacks epidemiological information on the disease burden of pediatric HIV. The National AIDS Control Program (NACP) estimates the numbers of HIV-positive children as a proportion of adult persons living with HIV. A third of HIV-positive children die before their first birthday and a half before they reach their second birthday. The early detection of HIV is crucial for the prevention of morbidities, growth delays, and death among HIV-positive children.

METHODS

The study aimed to estimate the disease burden of pediatric HIV among children in 'A' category district of a high HIV prevalence state. An 'A' category district is defined by the presence of > 1% HIV prevalence among the general population, as estimated by HIV Sentinel Surveillance. The study used an innovative three-pronged strategy combining cross-sectional and longitudinal methods. The overall burden of pediatric HIV was calculated as a product of cases detected multiplied by a net inflation factor, for each of three strategies.

RESULTS

The existing pool of HIV infection in the district is estimated to be 3266 (95% CI: 2621-4197) HIV positive children < 15 years of age, in a mid-year (2013) projected child population of about 1.4 million, thus giving an HIV prevalence of 0.23% (CI: 0.19-0.30) among children (0-14 years of age). The proportion of children among all people living with HIV in the district works out to 10.4% (CI: 8.6-13.5%).

CONCLUSIONS

The study estimate of 0.23% HIV prevalence among children (0-14 years of age) is higher than the NACP estimates (0.02) and is 2.5 higher than the Karnataka state estimate (0.09)²². Similarly, the proportion of children among all persons living with HIV in Belgaum district is 10.4% in this study, as against 6.54% for India. The study methodology is replicable for other settings and other diseases.

Comparison of HIV Incidence in the Zimbabwe Population-Based HIV Impact Assessment Survey (2015-2016) with Modeled Estimates: Progress Toward Epidemic Control

Between October 2015 and August 2016, Zimbabwe conducted the Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) cross-sectional survey to determine progress toward epidemic control. Of 25,131 eligible adults aged 15-64 years, 20,577 (81.8%) consented to face-to-face questionnaire and biomarker testing in this nationally representative household survey. Home-based rapid HIV testing was performed using Determine, First Response, and STAT-PAK as the tiebreaker. HIV-positive tests were confirmed in a laboratory using Geenius HIV-1/2; viral load (VL) was measured using Roche TaqMan and BioMerieux NucliSENS. Recency of infection was tested using Sedia HIV-1 Limiting Antigen (LAg)-Avidity. Presence of antiretroviral (ARV) drugs was detected using high performance liquid chromatography/mass spectrometry (HPLC/MS). The recent infection testing algorithm included LAg-avidity enzyme immunoassay [normalized optical density (ODn ≤1.5), VL ≥1,000 copies/mL, and absence of ARV drugs]. Weighted annual HIV incidence was compared with United Nations Joint Programme on HIV/AIDS (UNAIDS) Spectrum models estimates. Overall, 26 of 2,901 HIV-seropositive individuals had a recent infection (men, 8; women, 18). Overall weighted annual incidence among persons aged 15-64 years was 0.42% [95% confidence interval (CI): 0.25-0.59] and was 0.44% (95% CI: 0.25-0.62) for those aged 15-49 years, similar to 2016 Spectrum model estimate (0.54%, 95% CI: 0.49-0.66) for this age group. Among persons aged 15-49 years, HIV prevalence was 13.35% (95% CI: 12.71-14.02), estimated HIV-positive individuals were 968,951 (95% CI: 911,473-1,026,430), of these, 41,911 (95% CI: 37,412-44,787) were annual-new infections, and this was similar to 2016 Spectrum estimates. The observed HIV incidence in ZIMPHIA 2015-2016 validated the 2016 Spectrum estimates and Zimbabwe's progress toward epidemic control.

Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care

INTRODUCTION

Integrating services for non-communicable diseases (NCDs) into existing primary care platforms such as HIV programmes has been recommended as a way of strengthening health systems, reducing redundancies and leveraging existing systems to rapidly scale-up underdeveloped programmes. Mathematical modelling provides a powerful tool to address questions around priorities, optimization and implementation of such programmes. In this study, we examine the case for NCD-HIV integration, use Kenya as a case-study to highlight how modelling has supported wider policy formulation and decision-making in healthcare and to collate stakeholders' recommendations on use of models for NCD-HIV integration decision-making.

DISCUSSION

Across Africa, NCDs are increasingly posing challenges for health systems, which historically focused on the care of acute and infectious conditions. Pilot programmes using integrated care services have generated advantages for both provider and user, been cost-effective, practical and achieve rapid coverage scale-up. The shared chronic nature of NCDs and HIV means that many operational approaches and infrastructure developed for HIV programmes apply to NCDs, suggesting this to be a cost-effective and sustainable policy option for countries with large HIV programmes and small, un-resourced NCD programmes. However, the vertical nature of current disease programmes, policy financing and operations operate as barriers to NCD-HIV integration. Modelling has successfully been used to inform health decision-making across a number of disease areas and in a number of ways. Examples from Kenya include (i) estimating current and future disease burden to set priorities for public health interventions, (ii) forecasting the requisite investments by government, (iii) comparing the impact of different integration approaches, (iv) performing cost-benefit analysis for integration and (v) evaluating health system capacity needs.

CONCLUSIONS

Modelling can and should play an integral part in the decision-making processes for health in general and NCD-HIV integration specifically. It is especially useful where little data is available. The successful use of modelling to inform decision-making will depend on several factors including policy makers' comfort with and understanding of models and their uncertainties, modellers understanding of national priorities, funding opportunities and building local modelling capacity to ensure sustainability.

Trends in proportion of older HIV-infected people in care in Latin America and the Caribbean: a growing challenge

We aimed to quantify the proportion of people receiving care for HIV-infection that are 50 years or older (older HIV patients) in Latin America and the Caribbean between 2000 and 2015 and to estimate the contribution to the growth of this population of people enrolled before (<50yo) and after 50 years old (yo) (⩾50yo). We used a series of repeated, cross-sectional measurements over time in the Caribbean, Central and South American network (CCASAnet) cohort. We estimated the percentage of patients retained in care each year that were older HIV patients. For every calendar year, we divided patients into two groups: those who enrolled before age 50 and after age 50. We used logistic regression models to estimate the change in the proportion of older HIV patients between 2000 and 2015. The percentage of CCASAnet HIV patients over 50 years had a threefold increase (8% to 24%) between 2000 and 2015. Most of the growth of this population can be explained by the increasing proportion of people that enrolled before 50 years and aged in care. These changes will impact needs of care for people living with HIV, due to multiple comorbidities and high risk of disability associated with aging.

Documenting and explaining the HIV decline in east Zimbabwe: the Manicaland General Population Cohort

PURPOSE

The Manicaland cohort was established to provide robust scientific data on HIV prevalence and incidence, patterns of sexual risk behaviour and the demographic impact of HIV in a sub-Saharan African population subject to a generalised HIV epidemic. The aims were later broadened to include provision of data on the coverage and effectiveness of national HIV control programmes including antiretroviral therapy (ART).

PARTICIPANTS

General population open cohort located in 12 sites in Manicaland, east Zimbabwe, representing 4 major socioeconomic strata (small towns, agricultural estates, roadside settlements and subsistence farming areas). 9,109 of 11,453 (79.5%) eligible adults (men 17-54 years; women 15-44 years) were recruited in a phased household census between July 1998 and January 2000. Five rounds of follow-up of the prospective household census and the open cohort were conducted at 2-year or 3-year intervals between July 2001 and November 2013. Follow-up rates among surviving residents ranged between 77.0% (over 3 years) and 96.4% (2 years).

FINDINGS TO DATE

HIV prevalence was 25.1% at baseline and had a substantial demographic impact with 10-fold higher mortality in HIV-infected adults than in uninfected adults and a reduction in the growth rate in the worst affected areas (towns) from 2.9% to 1.0%pa. HIV infection rates have been highest in young adults with earlier commencement of sexual activity and in those with older sexual partners and larger numbers of lifetime partners. HIV prevalence has since fallen to 15.8% and HIV incidence has also declined from 2.1% (1998-2003) to 0.63% (2009-2013) largely due to reduced sexual risk behaviour. HIV-associated mortality fell substantially after 2009 with increased availability of ART.

FUTURE PLANS

We plan to extend the cohort to measure the effects on the epidemic of current and future HIV prevention and treatment programmes. Proposals for access to these data and for collaboration are welcome.

Improving estimates of children living with HIV from the Spectrum AIDS Impact Model

OBJECTIVE

Estimated numbers of children living with HIV determine programmatic and treatment needs. We explain the changes made to the UNAIDS estimates between 2015 and 2016, and describe the challenges around these estimates.

METHODS

Estimates of children newly infected, living with HIV, and dying of AIDS are developed by country teams using Spectrum software. Spectrum files are available for 160 countries, which represent 98% of the global population. In 2016, the methods were updated to reflect the latest evidence on mother-to-child HIV transmission and improved assumptions on the age children initiate antiretroviral therapy. We report updated results using the 2016 model and validate these estimates against mother-to-child transmission rates and HIV prevalence from population-based surveys for the survey year.

RESULTS

The revised 2016 model estimates 27% fewer children living with HIV in 2014 than the 2015 model, primarily due to changes in the probability of mother-to-child transmission among women with incident HIV during pregnancy. The revised estimates were consistent with population-based surveys of HIV transmission and HIV prevalence among children aged 5-9 years, but were lower than surveys among children aged 10-14 years.

CONCLUSIONS

The revised 2016 model is an improvement on previous models. Paediatric HIV models will continue to evolve as further improvements are made to the assumptions. Commodities forecasting and programme planning rely on these estimates, and increasing accuracy will be critical to enable effective scale-up and optimal use of resources. Efforts are needed to improve empirical measures of HIV prevalence, incidence, and mortality among children.