Estimating HIV incidence using dates of both HIV and AIDS diagnoses

A new method for estimating HIV incidence from a single cross-sectional survey

Estimating incidence from cross-sectional data sources is both important to the understanding of the HIV epidemic and challenging from a methodological standpoint. We develop a new incidence estimator that measures the size of the undiagnosed population and the amount of time spent undiagnosed in order to infer incidence and transmission rates. The estimator is calculated using commonly collected information on testing history and HIV status and, thus, can be deployed in many HIV surveys without additional cost. If ART biomarker status and/or viral load information is available, the estimator can be adjusted for biases in self-reported testing history. The performance of the estimator is explored in two large surveys in Kenya, where we find our point estimates to be consistent with assay-derived estimates, with much smaller standard errors.

Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data

Background

The Guangxi Zhuang Autonomous Region bears a relatively high burden of HIV/AIDS infection. The number of accumulatively reported HIV/AIDS cases in Guangxi is the third highest among 31 provinces or Autonomous Region from 2004 to 2007, changed to the second highest between 2011 and 2013, then returned to the third highest again after 2014. We aim to estimate the new infections and evaluate the real-time HIV epidemic in Guangxi, China, in order to reveal the rule of HIV transmission.

Methods

Firstly, the number of annually reported HIV and AIDS cases, as well as the number of cases linked with CD4 data are extracted from the HIV/AIDS information system in China. Secondly, two CD4-staged models are formulated by linking the with-host information on CD4 level to between-host transmission and surveillance data. Thirdly, new HIV infections, diagnosis rates and undiagnosed infections over time are estimated by using Bayesian method and Maximum Likelihood Estimation method.

Results

The data reveal that the newly reported cases have been decreasing since 2011, while lots of cases are identified at late CD4 stage. The data fitted results indicate that both models can describe the trend of the epidemic well. The estimation results show that the new and undiagnosed infections began to decrease from the period2006 - 2008. However, the diagnosis probabilities/rates keep at a very low level, and there are still a large number of infections undiagnosed, most of which have a large probability to be identified at late CD4 stage.

Conclusions

Our findings suggest that HIV/AIDS epidemic in Guangxi has been controlled to a certain extent, while the diagnosis rate still needs to be improved. More attentions should be paid to identify infections at their early CD4 stages. Meanwhile, comprehensive intervention measures should be continually strengthened in avoid of the rebound of new infections.

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.

Estimating the incidence and diagnosed proportion of HIV infections in Japan: a statistical modeling study

Background

Epidemiological surveillance of HIV infection in Japan involves two technical problems for directly applying a classical backcalculation method, i.e., (i) all AIDS cases are not counted over time and (ii) people diagnosed with HIV have received antiretroviral therapy, extending the incubation period. The present study aimed to address these issues and estimate the HIV incidence and the proportion of diagnosed HIV infections, using a simple statistical model.

Methods

From among Japanese nationals, yearly incidence data of HIV diagnoses and patients with AIDS who had not previously been diagnosed as HIV positive, from 1985 to 2017, were analyzed. Using the McKendrick partial differential equation, general convolution-like equations were derived, allowing estimation of the HIV incidence and the time-dependent rate of diagnosis. A likelihood-based approach was used to obtain parameter estimates.

Results

Assuming that the median incubation period was 10.0 years, the cumulative number of HIV infections was estimated to be 29,613 (95% confidence interval (CI): 29,059, 30,167) by the end of 2017, and the proportion of diagnosed HIV infections was estimated at 80.3% (95% CI [78.7%–82.0%]). Allowing the median incubation period to range from 7.5 to 12.3 years, the estimate of the proportion diagnosed can vary from 77% to 84%.

Discussion

The proportion of diagnosed HIV infections appears to have not yet reached 90% among Japanese nationals. Compared with the peak incidence from 2005–2008, new HIV infections have clearly been in a declining trend; however, there are still more than 1,000 new HIV infections per year in Japan. To increase the diagnosed proportion of HIV infections, it is critical to identify people who have difficulty accessing consultation, testing, and care, and to explore heterogeneous patterns of infection.

A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates

Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA.

How can we better identify early HIV infections?

PURPOSE OF REVIEW

Detection of early HIV infections (EHIs), including acute HIV infection (AHI), is important for individual health, prevention of HIV transmission, and measurement of HIV incidence. We describe markers of EHI, diagnostic strategies for detecting these markers, and ways to incorporate these strategies into diagnostic and HIV incidence algorithms.

RECENT FINDINGS

For individual diagnosis in the USA and Europe, laboratory-based diagnostic algorithms increasingly incorporate fourth-generation HIV antigen tests, allowing for earlier detection. In some sub-Saharan African settings, symptom-based screening is being explored to identify subsets of persons at high risk for AHI. Point-of-care diagnostics designed for AHI detection are in the pipeline and, if validated, represent an opportunity for real-time AHI diagnosis. At the population level, multiassay algorithms are promising new strategies for estimating HIV incidence on the basis of several assays applied to cross-sectional samples. These algorithms can be developed to optimize performance, in addition to cost and logistical considerations.

SUMMARY

There are important recent advances in detection of EHIs at the individual and population levels. Applying optimal combinations of tests in diagnostic and HIV incidence algorithms is urgently needed to support the multiple goals derived from enhanced detection and discrimination of EHIs.

Inferring HIV incidence from case surveillance with CD4+ cell counts

BACKGROUND

In some countries, HIV surveillance is based on case-reporting of newly diagnosed infections. We present a new back-projection method for estimating HIV-incidence trends using individuals' CD4 cell counts at diagnosis.

METHODS

On the basis of a review of CD4 cell count distributions among HIV-uninfected people, CD4 cell count following primary infection, and rates of CD4 cell count decline over time among people with HIV, we simulate the expected distribution in time between infection and diagnosis. Applying this to all diagnosed individuals provides a distribution of likely infection times and estimates for population incidence, level of undiagnosed HIV, and the average time from infection to diagnosis each year. We applied this method to the national HIV case surveillance data of Australia for 1983-2013.

RESULTS

The estimated number of new HIV infections in Australia in 2013 was 912 (95% uncertainty bound 835-1002). We estimate that 2280 (95% uncertainty bound 1900-2830) people were living with undiagnosed HIV at the end of 2013, corresponding to approximately 9.4% (95% uncertainty bound 7.8-10.1%) of all people living with HIV. With increases in the average CD4 count at diagnosis, the inferred HIV testing rate has been increasing over time and the estimated mean and median times between infection and diagnosis have decreased substantially. However, the estimated mean time between infection and diagnosis is considerably greater than the median, indicating that some people remain undiagnosed for long periods. Differences were found between cases attributable to male homosexual exposure versus other cases.

CONCLUSION

This methodology provides a novel way of estimating population incidence by combining diagnosis dates and CD4 cell counts at diagnosis.

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.

Disproportionate impact of combination antiretroviral therapy on AIDS incidence in Australia: results from a modified back-projection model

The objective of the current study is to describe the impact of Combination antiretroviral therapy (cART) on trends in AIDS incidence over time for selected population groups in Australia, specifically, men who have sex with men (MSM) and injecting drug users (IDUs). A modified back-projection modeling technique was used to predict the number of AIDS diagnoses without cART based on Australia's HIV/AIDS surveillance system database. Modelled estimates indicate that since 1996, the effective cART has reduced overall AIDS cases by ~70 and ~10% among MSM and IDUs respectively. The predicted reduction in AIDS cases among IDUs aged less than 40 years was 36% while there was no reduction predicted for those aged 40 years or older. The impact of cART on AIDS diagnoses has been modest among IDUs. Late presentation, poor access to health services and barriers to uptake of cART may account for the divergence between these population groups.

HIV in hiding: methods and data requirements for the estimation of the number of people living with undiagnosed HIV

Many people who are HIV positive are unaware of their infection status. Estimation of the number of people with undiagnosed HIV within a country or region is vital for understanding future need for treatment and for motivating testing programs. We review the available estimation approaches which are in current use. They can be broadly classified into those based on prevalence surveys and those based on reported HIV and AIDS cases. Estimation based on prevalence data requires data from regular prevalence surveys in different population groups together with estimates of the size of these groups. The recommended minimal case reporting data needed to estimate the number of patients with undiagnosed HIV are HIV diagnoses, including CD4 count at diagnosis and whether there has been an AIDS diagnosis in the 3 months before or after HIV diagnosis, and data on deaths in people with HIV. We would encourage all countries to implement several methods that will help develop our understanding of strengths and weaknesses of the various methods.

Measuring the HIV/AIDS epidemic: approaches and challenges

In this article, the author reviews current approaches and methods for measuring the scope of the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) epidemic and their strengths and weaknesses. In recent years, various public health agencies have revised statistical estimates of the scope of the HIV/AIDS pandemic. The author considers the reasons underlying these revisions. New sources of data for estimating HIV prevalence have become available, such as nationally representative probability-based surveys. New technologies such as biomarkers that indicate when persons became infected are now used to determine HIV incidence rates. The author summarizes the main sources of errors and problems with these and other approaches and discusses opportunities for improving their reliability. Changing methods and data sources present new challenges, because incidence and prevalence estimates produced at different points in time are not directly comparable with each other, which complicates assessment of time trends. The methodological changes help explain the changes in global statistics. As methods and data sources continue to improve, the development of statistical tools for better assessing the extent to which changes in HIV/AIDS statistics can be attributed to changes in methodology versus real changes in the underlying epidemic is an important challenge.

Increasing HIV transmission through male homosexual and heterosexual contact in Australia: results from an extended back-projection approach

OBJECTIVES

The aim of the study was to reconstruct the HIV epidemic in Australia for selected populations categorized by exposure route; namely, transmission among men who have sex with men (MSM), transmission among injecting drug users (IDUs), and transmission among heterosexual men and women in Australia.

DESIGN

Statistical back-projection techniques were extended to reconstruct the historical HIV infection curve using surveillance data. Methods We developed and used a novel modified back-projection modelling technique that makes maximal use of all available surveillance data sources in Australia, namely, (1) newly diagnosed HIV infections, (2) newly acquired HIV infections and (3) AIDS diagnoses.

RESULTS

The analyses suggest a peak HIV incidence in Australian MSM of approximately 2000 new infections per year in the late 1980s, followed by a rapid decline to a low of <500 in the early 1990s. We estimate that, by 2007, cumulatively approximately 20 000 MSM were infected with HIV, of whom 13% were not diagnosed with HIV infection. Similarly, a total of approximately 1050 and approximately 2600 individuals were infected through sharing needles and heterosexual contact, respectively, and in 12% and 23% of these individuals, respectively, the infection remained undetected.

DISCUSSION

Male homosexual contact accounts for the majority of new HIV infections in Australia. However, the transmission route distribution of new HIV infections has changed over time. The number of HIV infections is increasing substantially among MSM, increasing moderately in those infected via heterosexual exposure, and decreasing in IDUs.

Characterizing trends in HIV infection among men who have sex with men in Australia by birth cohorts: results from a modified back-projection method

Background

We set out to estimate historical trends in HIV incidence in Australian men who have sex with men with respect to age at infection and birth cohort.

Methods

A modified back-projection technique is applied to data from the HIV/AIDS Surveillance System in Australia, including "newly diagnosed HIV infections", "newly acquired HIV infections" and "AIDS diagnoses", to estimate trends in HIV incidence over both calendar time and age at infection.

Results

Our results demonstrate that since 2000, there has been an increase in new HIV infections in Australian men who have sex with men across all age groups. The estimated mean age at infection increased from ~35 years in 2000 to ~37 years in 2007. When the epidemic peaked in the mid 1980s, the majority of the infections (56%) occurred among men aged 30 years and younger; 30% occurred in ages 31 to 40 years; and only ~14% of them were attributed to the group who were older than 40 years of age. In 2007, the proportion of infections occurring in persons 40 years or older doubled to 31% compared to the mid 1980s, while the proportion of infections attributed to the group younger than 30 years of age decreased to 36%.

Conclusion

The distribution of HIV incidence for birth cohorts by infection year suggests that the HIV epidemic continues to affect older homosexual men as much as, if not more than, younger men. The results are useful for evaluating the impact of the epidemic across successive birth cohorts and study trends among the age groups most at risk.

Estimation of HIV incidence in the United States

CONTEXT

Incidence of human immunodeficiency virus (HIV) in the United States has not been directly measured. New assays that differentiate recent vs long-standing HIV infections allow improved estimation of HIV incidence.

OBJECTIVE

To estimate HIV incidence in the United States.

DESIGN, SETTING, AND PATIENTS

Remnant diagnostic serum specimens from patients 13 years or older and newly diagnosed with HIV during 2006 in 22 states were tested with the BED HIV-1 capture enzyme immunoassay to classify infections as recent or long-standing. Information on HIV cases was reported to the Centers for Disease Control and Prevention through June 2007. Incidence of HIV in the 22 states during 2006 was estimated using a statistical approach with adjustment for testing frequency and extrapolated to the United States. Results were corroborated with back-calculation of HIV incidence for 1977-2006 based on HIV diagnoses from 40 states and AIDS incidence from 50 states and the District of Columbia.

MAIN OUTCOME MEASURE

Estimated HIV incidence.

RESULTS

An estimated 39,400 persons were diagnosed with HIV in 2006 in the 22 states. Of 6864 diagnostic specimens tested using the BED assay, 2133 (31%) were classified as recent infections. Based on extrapolations from these data, the estimated number of new infections for the United States in 2006 was 56,300 (95% confidence interval [CI], 48,200-64,500); the estimated incidence rate was 22.8 per 100,000 population (95% CI, 19.5-26.1). Forty-five percent of infections were among black individuals and 53% among men who have sex with men. The back-calculation (n = 1.230 million HIV/AIDS cases reported by the end of 2006) yielded an estimate of 55,400 (95% CI, 50,000-60,800) new infections per year for 2003-2006 and indicated that HIV incidence increased in the mid-1990s, then slightly declined after 1999 and has been stable thereafter.

CONCLUSIONS

This study provides the first direct estimates of HIV incidence in the United States using laboratory technologies previously implemented only in clinic-based settings. New HIV infections in the United States remain concentrated among men who have sex with men and among black individuals.

The status of national HIV case surveillance, United States 2006

Since the height of HIV incidence in the mid-1980s, advances in treatment have delayed progression of HIV infection. As a result, surveillance of AIDS cases alone is no longer sufficient to monitor the current status of the HIV epidemic. At the national level, new HIV diagnoses and progression of these cases to AIDS are used to describe the epidemic. The capacity to monitor the national HIV epidemic has consistently improved over the last several years. An increasing number of states report diagnosed HIV cases to the national surveillance system, allowing data from this system to better represent the national picture. Monitoring the national HIV epidemic depends on a nationwide system using standardized methods of data collection, and establishing such a comprehensive system remains one of the highest priorities for national HIV case surveillance.

Estimating incidence of the French BSE infection using a joint analysis of both asymptomatic and clinical BSE surveillance data

Bovine Spongiform Encephalopathy (BSE) clinical surveillance data were the main source of information to perform back-calculation of BSE infection incidence. Since 2001, systematic BSE screening tests enhanced the clinical surveillance and allowed to detect some preclinical, i.e. asymptomatic, cases of BSE. We propose a method to incorporate additional information provided by screening tests. It was the first time that a back-calculation model was developed for a full BSE clinical surveillance. In the spirit, our approach resembles what it was done in the Acquired Immune Deficiency Syndrome (AIDS) epidemic to incorporate the Human Immunodeficiency Virus (HIV) diagnosis. Nevertheless, in the BSE epidemic, we had to consider different surveillance systems, their peculiarity, and the phenomenon of communicating vessels between these surveillance systems. In addition, both the preclinical sensitivity of tests and the status of BSE cases, asymptomatic or clinical, were not precisely known. We applied the model to the French BSE epidemic in order to obtain an updated estimate of the incidence of BSE infection. Our back-calculation model fitted very well the observed data of each surveillance system. We detected a lengthening of the incubation period and estimated that the number of infections was very small in the late 1990s and zero in July 2001.

Bayesian back-calculation using a multi-state model with application to HIV

Back-calculation is a method of obtaining estimates of the number of infections of a disease over time. Data on an endpoint of the disease, together with knowledge of the time from infection to endpoint, allows reconstruction of the incidence of infection. The technique has had much success when applied to the HIV epidemic, using incidence of AIDS diagnoses to inform past HIV infections. In recent years, the period from infection to AIDS has changed considerably due to new regimes of anti-viral therapies. This has led to attempts to use incidence of first positive HIV test as an alternative basis for back-calculation. Developing on earlier work, this paper explores the feasibility of a multi-state formulation of the back-calculation method that models the disease and diagnosis processes and uses HIV diagnoses as an endpoint. Estimation is carried out in a Bayesian framework, which naturally allows incorporation of external information to inform the diagnosis probabilities. The idea is illustrated on data from the HIV epidemic in homosexuals in England and Wales.

Monitoring the severe acute respiratory syndrome epidemic and assessing effectiveness of interventions in Hong Kong Special Administrative Region

OBJECTIVE

To estimate the infection curve of severe acute respiratory syndrome (SARS) using the back projection method and to assess the effectiveness of interventions.

DESIGN

Statistical method.

DATA

The daily reported number of SARS and interventions taken by Hong Kong Special Administrative Region (HKSAR) up to 24 June 2003 are used.

METHOD

To use a back projection technique to construct the infection curve of SARS in Hong Kong. The estimated epidemic curve is studied to identify the major events and to assess the effectiveness of interventions over the course of the epidemic.

RESULTS

The SARS infection curve in Hong Kong is constructed for the period 1 March 2003 to 24 June 2003. Some interventions seem to be effective while others apparently have little or no effect. The infections among the medical and health workers are high.

CONCLUSIONS

Quarantine of the close contacts of confirmed and suspected SARS cases seems to be the most effective intervention against spread of SARS in the community. Thorough disinfection of the infected area against environmental hazards is helpful. Infections within hospitals can be reduced by better isolation measures and protective equipments.

Age-specific back-projection of HIV diagnosis data

A method for reconstructing the HIV infection curve from data on both HIV and AIDS diagnoses is enhanced by using age as a covariate and by using the diagnosis data to estimate parameters that were previously assumed known. Maximum likelihood estimation is used for parameters of the induction distribution. Each of the set of parameters that specify the baseline rate of infection over time and the set of parameters giving the relative susceptibility over age are estimated by maximizing the likelihood subject to a smoothness requirement. We find that estimating the extra parameters is feasible, producing estimates with good precision. Including age as a covariate gives 90 per cent confidence intervals for the HIV incidence curve that are about 20 per cent narrower than those obtained when age data are not used.