Estimating the HIV incidence rate: recent and future developments

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.

Facilitating Next-Generation Pre-Exposure Prophylaxis Clinical Trials Using HIV Recent Infection Assays: A Consensus Statement from the Forum HIV Prevention Trial Design Project

Standard-of-care HIV pre-exposure prophylaxis (PrEP) is highly efficacious, but uptake of and persistence on a daily oral pill is low in many settings. Evaluation of alternate PrEP products will require innovation to avoid the unpractically large sample sizes in noninferiority trials. We propose estimating HIV incidence in people not on PrEP as an external counterfactual to which on-PrEP incidence in trial subjects can be compared. HIV recent infection testing algorithms (RITAs), such as the limiting antigen avidity assay plus viral load used on specimens from untreated HIV positive people identified during screening, is one possible approach. Its feasibility is partly dependent on the sample size needed to ensure adequate power, which is impacted by RITA performance, the number of recent infections identified, the expected efficacy of the intervention, and other factors. Screening sample sizes to support detection of an 80% reduction in incidence for 3 key populations are more modest, and comparable to the number of participants in recent phase III PrEP trials. Sample sizes would be significantly larger in populations with lower incidence, where the false recency rate is higher or if PrEP efficacy is expected to be lower. Our proposed counterfactual approach appears to be feasible, offers high statistical power, and is nearly contemporaneous with the on-PrEP population. It will be important to monitor the performance of this approach during new product development for HIV prevention. If successful, it could be a model for preventive HIV vaccines and prevention of other infectious diseases.

Probabilistic HIV recency classification-a logistic regression without labeled individual level training data

Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest risk of new infection, and evaluating existing programs of prevention and treatment. Starting from 2015, the Population-based HIV Impact Assessment (PHIA) individual-level surveys are implemented in the most-affected countries in sub-Saharan Africa. PHIA is a nationally-representative HIV-focused survey that combines household visits with key questions and cutting-edge technologies such as biomarker tests for HIV antibody and HIV viral load which offer the unique opportunity of distinguishing between recent infection and long-term infection, and providing relevant HIV information by age, gender, and location. In this article, we propose a semi-supervised logistic regression model for estimating individual level HIV recency status. It incorporates information from multiple data sources - the PHIA survey where the true HIV recency status is unknown, and the cohort studies provided in the literature where the relationship between HIV recency status and the covariates are presented in the form of a contingency table. It also utilizes the national level HIV incidence estimates from the epidemiology model. Applying the proposed model to Malawi PHIA data, we demonstrate that our approach is more accurate for the individual level estimation and more appropriate for estimating HIV recency rates at aggregated levels than the current practice - the binary classification tree (BCT).

Subnational HIV incidence trends in Malawi: large, heterogeneous declines across space

The rate of new HIV infections globally has decreased substantially from its peak in the late 1990s, but the epidemic persists and remains highest in many countries in eastern and southern Africa. Previous research hypothesised that, as the epidemic recedes, it will become increasingly concentrated among sub-populations and geographic areas where transmission is the highest and that are least effectively reached by treatment and prevention services. However, empirical data on subnational HIV incidence trends is sparse, and the local transmission rates in the context of effective treatment scale-up are unknown. In this work, we developed a novel Bayesian spatio-temporal epidemic model to estimate adult HIV prevalence, incidence and treatment coverage at the district level in Malawi from 2010 through the end of 2021. We found that HIV incidence decreased in every district of Malawi between 2010 and 2021 but the rate of decline varied by area. National-level treatment coverage more than tripled between 2010 and 2021 and more than doubled in every district. Large increases in treatment coverage were associated with declines in HIV transmission, with 12 districts having incidence-prevalence ratios of 0.03 or less (a previously suggested threshold for epidemic control). Across districts, incidence varied more than HIV prevalence and ART coverage, suggesting that the epidemic is becoming increasingly spatially concentrated. Our results highlight the success of the Malawi HIV treatment programme over the past decade, with large improvements in treatment coverage leading to commensurate declines in incidence. More broadly, we demonstrate the utility of spatially resolved HIV modelling in generalized epidemic settings. By estimating temporal changes in key epidemic indicators at a relatively fine spatial resolution, we were able to directly assess, for the first time, whether the ART scaleup in Malawi resulted in spatial gaps or hotspots. Regular use of this type of analysis will allow HIV program managers to monitor the equity of their treatment and prevention programmes and their subnational progress towards epidemic control.

Methods and indicators to validate country reductions in incidence of hepatitis C virus infection to elimination levels set by WHO

One of the main goals of the 2016 Global Health Sector Strategy on viral hepatitis is the elimination of hepatitis C virus (HCV) as a public health problem by 2030, defined as an 80% reduction in incidence and 65% reduction in mortality relative to 2015. Although monitoring HCV incidence is key to validating HCV elimination, use of the gold-standard method, which involves prospective HCV retesting of people at risk, can be prohibitively resource-intensive. Additionally, few countries collected quality data in 2015 to enable an 80% decrease by 2030 to be calculated. Here, we first review different methods of monitoring HCV incidence and discuss their resource implications and applicability to various populations. Second, using mathematical models developed for various global settings, we assess whether trends in HCV chronic prevalence or HCV antibody prevalence or scale-up levels for HCV testing, treatment, and preventative interventions can be used as reliable alternative indicators to validate the HCV incidence target. Third, we discuss the advantages and disadvantages of an absolute HCV incidence target and suggest a suitable threshold. Finally, we propose three options that countries can use to validate the HCV incidence target, depending on the available surveillance infrastructure.

Estimation of HIV incidence from analysis of HIV prevalence patterns by age and years since starting sex work among female sex workers in Zimbabwe

OBJECTIVES

To estimate HIV incidence among female sex workers (FSW) in Zimbabwe: using HIV prevalence by age and number of years since started selling sex (YSSS).

DESIGN

We pooled data from FSW aged 18-39 participating in respondent-driven sampling surveys conducted in Zimbabwe between 2011-2017.

METHODS

For each year of age, we estimated: HIV prevalence (Pt) and the change in HIV prevalence from the previous age (Pt-Pt-1). We then estimated the rate of new HIV infections during that year of age: It = Pt-Pt-1/(1-Pt-1), and calculated HIV incidence for 18-24 and 25-39 year-olds separately as the weighted average of It. We estimated HIV incidence for FSW 1-5 years and 6-15 years since first selling sex using the same approach, and compared HIV prevalence among FSW first selling sex at their current age with the general population.

RESULTS

Among 9,906 women, 50.2% were HIV positive. Based on HIV prevalence increases by age, we estimated an HIV incidence of 6.3/100 person-years at risk (pyar) (95%CI 5.3,7.6) among 18-24 year-olds, and 3.3/100 pyar (95% CI 1.3,4.2) among 25-39 year-olds. Based on prevalence increases by YSSS, HIV incidence was 5.3/100 pyar (95% CI 4.3,8.5) between 1-5 years since first selling sex, and 2.1/100 pyar (95% CI -1.3, 7.2) between 6-15 years.

CONCLUSIONS

Our analysis is consistent with very high HIV incidence among FSW in Zimbabwe, especially among those who are young and recently started selling sex. There is a critical need to engage young entrants into sex work in interventions that reduce their HIV risk.

Inferring population HIV incidence trends from surveillance data of recent HIV infection among HIV testing clients

BACKGROUND

Measuring recent HIV infections from routine surveillance systems could allow timely and granular monitoring of HIV incidence patterns. We evaluated the relationship of two recent infection indicators with alternative denominators to true incidence patterns.

METHODS

We used a mathematical model of HIV testing behaviours, calibrated to population-based surveys and HIV testing services programme data, to estimate the number of recent infections diagnosed annually from 2010 to 2019 in Côte d'Ivoire, Malawi, and Mozambique. We compared two different denominators to interpret recency data: those at risk of HIV acquisition (HIV-negative tests and recent infections) and all people testing HIV positive. Sex and age-specific longitudinal trends in both interpretations were then compared with modelled trends in HIV incidence, testing efforts and HIV positivity among HIV testing services clients.

RESULTS

Over 2010-2019, the annual proportion of the eligible population tested increased in all countries, while positivity decreased. The proportion of recent infections among those at risk of HIV acquisition decreased, similar to declines in HIV incidence among adults (≥15 years old). Conversely, the proportion of recent infections among HIV-positive tests increased. The female-to-male ratio of the proportion testing recent among those at risk was closer to 1 than the true incidence sex ratio.

CONCLUSION

The proportion of recent infections among those at risk of HIV acquisition is more indicative of HIV incidence than the proportion among HIV-positive tests. However, interpreting the observed patterns as surrogate measures for incidence patterns may still be confounded by different HIV testing rates between population groups or over time.

Regional disparity of HIV incidence and prevalence among men who have sex with men

BACKGROUND

HIV incidence can be estimated with cross-sectional studies using clinical, serological, and molecular data. Worldwide, HIV incidence data in only men who have sex with men (MSM) are scarce and principally focus on those with healthcare or under treatment. However, better estimates can be obtained through studies with national representativeness. The objective was to estimate the prevalence, incidence, and factors associated with acquiring HIV in a national sample of MSM who attend meeting places, considering geographical regions.

METHODS

A nationally representative survey of MSM attending meeting places was performed in Mexico. Participants answered a questionnaire, and a dried blood spot (DBS) was collected. Samples were classified as recent infections using an algorithm with HIV status, antiretroviral therapy, and the result of BED-EIA assay. Parameters were analysed considering regions and demographic and sexual behaviour characteristics.

RESULTS

The national HIV prevalence was 17.4% with regional differences; the highest prevalence (20.7%) was found in Mexico City, and the lowest prevalence was found in the West region (11.5%). The incidence was 9.4 per 100 p/y, with regional values from 6.2 to 13.2 for the Northeast and the Centre regions, respectively. Age, age at sexual debut, low wealth index, and rewarded sex were associated with HIV prevalence. Centre region, use of private clinics as health services, and having sex exclusively with men were associated with recent HIV infections.

CONCLUSIONS

The incidence and prevalence showed regional differences, suggesting a difference in the dynamics of HIV transmission; some regions have a greater case accumulation, and others have a greater rate of new infections. Understanding this dynamic will allow developing health programs focused on HIV prevention or treating people already living with HIV.

Estimation of time of HIV seroconversion using a modified CD4 depletion model

Introduction

Several methods have been proposed to estimate the time of HIV seroconversion, including those based on CD4 cell depletion models. However, previous models have failed to consider the heterogeneity that exists in CD4 trajectories among different sub-populations. Our objective was to estimate the time from HIV seroconversion relative to the HIV diagnosis date in a population-based cohort of people living with HIV (PLWH) in the province of British Columbia, Canada.

Methods

We used linked administrative and clinical data from the British Columbia Seek and Treat for Optimal Prevention of HIV/AIDS (STOP HIV/AIDS) cohort, which contains longitudinal individual-level data on all PLWH ever diagnosed in the province. Eligible participants were aged ≥18 years and diagnosed with HIV between 1989 and 2013. The outcome was pre-antiretroviral treatment CD4 cell count measurements assessed every six months. Models were stratified by age and stage of HIV infection at diagnosis. Several explanatory variables were considered including longitudinal viral load measurements. Longitudinal CD4, square root transformed, was modeled via a non-linear mixed effects model; time was modeled using an exponential decay function. We assumed a Gaussian distribution (identity link), an AR(1) correlation structure, and a random intercept and slope for the longitudinal viral load measurements. Due to the population variation in CD4 count among uninfected individuals, we assumed 500 to 1500 cells/mm³ as the normal range when estimating the time of HIV seroconversion.

Results

Longitudinal data on 1,253 individuals were analysed: 80% male, 33% White, and the median age at diagnosis was 38 years (25^th-75^th percentile [Q₁-Q₃], 31 to 45). CD4 decay differed by stage of infection at diagnosis and age, with those ≥50 years in Stages 1 and 2 experiencing a faster decline in CD4 over time. The median duration of infection from seroconversion until HIV diagnosis was 6.9 (Q₁-Q₃, 3.9 to 10.1) years.

Conclusions

Considering the heterogeneity that exists in individual CD4 cell trajectories in a population, we presented a methodology that only relies on routinely collected HIV-related data, which can be further extended to estimate other epidemic measures.

Performance of a Modified In-House HIV-1 Avidity Assay among a Cohort of Newly Diagnosed HIV-1 Infected Individuals and the Effect of ART on the Maturation of HIV-1 Specific Antibodies

BACKGROUND

Viral kinetics impact humoral immune response to HIV; antibody avidity testing helps distinguish recent (<6 months) and long-term HIV infection. This study aims to determine the frequency of recent HIV-1 infection among clients attending ICTC (Integrated Counselling and Testing Centre) using a commercial EIA, to correlate it with a modified in-house avidity assay and to study the impact of ART on anti-HIV-1 antibody maturation.

METHODS

Commercial LAg Avidity EIA was used to detect antibody avidity among 117 treatment naïve HIV-1 infected individuals. A second-generation HIV ELISA was modified for in-house antibody avidity testing and cutoff was set based on Receiver Operating Characteristic (ROC) analysis. Archived paired samples from 25 HIV-1 infected individuals before ART and after successful ART; samples from 7 individuals responding to ART and during virological failure were also tested by LAg Avidity EIA.

RESULTS

Six individuals (5.1%) were identified as recently infected by a combination of LAg avidity assay and HIV-1 viral load testing. The modified in-house avidity assay demonstrated sensitivity and specificity of 100% and 98.2%, respectively, at AI=0.69 by ROC analysis. Median ODn values of individuals when responding to ART were significantly lower than pre-ART [4.136 (IQR 3.437- 4.827) vs 4.455 (IQR 3.748-5.120), p=0.006] whereas ODn values were higher during virological failure [4.260 (IQR 3.665 - 4.515) vs 2.868 (IQR 2.247 - 3.921), p=0.16].

CONCLUSION

This modified in-house antibody avidity assay is an inexpensive method to detect recent HIV-1 infection. ART demonstrated significant effect on HIV-1 antibody avidity owing to changes in viral kinetics.

Cross-sectional human immunodeficiency virus incidence estimation accounting for heterogeneity across communities

Accurate estimation of human immunodeficiency virus (HIV) incidence rates is crucial for the monitoring of HIV epidemics, the evaluation of prevention programs, and the design of prevention studies. Traditional cohort approaches to measure HIV incidence require repeatedly testing large cohorts of HIV-uninfected individuals with an HIV diagnostic test (eg, enzyme-linked immunosorbent assay) for long periods of time to identify new infections, which can be prohibitively costly, time-consuming, and subject to loss to follow-up. Cross-sectional approaches based on the usual HIV diagnostic test and biomarkers of recent infection offer important advantages over standard cohort approaches, in terms of time, cost, and attrition. Cross-sectional samples usually consist of individuals from different communities. However, small sample sizes limit the ability to estimate community-specific incidence and existing methods typically ignore heterogeneity in incidence across communities. We propose a permutation test for the null hypothesis of no heterogeneity in incidence rates across communities, develop a random-effects model to account for this heterogeneity and to estimate community-specific incidence, and provide one way to estimate the coefficient of variation. We evaluate the performance of the proposed methods through simulation studies and apply them to the data from the National Institute of Mental Health Project ACCEPT, a phase 3 randomized controlled HIV prevention trial in Sub-Saharan Africa, to estimate the overall and community-specific HIV incidence rates.

Modeling methods for estimating HIV incidence: a mathematical review

Estimating HIV incidence is crucial for monitoring the epidemiology of this infection, planning screening and intervention campaigns, and evaluating the effectiveness of control measures. However, owing to the long and variable period from HIV infection to the development of AIDS and the introduction of highly active antiretroviral therapy, accurate incidence estimation remains a major challenge. Numerous estimation methods have been proposed in epidemiological modeling studies, and here we review commonly-used methods for estimation of HIV incidence. We review the essential data required for estimation along with the advantages and disadvantages, mathematical structures and likelihood derivations of these methods. The methods include the classical back-calculation method, the method based on CD4+ T-cell depletion, the use of HIV case reporting data, the use of cohort study data, the use of serial or cross-sectional prevalence data, and biomarker approach. By outlining the mechanistic features of each method, we provide guidance for planning incidence estimation efforts, which may depend on national or regional factors as well as the availability of epidemiological or laboratory datasets.

Evaluation of an HIV recent infection testing algorithm with serological assays among men who have sex with men in Mexico

BACKGROUND

Human immunodeficiency virus (HIV) incidence should be calculated in cross-sectional studies using recent infection testing algorithms (RITA) that consider clinical variables and serological test results such as enzyme-linked immunosorbent assay (ELISA) and dried blood spot (DBS) analysis.

METHODS

The correlation between serum samples and DBS was evaluated using two commercial ELISA kits: SediaTM BED HIV-1 Incidence EIA (BED-Sedia) and Maxim HIV-1 Limiting Antigen Avidity (LAg-Avidity). Eight different RITAs were developed; all of them included serological assays. A combination of the variables viral load, antiretroviral therapy (ART) and CD4 count was used to build the RITAs. The sensitivity, specificity, Youden index, predictive positive value, predictive negative value, false recent rate (FRR) and false long-term rate were evaluated.

RESULTS

The correlations between serum samples and DBS were 0.990 and 0.867 for BED-Sedia and LAg-avidity, respectively. Using only serological assays, the Youden index was higher for LAg-avidity than BED-Sedia (82.1-83.0% versus 69.2-69.6%). The best RITA was ART-serology, which showed a Youden index of 91.2-93.9% and FRR of 1.8-2.2%.

CONCLUSIONS

Using DBS samples to determine HIV incidence is a good tool for epidemiological surveillance. The RITA that included ART and serological tests (BED-Sedia or LAg-avidity) showed the highest sensitivity and specificity and a low FRR.

Estimation of the burden of people living with Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) in Kerala state, India

Background

Worldwide, 36.7 million people were infected with Acquired Immunodeficiency Syndrome (AIDS) by the end of 2015. Over the period 2007 to 2015, there was a declining trend in the prevalence of adult Human Immunodeficiency Virus (HIV) in the state of Kerala, India. The current study aims to find a suitable statistical modelling technique for the distribution of HIV incubation time and predict the cumulative number of AIDS cases.

Materials and Methods

The requisite data were obtained from the Kerala State AIDS Control Society (KSACS) for the years 2007 to 2015. To assess the distribution of HIV incubation time, the data of 22 HIV-infected Keralite patients were retrieved from the medical records of a teaching hospital. Data included age, gender, and incubation time. The back-calculation method was utilized to predict the cumulative HIV/AIDS cases.

Results

The estimated total cumulative AIDS cases in Kerala for the years 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014 and 2015 were found to be 35,777, 48,944, 62,039, 45,669, 45,668, and 43,605, 42,377, 39,362, 37,617, 39,583, 25,414 respectively using back-calculation method with Weibull (2) incubation time distribution. The mean incubation time of the total HIV cases (male and female) was 4.4 years which indicates a rapid progression of the disease in the state of Kerala.

Conclusion

The back-calculation method is a powerful tool to estimate the cumulative frequency of AIDS cases; which predicted a declining HIV trend among Keralites. Moreover, the Weibull distribution is the best fitted distribution for HIV incubation time in our population.

Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015

BACKGROUND

Botswana is close to reaching the UNAIDS "90-90-90" HIV testing, antiretroviral treatment (ART), and viral suppression goals. We sought to determine HIV incidence in this setting with both high HIV prevalence and high ART coverage.

METHODS

We used a cross-sectional approach to assessing HIV incidence. A random, population-based sample of adults age 16-64 years was enrolled in 30 rural and peri-urban communities as part of the Botswana Combination Prevention Project (BCPP), from October 2013 -November 2015. Data and samples from the baseline household survey were used to estimate cross-sectional HIV incidence, following an algorithm that combined Limiting-Antigen Avidity Assay (LAg-Avidity EIA), ART status (documented or by testing ARV drugs in plasma) and HIV-1 RNA load. The LAg-Avidity EIA cut-off normalized optical density (ODn) was set at 1.5. The HIV-1 RNA cut-off was set at 400 copies/mL. For estimation purposes, the Mean Duration of Recent Infection was 130 days and the False Recent Rate (FRR) was evaluated at values of either 0 or 0.39%.

RESULTS

Among 12,610 individuals participating in the baseline household survey, HIV status was available for 12,570 participants and 3,596 of them were HIV positive. LAg-Avidity EIA data was generated for 3,581 (99.6%) of HIV-positive participants. Of 326 participants with ODn ≤1.5, 278 individuals were receiving ART verified through documentation and were considered to represent longstanding HIV infections. Among the remaining 48 participants who reported no use of ART, 14 had an HIV-1 RNA load ≤400 copies/mL (including 3 participants with ARVs in plasma) and were excluded, as potential elite/viremic controllers or undisclosed ART. Thus, 34 LAg-Avidity-EIA-recent, ARV-naïve individuals with detectable HIV-1 RNA (>400 copies/mL) were classified as individuals with recent HIV infections. The annualized HIV incidence among 16-64 year old adults was estimated at 1.06% (95% CI 0.68-1.45%) with zero FRR, and at 0.64% (95% CI 0.24-1.04%) using a previously defined FRR of 0.39%. Within a subset of younger individuals 16-49 years old, the annualized HIV incidence was estimated at 1.29% (95% CI 0.82-1.77%) with zero FRR, and at 0.90% (95% CI 0.42-1.38%) with FRR set to 0.39%.

CONCLUSIONS

Using a cross-sectional estimate of HIV incidence from 2013-2015, we found that at the time of near achievement of the UNAIDS 90-90-90 targets, ~1% of adults (age 16-64 years) in Botswana's rural and peri-urban communities became HIV infected annually.

Estimating dengue incidence and hospitalization in Malaysia, 2001 to 2013

Background

Epidemiologic measures of the dengue burden such as prevalence and incidence are important for policy-making and monitoring the progress of disease control. It is a common practice where epidemiologic and economic research estimate dengue burden based on notification data. However, a basic challenge in estimating the incidence of dengue is that a significant proportion of infected population are asymptomatic. It can be overcome by using mathematical models that relate observed prevalence and mortality to incidence. In this study, we estimate the trend of dengue incidence and hospitalization in Malaysia.

Methods

This study is based entirely on the available secondary data sources on dengue in Malaysia. The age-specific incidence of dengue between 2001 and 2013 was estimated using the prevalence and mortality estimates in an incidence-prevalence-mortality (IPM) model. Data on dengue prevalence were extracted from six sero-surveys conducted in Malaysia between 2001 and 2013; while statistics on dengue notification and Case Fatality Rate were derived from National Dengue Surveillance System. Dengue hospitalization data for the years 2009 to 2013 were extracted from the Health Informatics Centre and the volumes of dengue hospitalization for hospitals with missing data were estimated with Poisson models.

Results

The dengue incidence in Malaysia varied from 69.9 to 93.4 per 1000 population (pkp) between 2001 and 2013.The temporal trend in incidence rate was decreasing since 2001. It has been reducing at an average rate of 2.57 pkp per year from 2001 to 2013 (p = 0.011). The age-specific incidence of dengue decreased steadily with dengue incidence reaching zero by age > 70 years. Dengue notification rate has remained stable since 2001 and the number of notified cases each year was only a small fraction of the incident cases (0.7 to 2.3%). Similarly, the dengue hospitalization was larger but still a small fraction of the incident cases (3.0 to 5.6%).

Conclusion

Dengue incidence can be estimated with the use of sero-prevalence surveys and mortality data. This study highlights a reducing trend of dengue incidence in Malaysia and demonstrates the discrepancy between true dengue disease burden and cases reported by national surveillance system. Sero-prevalence studies with representative samples should be conducted regularly to allow better estimation of dengue burden in Malaysia.

Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection

Background

There is today no gold standard method to accurately define the time passed since infection at HIV diagnosis. Infection timing and incidence measurement is however essential to better monitor the dynamics of local epidemics and the effect of prevention initiatives.

Methods

Three methods for infection timing were evaluated using 237 serial samples from documented seroconversions and 566 cross sectional samples from newly diagnosed patients: identification of antibodies against the HIV p31 protein in INNO-LIA, SediaTM BED CEIA and SediaTM LAg-Avidity EIA. A multi-assay decision tree for infection timing was developed.

Results

Clear differences in recency window between BED CEIA, LAg-Avidity EIA and p31 antibody presence were observed with a switch from recent to long term infection a median of 169.5, 108.0 and 64.5 days after collection of the pre-seroconversion sample respectively. BED showed high reliability for identification of long term infections while LAg-Avidity is highly accurate for identification of recent infections. Using BED as initial assay to identify the long term infections and LAg-Avidity as a confirmatory assay for those classified as recent infection by BED, explores the strengths of both while reduces the workload. The short recency window of p31 antibodies allows to discriminate very early from early infections based on this marker. BED recent infection results not confirmed by LAg-Avidity are considered to reflect a period more distant from the infection time. False recency predictions in this group can be minimized by elimination of patients with a CD4 count of less than 100 cells/mm3 or without no p31 antibodies. For 566 cross sectional sample the outcome of the decision tree confirmed the infection timing based on the results of all 3 markers but reduced the overall cost from 13.2 USD to 5.2 USD per sample.

Conclusions

A step-wise multi assay decision tree allows accurate timing of the HIV infection at diagnosis at affordable effort and cost and can be an important new tool in studies analyzing the dynamics of local epidemics or the effects of prevention strategies.

Household survey of HIV incidence in Rwanda: a national observational cohort study

BACKGROUND

In Rwanda, HIV prevalence among adults aged 15-49 years has been stable at 3% since 2005. The aim of this study was to characterise HIV incidence across Rwanda.

METHODS

We did a nationally representative, prospective HIV incidence survey for the period of 2013-14, which used two-stage sampling. We randomly selected 492 villages in the first sampling stage and 14 households per village in the second stage. Participants completed a questionnaire and 14 140 people were tested for HIV. 13 728 participants were HIV negative, and were enrolled in the incidence cohort. Participants were retested and surveyed again after 12 months. Weights were calculated as the inverse of the probability to select the villages and the households.

FINDINGS

The study period was from Nov 5, 2013, to Nov 15, 2014. Among 14 222 respondents from 6792 households, 14 140 were tested for HIV and 13 728 were HIV negative. Of 12 593 people who participated in the endpoint data collection activities, 5965 (47·4%) were men and the mean age was 30 years (SD 10·8). 11 237 (89·2%) participants lived in rural areas, 4826 (38·3%) were single, and 7140 (56·7%) were married or cohabitating. During the year, 35 participants had seroconversion, including 13 men and 22 women, resulting in an overall incidence of 0·27 per 100 person-years (95% CI 0·18-0·35). Incidence was 0·21 per 100 person-years (0·10-0·32) in men and 0·32 per 100 person-years (0·19-0·45) in women. Our findings suggested multiple breakouts, with multiple seroconversions occurring in three villages and two households. Incidence was higher in adults aged 36-45 years (0·37 per 100 person-years, 0·12-0·62; adjusted hazard ratio [aHR] 4·49, 95% CI 1·30-14·70) relative to those aged 16-25, higher in western province (0·57 per 100 person-years, 0·31-0·87; aHR 5·90, 1·33-25·28) relative to the northern province, and higher in urban areas (0·65 per 100 person-years, 0·23-1·07; aHR 3·10, 1·28-6·99) than in rural areas.

INTERPRETATION

The incidence of HIV in Rwanda was higher than that previously estimated from models, with outbreaks seeming to contribute to the ongoing epidemic. Characterisation of incident infections can help the national HIV programmes to plan for preventive interventions tailored to the most at risk populations.

FUNDING

Global Fund to Fight HIV, Tuberculosis and Malaria, WHO Rwanda, UNAIDS Rwanda, and the Government of Rwanda.

Estimating False-Recent Classification for the Limiting-Antigen Avidity EIA and BED-Capture Enzyme Immunoassay in Vietnam: Implications for HIV-1 Incidence Estimates

Laboratory tests that can distinguish recent from long-term HIV infection are used to estimate HIV incidence in a population, but can potentially misclassify a proportion of long-term HIV infections as recent. Correct application of an assay requires determination of the proportion false recents (PFRs) as part of the assay characterization and for calculating HIV incidence in a local population using a HIV incidence assay. From April 2009 to December 2010, blood specimens were collected from HIV-infected individuals attending nine outpatient clinics (OPCs) in Vietnam (four from northern and five from southern Vietnam). Participants were living with HIV for ≥1 year and reported no antiretroviral (ARV) drug treatment. Basic demographic data and clinical information were collected. Specimens were tested with the BED capture enzyme immunoassay (BED-CEIA) and the Limiting-antigen (LAg)-Avidity EIA. PFR was estimated by dividing the number of specimens classified as recent by the total number of specimens; 95% confidence intervals (CI) were calculated. Specimens that tested recent had viral load testing performed. Among 1,813 specimens (north, n = 942 and south, n = 871), the LAg-Avidity EIA PFR was 1.7% (CI: 1.2-2.4) and differed by region [north 2.7% (CI: 1.8-3.9) versus south 0.7% (CI: 0.3-1.5); p = .002]. The BED-CEIA PFR was 2.3% (CI: 1.7-3.0) and varied by region [north 3.4% (CI: 2.4-4.7) versus south 1.0% (CI: 0.5-1.2), p < .001]. Excluding specimens with an undetectable VL, the LAg-Avidity EIA PFR was 1.2% (CI: 0.8-1.9) and the BED-CEIA PFR was 1.7% (CI: 1.2-2.4). The LAg-Avidity EIA PFR was lower than the BED-CEIA PFR. After excluding specimens with an undetectable VL, the PFR for both assays was similar. A low PFR should facilitate the implementation of the LAg-Avidity EIA for cross-sectional incidence estimates in Vietnam.

Pairwise diversity and tMRCA as potential markers for HIV infection recency

Intrahost human immunodeficiency virus (HIV)-1 diversity increases linearly over time. We assessed the extent to which mean pairwise distances and the time to the most recent common ancestor (tMRCA) inferred from intrahost HIV-1C env sequences were associated with the estimated time of HIV infection. Data from a primary HIV-1C infection study in Botswana were used for this analysis (N = 42). A total of 2540 HIV-1C env gp120 variable loop region 1 to conserved region 5 (V1C5) of the HIV-1 envelope gp120 viral sequences were generated by single genome amplification and sequencing, with an average of 61 viral sequences per participant and 11 sequences per time point per participant. Raw pairwise distances were calculated for each time point and participant using the ape package in R software. The tMRCA was estimated using phylogenetic inference implemented in Bayesian Evolutionary Analysis by Sampling Trees v1.8.2. Pairwise distances and tMRCA were significantly associated with the estimated time since HIV infection (both P < 0.001). Taking into account multiplicity of HIV infection strengthened these associations. HIV-1C env-based pairwise distances and tMRCA can be used as potential markers for HIV recency. However, the tMRCA estimates demonstrated no advantage over the pairwise distances estimates.

Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model

Background

Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence.

Methods

We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD), with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI) in the U.S. population and incidence of heart disease in the Canadian population.

Results

Model-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence.

Conclusion

It is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.

The Incidence Patterns Model to Estimate the Distribution of New HIV Infections in Sub-Saharan Africa: Development and Validation of a Mathematical Model

BACKGROUND

Programmatic planning in HIV requires estimates of the distribution of new HIV infections according to identifiable characteristics of individuals. In sub-Saharan Africa, robust routine data sources and historical epidemiological observations are available to inform and validate such estimates.

METHODS AND FINDINGS

We developed a predictive model, the Incidence Patterns Model (IPM), representing populations according to factors that have been demonstrated to be strongly associated with HIV acquisition risk: gender, marital/sexual activity status, geographic location, "key populations" based on risk behaviours (sex work, injecting drug use, and male-to-male sex), HIV and ART status within married or cohabiting unions, and circumcision status. The IPM estimates the distribution of new infections acquired by group based on these factors within a Bayesian framework accounting for regional prior information on demographic and epidemiological characteristics from trials or observational studies. We validated and trained the model against direct observations of HIV incidence by group in seven rounds of cohort data from four studies ("sites") conducted in Manicaland, Zimbabwe; Rakai, Uganda; Karonga, Malawi; and Kisesa, Tanzania. The IPM performed well, with the projections' credible intervals for the proportion of new infections per group overlapping the data's confidence intervals for all groups in all rounds of data. In terms of geographical distribution, the projections' credible intervals overlapped the confidence intervals for four out of seven rounds, which were used as proxies for administrative divisions in a country. We assessed model performance after internal training (within one site) and external training (between sites) by comparing mean posterior log-likelihoods and used the best model to estimate the distribution of HIV incidence in six countries (Gabon, Kenya, Malawi, Rwanda, Swaziland, and Zambia) in the region. We subsequently inferred the potential contribution of each group to transmission using a simple model that builds on the results from the IPM and makes further assumptions about sexual mixing patterns and transmission rates. In all countries except Swaziland, individuals in unions were the single group contributing to the largest proportion of new infections acquired (39%-77%), followed by never married women and men. Female sex workers accounted for a large proportion of new infections (5%-16%) compared to their population size. Individuals in unions were also the single largest contributor to the proportion of infections transmitted (35%-62%), followed by key populations and previously married men and women. Swaziland exhibited different incidence patterns, with never married men and women accounting for over 65% of new infections acquired and also contributing to a large proportion of infections transmitted (up to 56%). Between- and within-country variations indicated different incidence patterns in specific settings.

CONCLUSIONS

It is possible to reliably predict the distribution of new HIV infections acquired using data routinely available in many countries in the sub-Saharan African region with a single relatively simple mathematical model. This tool would complement more specific analyses to guide resource allocation, data collection, and programme planning.

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana

BACKGROUND

Cross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by reducing the likelihood of a false-recent result.

METHODS

The data comes from 854 time-points and 42 participants enrolled in a primary HIV-1C infection study in Botswana. Time points after treatment initiation or with evidence of multiplicity of infection were excluded from the final analysis. PwD was calculated from quasispecies generated using single genome amplification and sequencing. We evaluated the ability of PwD to correctly classify HIV infection recency within <130, <180 and <360 days post-seroconversion using Receiver Operator Characteristics (ROC) methods. Following a secondary PwD screening, we quantified the reduction in the relative false-recency rate (rFRR) of the BED and LAg assays while maintaining a sensitivity of either 75, 80, 85 or 90%.

RESULTS

The final analytic sample consisted of 758 time-points from 40 participants. The PwD assay was more accurate in classifying infection recency for the 130 and 180-day cut-offs when compared with the recommended LAg and BED thresholds. A higher AUC statistic confirmed the superior predictive performance of the PwD assay for the three cut-offs. When used for combination screening, the PwD assay reduced the rFRR of the LAg assay by 52% and the BED assay by 57.8% while maintaining a 90% sensitivity for the 130 and 180-day cut-offs respectively.

CONCLUSION

PwD can accurately determine HIV infection recency. A secondary PwD screening reduces misclassification and increases the accuracy of serologic-based assays.

Rural-urban comparisons of dengue seroprevalence in Malaysia

Background

Each year an estimated 390 million dengue infections occur worldwide. In Malaysia, dengue is a growing public health concern but estimate of its disease burden remains uncertain. We compared the urban-rural difference of dengue seroprevalence and determined age-specific dengue seroprevalence in Malaysia.

Methods

We undertook analysis on 11,821 subjects from six seroprevalence surveys conducted in Malaysia between 2001 and 2013, which composed of five urban and two rural series.

Results

Prevalence of dengue increased with age in both urban and rural locations in Malaysia, which exceeded 90 % among those aged 70 years or beyond. The age-specific rates of the 5 urban surveys overlapped without clear separation among them, while prevalence was lower in younger subjects in rural series than in urban series, the trend reversed in older subjects. There were no differences in the seroprevalence by gender, ethnicity or region. Poisson regression model confirmed the prevalence have not changed in urban areas since 2001 but in rural areas, there was a significant positive time trend such that by year 2008, rural prevalence was as high as in urban areas.

Conclusion

Dengue seroprevalence has stabilized but persisted at a high level in urban areas since 2001, and is fast stabilizing in rural areas at the same high urban levels by 2008. The cumulative seroprevalence of dengue exceeds 90 % by the age of 70 years, which translates into 16.5 million people or 55 % of the total population in Malaysia, being infected by dengue by 2013.

Identifying Recent HIV Infections: From Serological Assays to Genomics

In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.

Recalibration of the limiting antigen avidity EIA to determine mean duration of recent infection in divergent HIV-1 subtypes

Background

Mean duration of recent infection (MDRI) and misclassification of long-term HIV-1 infections, as proportion false recent (PFR), are critical parameters for laboratory-based assays for estimating HIV-1 incidence. Recent review of the data by us and others indicated that MDRI of LAg-Avidity EIA estimated previously required recalibration. We present here results of recalibration efforts using >250 seroconversion panels and multiple statistical methods to ensure accuracy and consensus.

Methods

A total of 2737 longitudinal specimens collected from 259 seroconverting individuals infected with diverse HIV-1 subtypes were tested with the LAg-Avidity EIA as previously described. Data were analyzed for determination of MDRI at ODn cutoffs of 1.0 to 2.0 using 7 statistical approaches and sub-analyzed by HIV-1 subtypes. In addition, 3740 specimens from individuals with infection >1 year, including 488 from patients with AIDS, were tested for PFR at varying cutoffs.

Results

Using different statistical methods, MDRI values ranged from 88–94 days at cutoff ODn = 1.0 to 177–183 days at ODn = 2.0. The MDRI values were similar by different methods suggesting coherence of different approaches. Testing for misclassification among long-term infections indicated that overall PFRs were 0.6% to 2.5% at increasing cutoffs of 1.0 to 2.0, respectively. Balancing the need for a longer MDRI and smaller PFR (<2.0%) suggests that a cutoff ODn = 1.5, corresponding to an MDRI of 130 days should be used for cross-sectional application. The MDRI varied among subtypes from 109 days (subtype A&D) to 152 days (subtype C).

Conclusions

Based on the new data and revised analysis, we recommend an ODn cutoff = 1.5 to classify recent and long-term infections, corresponding to an MDRI of 130 days (118–142). Determination of revised parameters for estimation of HIV-1 incidence should facilitate application of the LAg-Avidity EIA for worldwide use.

Epidemiology of HIV in Latin America and the Caribbean

PURPOSE OF REVIEW

The aim of the present review is to update HIV/AIDS Epidemiology in Latin America and the Caribbean highlighting the concentrated aspect of epidemic in the region.

RECENT FINDINGS

Among general population, HIV prevalence in Latin America is at stable levels (0.2-0.7%). The Caribbean still has one of the highest HIV prevalence rates in the world (<0.1-3%), but incidences have declined around 49%. This is not the current situation for high-risk key populations; most incident cases occur among MSM. Available data on transgender women suggest that they are the most-at-risk group. Female sex workers still have a 12-fold the chance of being HIV positive compared with other women. IDU prevalence was revised to 0.45%, but non-IDU has been suggested as a mediator between sexual risk and HIV.

SUMMARY

The increase in treatment coverage (mean is at 63%) resulted in modifications of HIV/AIDS epidemiology. New strategies to seek, test and link key populations to care are urgently needed and targeted interventions to prevent HIV expansion among them must be adopted. These strategies should consider the particular situation regarding social inequalities, discrimination and violence that pervade the HIV epidemic among key populations.

Improved testing of recent HIV-1 infections with the BioRad avidity assay compared to the limiting antigen avidity assay and BED Capture enzyme immunoassay: evaluation using reference sample panels from the German Seroconverter Cohort

Background

The variety and limitations of current laboratory methods for estimating HIV-incidence has driven attempts to improve and standardize the performance of serological ‘Tests for Recent HIV-Infections’ (TRI). Primary and follow-up HIV-1 positive plasma samples from individuals with well-defined dates of infection collected as part of the German Seroconverter Cohort provided specimens highly suitable for use in comparing the performance of three TRIs: the AWARE™ BED™ EIA HIV-1 Incidence test (BED-CEIA), Genetic systems HIV-1/HIV-2 Plus O EIA antibody avidity-based assay (BioRad Avidity) and Sedia™ HIV-1 LAg Avidity EIA (LAg Avidity).

Methods

The evaluation panel included 180 specimens: 44 from antiretroviral (ARV)-naïve individuals with recently acquired HIV-infection (≤130 days; 25 B and 19 non-B subtypes) and 136 from long-term (>12 months) infected individuals [101 ARV-naïve subtype B, 16 non-B subtypes, 14 ARV-treated individuals, 5 slow progressors (SLP)].

Results

For long-term infected, ARV-naïve individuals the false recent rates (FRR) of both the BioRad and LAg Avidity assays were 2% (2/101 for subtype B) and 6% (1/16 for subtype ‘non-B’), while the FRR of the BED-CEIA was 7% (7/101 for subtype B) and 25% (4/16 for subtype ‘non-B’) (all p>0.05). Misclassification of ARV-treated individuals and SLP was rare by LAg (1/14, 0/5) and BioRad Avidity assays (2/14, 1/5) but more frequent by BED-CEIA (5/14, 3/5). Among recently-infected individuals (subtype B), 60% (15/25) were correctly classified by BED-CEIA, 88% (22/25) by BioRad Avidity and significantly fewer by LAg (48%, 12/25) compared to BioRad Avidity (p = 0.005) with a higher true-recency rate among non-B infections for all assays.

Conclusions

This study using well-characterized specimens demonstrated lower FRRs for both avidity methods than with the BED-CEIA. For recently infected individuals the BioRad Avidity assay was shown to give the most accurate results.

Short Communication: Defining optimality of a test for recent infection for HIV incidence surveillance

The estimation of HIV incidence from cross-sectional surveys using tests for recent infection has attracted much interest. It is increasingly recognized that the lack of high performance recent infection tests is hindering the implementation of this surveillance approach. With growing funding opportunities, test developers are currently trying to fill this gap. However, there is a lack of consensus and clear guidance for developers on the evaluation and optimization of candidate tests. A fundamental shift from conventional thinking about test performance is needed: away from metrics relevant in typical public health settings where the detection of a condition in individuals is of primary interest (sensitivity, specificity, and predictive values) and toward metrics that are appropriate when estimating a population-level parameter such as incidence (accuracy and precision). The inappropriate use of individual-level diagnostics performance measures could lead to spurious assessments and suboptimal designs of tests for incidence estimation. In some contexts, such as population-level application to HIV incidence, bias of estimates is essentially negligible, and all that remains is the maximization of precision. The maximization of the precision of incidence estimates provides a completely general criterion for test developers to assess and optimize test designs. Summarizing the test dynamics into the properties relevant for incidence estimation, high precision estimates are obtained when (1) the mean duration of recent infection is large, and (2) the false-recent rate is small. The optimal trade-off between these two test properties will produce the highest precision, and therefore the most epidemiologically useful incidence estimates.

Evaluation of the false recent classification rates of multiassay algorithms in estimating HIV type 1 subtype C incidence

Laboratory cross-sectional assays are useful for the estimation of HIV incidence, but are known to misclassify individuals with long-standing infection as recently infected. The false recent rate (FRR) varies widely across geographic areas; therefore, accurate estimates of HIV incidence require a locally defined FRR. We determined FRR for Botswana, where HIV-1 subtype C infection is predominant, using the BED capture enzyme immunoassay (BED), a Bio-Rad Avidity Index (BAI) assay (a modification of the Bio-Rad HIV1/2+O EIA), and two multiassay algorithms (MAA) that included clinical data. To estimate FRR, stored blood samples from 512 antiretroviral (ARV)-naive HIV-1 subtype C-infected individuals from a prospective cohort in Botswana were tested at 18-24 months postenrollment. The following FRR mean (95% CI) values were obtained: BED 6.05% (4.15-8.48), BAI 5.57% (3.70-8.0), BED-BAI 2.25% (1.13-4.0), and a combination of BED-BAI with CD4 (>200) and viral load (>400) threshold 1.43% (0.58-2.93). The interassay agreement between BED and BAI was 92.8% (95% CI, 90.1-94.5) for recent/long-term classification. Misclassification was associated with viral suppression for BED [adjusted OR (aOR) 10.31; p=0.008], BAI [aOR 9.72; p=0.019], and MAA1 [aOR 16.6; p=0.006]. Employing MAA can reduce FRR to <2%. A local FRR can improve cross-sectional HIV incidence estimates.

Modelling HIV incidence and survival from age-specific seroprevalence after antiretroviral treatment scale-up in rural South Africa

OBJECTIVE

Our study uses sex-specific and age-specific HIV prevalence data from an ongoing population-based demographic and HIV survey to infer HIV incidence and survival in rural KwaZulu-Natal between 2003 and 2011, a period when antiretroviral treatment (ART) was rolled out on a large scale.

DESIGN

Catalytic mathematical model for estimating HIV incidence and differential survival in HIV-infected persons on multiple rounds of HIV seroprevalence.

METHODS

We evaluate trends of HIV incidence and survival by estimating parameters separately for women and men aged 15-49 years during three calendar periods (2003-2005, 2006-2008, 2009-2011) reflecting increasing ART coverage. We compare model-based estimates of HIV incidence with observed cohort-based estimates from the longitudinal HIV surveillance.

RESULTS

Median survival after HIV infection increased significantly between 2003-2005 and 2009-2011 from 10.0 [95% confidence interval (CI) 8.8-11.2] to 14.2 (95% CI 12.6-15.8) years in women (P < 0.001) and from 10.0 (95% CI 9.2-10.8) to 14.0 (95% CI 10.6-17.4) years in men (P = 0.02). Our model suggests no statistically significant reduction of HIV incidence in the age-group 15-49 years in 2009-2011 compared with 2003-2005. Age-specific and sex-specific model-based HIV incidence estimates were in good agreement with observed cohort-based estimates from the ongoing HIV surveillance.

CONCLUSION

Our catalytic modelling approach using cross-sectional age-specific HIV prevalence data could be useful to monitor trends of HIV incidence and survival in other African settings with a high ART coverage.

Towards estimation of HIV-1 date of infection: a time-continuous IgG-model shows that seroconversion does not occur at the midpoint between negative and positive tests

Estimating date of infection for HIV-1-infected patients is vital for disease tracking and informed public health decisions, but is difficult to obtain because most patients have an established infection of unknown duration at diagnosis. Previous studies have used HIV-1-specific immunoglobulin G (IgG) levels as measured by the IgG capture BED enzyme immunoassay (BED assay) to indicate if a patient was infected recently, but a time-continuous model has not been available. Therefore, we developed a logistic model of IgG production over time. We used previously published metadata from 792 patients for whom the HIV-1-specific IgG levels had been longitudinally measured using the BED assay. To account for patient variability, we used mixed effects modeling to estimate general population parameters. The typical patient IgG production rate was estimated at r = 6.72[approximate 95% CI 6.17,7.33]×10⁻³ OD-n units day⁻¹, and the carrying capacity at K = 1.84[1.75,1.95] OD-n units, predicting how recently patients seroconverted in the interval ^∧t = (31,711) days. Final model selection and validation was performed on new BED data from a population of 819 Swedish HIV-1 patients diagnosed in 2002–2010. On an appropriate subset of 350 patients, the best model parameterization had an accuracy of 94% finding a realistic seroconversion date. We found that seroconversion on average is at the midpoint between last negative and first positive HIV-1 test for patients diagnosed in prospective/cohort studies such as those included in the training dataset. In contrast, seroconversion is strongly skewed towards the first positive sample for patients identified by regular public health diagnostic testing as illustrated in the validation dataset. Our model opens the door to more accurate estimates of date of infection for HIV-1 patients, which may facilitate a better understanding of HIV-1 epidemiology on a population level and individualized prevention, such as guidance during contact tracing.

Trends in HIV prevalence among young people in generalised epidemics: implications for monitoring the HIV epidemic

Background

Countries measure trends in HIV incidence to assess the impact of HIV prevention and treatment programmes. Most countries have approximated trends in HIV incidence through modelled estimates or through trends in HIV prevalence among young people (aged 15–24 years) assuming they have recently become sexually active and have thus only been recently exposed to HIV.

Methods

Trends in HIV incidence are described and results are compared using three proxy measures of incidence: HIV prevalence among young women attending antenatal clinics (ANCs) in 22 countries; HIV prevalence among young male and female nationally representative household survey respondents in 14 countries; and modelled estimates of adult (ages 15–49 years) HIV incidence in 26 countries. The significance of changes in prevalence among ANC attendees and young survey respondents is tested.

Results

Among 26 countries, 25 had evidence of some decline in HIV incidence and 15 showed statistically significant declines in either ANC data or survey data. Only in Mozambique did the direction of the trend in young ANC attendees differ from modelled adult incidence, and in Mali and Zambia trends among young men differed from trends in adult incidence. The magnitude of change differed by method.

Conclusions

Trends in HIV prevalence among young people show encouraging declines. Changes in fertility patterns, HIV-infected children surviving to adulthood, and participation bias could affect future proxy measures of incidence trends.

The physiology of sexual violence, genito-anal injury and HIV: opportunities for improving risk estimation

Increased understanding about the relative contribution of genito-anal injury to HIV transmission may improve epidemic model estimates of the distribution of risk among and across different subpopulations. Better understanding about the distribution of HIV among subpopulations that are at highest risk of sexual violence can also improve the design and prioritization of combination prevention interventions that are most likely to reduce the risk of sexual violence and its potential contribution to HIV transmission. The effective incorporation of physiological and social variables into epidemic modelling will likely require new research approaches that can help communicate the level of risk associated with different types of 'heterosexual' transmission. Reference models that reflect the potential impact of sexual violence and genital injury can help direct attention toward key variables and uncertainties. For further research that clarifies these relationships will require multidisciplinary collaboration among groups with expertise in epidemiology, social science, public health, and clinical and basic science.

A general HIV incidence inference scheme based on likelihood of individual level data and a population renewal equation

We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.

Is back-projection methodology still relevant for estimating HIV incidence from national surveillance data?

Accurate estimates of HIV incidence are crucial to understand the extent of transmission of the infection, evaluate intervention strategies and effectively plan new public health control measures. HIV/AIDS surveillance systems in numerous industrialised countries record the number of known new HIV and/or AIDS diagnoses, which are often used as a surrogate marker for HIV incidence. HIV/AIDS diagnosis data have been used to reconstruct historical HIV incidence trends using modified back-projection methods. Estimates of HIV incidence are most robust when reliable data on the number of incident infections, a subset of all diagnoses, is widely available, and surveillance systems should prioritise the collection of these data. Back-projection alone provides reliable estimates of HIV incidence in the past, but is not useful when estimating current or future HIV incidence. However, back-projection methodology should be used in conjunction with other corroborative methods to estimate current HIV incidence, and methods to combine the various techniques should be investigated.

A new general biomarker-based incidence estimator

BACKGROUND

Estimating disease incidence from cross-sectional surveys, using biomarkers for "recent" infection, has attracted much interest. Despite widespread applications to HIV, there is currently no consensus on the correct handling of biomarker results classifying persons as "recently" infected long after the infections occurred.

METHODS

We derive a general expression for a weighted average of recent incidence that-unlike previous estimators-requires no particular assumption about recent infection biomarker dynamics or about the demographic and epidemiologic context. This is possible through the introduction of an explicit timescale T that truncates the period of averaging implied by the estimator.

RESULTS

The recent infection test dynamics can be summarized into 2 parameters, similar to those appearing in previous estimators: a mean duration of recent infection and a false-recent rate. We identify a number of dimensionless parameters that capture the bias that arises from working with tractable forms of the resulting estimator and elucidate the utility of the incidence estimator in terms of the performance of the recency test and the population state. Estimation of test characteristics and incidence is demonstrated using simulated data. The observed confidence interval coverage of the test characteristics and incidence is within 1% of intended coverage.

CONCLUSIONS

Biomarker-based incidence estimation can be consistently adapted to a general context without the strong assumptions of previous work about biomarker dynamics and epidemiologic and demographic history.

A literature review of reporting standards of HIV progression models

OBJECTIVE

We conducted a systematic review of HIV progression models to identify the mathematical structures used, the main research questions and key model aspects in terms of quality and robustness.

METHODS

We searched for articles published before February 2009 that described models of HIV progression in humans. We included two strategies of search with and without MeSH terms. We classified the models by their mathematical structure and research question. We created a checklist of desirable features of the models, reviewed and classified the articles to inform our conclusions.

RESULTS

Among 3491 articles found, 93 met the inclusion criteria. Among the selected articles, 60 used transition models, 25 applied differential equations, and eight had other structures. We did not find a relation between the type of question explored and the modeling method used. None of the studies complied with the complete set of items in the checklist, but 6.5% cover at least 90% of them.

CONCLUSION

There is an enormous heterogeneity of HIV modeling exercises in terms of methods used and topics addressed, as well as in the presentation of key aspects of the articles in terms of quality and robustness.

Workshop summary: Novel biomarkers for HIV incidence assay development

Reliable methods for measuring human immunodeficiency virus (HIV) incidence are a high priority for HIV prevention. They are particularly important to assess the population-level effectiveness of new prevention strategies, to evaluate the community-wide impact of ongoing prevention programs, and to assess whether a proposed prevention trial can be performed in a timely and cost-efficient manner in a particular population and setting. New incidence assays and algorithms that are accurate, rapid, cost-efficient, and can be performed on easily-obtained specimens are urgently needed. On May 4, 2011, the Division of AIDS (DAIDS), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), sponsored a 1-day workshop to examine strategies for developing new assays to distinguish recent from chronic HIV infections. Participants included leading investigators, clinicians, public health experts, industry, regulatory specialists, and other stakeholders. Immune-based parameters, markers of viral sequence diversity, and other biomarkers such as telomere length were evaluated. Emerging nanotechnology and chip-based diagnostics, including algorithms for performing diverse assays on a single platform, were also reviewed. This report summarizes the presentations, panel discussions, and the consensus reached for pursuing the development of a new generation of HIV incidence assays.

More and better information to tackle HIV epidemics: towards improved HIV incidence assays

Timothy Hallett and colleagues from the Incidence Assay Critical Path Working Group argue that a quick, easy, valid, and precise method of estimating HIV incidence in populations is needed, and discuss several new technologies to address this need.