Integration of a recent infection testing algorithm into HIV surveillance in Ireland: improving HIV knowledge to target prevention

Demographic Characteristics and Hot-Spot Areas of Recent Infections Among New HIV Diagnoses in Sichuan, China, Between 2018 and 2020

Background

Sichuan Province is severely affected by the HIV epidemic in China. Little is known about the characteristics of recent infections among new HIV diagnoses, which is critical to prevention strategies, evaluation of the HIV epidemic and health resource allocation. Meanwhile, individuals at primary stages of infection are related to the hot-spot areas of ongoing transmission in new HIV diagnoses, which is also rarely known.

Objective

This article aimed to report the proportion of recent infections among new HIV diagnoses, and to reveal demographic characteristics associated with HIV recent infections, and finally, to indicate the hot-spot areas of ongoing transmission in Sichuan province between 2018 and 2020.

Methods

Limiting Antigen (LAg)-Avidity assay was performed to detect recent infection within new HIV diagnoses reported in odd months between 2018 and 2020. Results were reclassified according to the data on CD4 cell count, antiretroviral treatment and the existence of an AIDS-defining illness. Logistic regression was used to determine characteristics associated with HIV recent infections. The spatial analysis was conducted with ArcGIS 10.7 to figure hot-spot areas of HIV recent infections.

Results

42,089 newly diagnosed HIV-1 cases were tested using the LAg-Avidity EIA. In total, 5848 (13.89%) of those were classified as HIV recent infections. Female, age between 18-25 years and men who had sex with men were related to higher proportion of HIV recent infections. Logistic regression revealed that MSM aged between 18-25 years were more likely to be classified as recent infection. Spatial analysis demonstrated significant clustering in Chengdu, Yibin, Luzhou city between 2018 and 2020. Hot spots were mainly clustered in the center of Sichuan in 2018, but gradually spread to southwest and northwest between 2019 and 2020.

Conclusion

Enhanced preventive measures among relevant risk groups and areas where the potential HIV-1 transmission is ongoing is urgently needed to curb further spread.

Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis

Background

Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data.

Methods

It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data.

Results

We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result.

Conclusion

Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other.

Use of HIV Recency Assays for HIV Incidence Estimation and Other Surveillance Use Cases: Systematic Review

BACKGROUND

HIV assays designed to detect recent infection, also known as "recency assays," are often used to estimate HIV incidence in a specific country, region, or subpopulation, alone or as part of recent infection testing algorithms (RITAs). Recently, many countries and organizations have become interested in using recency assays within case surveillance systems and routine HIV testing services to measure other indicators beyond incidence, generally referred to as "non-incidence surveillance use cases."

OBJECTIVE

This review aims to identify published evidence that can be used to validate methodological approaches to recency-based incidence estimation and non-incidence use cases. The evidence identified through this review will be used in the forthcoming technical guidance by the World Health Organization (WHO) and United Nations Programme on HIV/AIDS (UNAIDS) on the use of HIV recency assays for identification of epidemic trends, whether for HIV incidence estimation or non-incidence indicators of recency.

METHODS

To identify the best methodological and field implementation practices for the use of recency assays to estimate HIV incidence and trends in recent infections for specific populations or geographic areas, we conducted a systematic review of the literature to (1) understand the use of recency testing for surveillance in programmatic and laboratory settings, (2) review methodologies for implementing recency testing for both incidence estimation and non-incidence use cases, and (3) assess the field performance characteristics of commercially available recency assays.

RESULTS

Among the 167 documents included in the final review, 91 (54.5%) focused on assay or algorithm performance or methodological descriptions, with high-quality evidence of accurate age- and sex-disaggregated HIV incidence estimation at national or regional levels in general population settings, but not at finer geographic levels for prevention prioritization. The remaining 76 (45.5%) described the field use of incidence assays including field-derived incidence (n=45), non-incidence (n=25), and both incidence and non-incidence use cases (n=6). The field use of incidence assays included integrating RITAs into routine surveillance and assisting with molecular genetic analyses, but evidence was generally weaker or only reported on what was done, without validation data or findings related to effectiveness of using non-incidence indicators calculated through the use of recency assays as a proxy for HIV incidence.

CONCLUSIONS

HIV recency assays have been widely validated for estimating HIV incidence in age- and sex-specific populations at national and subnational regional levels; however, there is a lack of evidence validating the accuracy and effectiveness of using recency assays to identify epidemic trends in non-incidence surveillance use cases. More research is needed to validate the use of recency assays within HIV testing services, to ensure findings can be accurately interpreted to guide prioritization of public health programming.

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.

Monitoring Recently Acquired HIV Infections in Amsterdam, The Netherlands: The Attribution of Test Locations

Background: Surveillance of recent HIV infections (RHI) using an avidity assay has been implemented at Dutch sexual health centres (SHC) since 2014, but data on RHI diagnosed at other test locations is lacking.

Setting: Implementation of the avidity assay in HIV treatment clinics for the purpose of studying RHI among HIV patients tested at different test locations.

Methods: We retrospectively tested leftover specimens from newly diagnosed HIV patients in care in 2013–2015 in Amsterdam. Avidity Index (AI) values ≤0.80 indicated recent infection (acquired ≤6 months prior to diagnosis), and AI > 0.80 indicated established infection (acquired >6 months prior to diagnosis). An algorithm for RHI was applied to correct for false recency. Recency based on this algorithm was compared with recency based on epidemiological data only. Multivariable logistic regression analysis was used to identify factors associated with RHI among men who have sex with men (MSM).

Results: We tested 447 specimens with avidity; 72% from MSM. Proportions of RHI were 20% among MSM and 10% among heterosexuals. SHC showed highest proportions of RHI (27%), followed by GPs (15%), hospitals (5%), and other/unknown locations (11%) (p < 0.001). Test location was the only factor associated with RHI among MSM. A higher proportion of RHI was found based on epidemiological data compared to avidity testing combined with the RHI algorithm.

Conclusion: SHC identify more RHI infections compared to other test locations, as they serve high-risk populations and offer frequent HIV testing. Using avidity-testing for surveillance purposes may help targeting prevention programs, but the assay lacks robustness and its added value may decline with improved, repeat HIV testing and data collection.

Identifying major drivers of incident HIV infection using recent infection testing algorithms (RITAs) to precisely inform targeted prevention

BACKGROUND

Recent infection testing algorithms (RITAs) incorporating clinical information with the HIV recency assay have been proven to accurately classify recent infection. However, little evidence exists on whether RITAs would help in precisely identifying major drivers of the ongoing HIV epidemic.

METHODS

HIV recency test results and clinical information were collected from 1152 newly diagnosed HIV cases between 2015 and 2017 in Dehong prefecture of Yunnan province, and the efficacy of four different RITAs in identifying risk factors for new HIV infection was compared.

RESULTS

RITA 1 uses the recency test only. RITA 2 and RITA 3 combine the recency test with CD4+ T cell count and viral load (VL), respectively. RITA 4 combines both CD4+ T cell count and VL. All RITAs identified the MSM group and young people between 15 and 24 years as risk factors for incident HIV infection. RITA 3 and RITA 4 further identified the Dai ethnic minority as a risk factor, which had not been identified before when only the HIV recency test was used.

CONCLUSIONS

By comparing different RITAs, we determined that greater accuracy in classifying recent HIV infection could help elucidate major drivers impacting the ongoing epidemic and thus inform targeted interventions.