James Jansson

Per-contact probability of HIV transmission in homosexual men in Sydney in the era of HAART.

Objective:The objective of this study is to estimate per-contact probability of HIV transmission in homosexual men due to unprotected anal intercourse (UAI) in the era of HAART. Design:Data were collected from a longitudinal cohort study of community-based HIV-negative homosexual men in Sydney, Australia. Methods:A total of 1427 participants were recruited from June 2001 to December 2004. They were followed up with 6-monthly detailed behavioral interviews and annual testing for HIV till June 2007. Data were used in a bootstrapping method, coupled with a statistical analysis that optimized a likelihood function for estimating the per-exposure risks of HIV transmission due to various forms of UAI. Results:During the study, 53 HIV seroconversion cases were identified. The estimated per-contact probability of HIV transmission for receptive UAI was 1.43% [95% confidence interval (CI) 0.48–2.85] if ejaculation occurred inside the rectum, and it was 0.65% (95% CI 0.15–1.53) if withdrawal prior to ejaculation was involved. The estimated transmission rate for insertive UAI in participants who were circumcised was 0.11% (95% CI 0.02–0.24), and it was 0.62% (95% CI 0.07–1.68) in uncircumcised men. Thus, receptive UAI with ejaculation was found to be approximately twice as risky as receptive UAI with withdrawal or insertive UAI for uncircumcised men and over 10 times as risky as insertive UAI for circumcised men. Conclusion:Despite the fact that a high proportion of HIV-infected men are on antiretroviral treatment and have undetectable viral load, the per-contact probability of HIV transmission due to UAI is similar to estimates reported from developed country settings in the pre-HAART era.

Relative risk of renal disease among people living with HIV: a systematic review and meta-analysis

BackgroundAntiretroviral therapy (ART) has substantially decreased mortality and HIV-related morbidity. However, other morbidities appear to be more common among PLHIV than in the general population. This study aimed to estimate the relative risk of renal disease among people living with HIV (PLHIV) compared to the HIV-uninfected population.MethodsWe conducted a systematic review and meta-analysis of relative risks of renal disease among populations of PLHIV reported in studies from the peer-reviewed literature. We searched Medline for relevant journal articles published before September 2010, yielding papers published during or after 2002. We also searched conference proceedings of the International AIDS Society (IAS) and Conference on Retroviruses and Opportunistic Infections (CROI) prior to and including 2010. Eligible studies were observational studies reporting renal disease defined as acute or chronic reduced renal function with glomerular filtration rate less than or equal to 60 ml/min/1.73 m2 among HIV-positive adults. Pooled relative risks were calculated for various groupings, including class of ART drugs administered.ResultsThe overall relative risk of renal disease was 3.87 (95% CI: 2.85-6.85) among HIV-infected people compared to HIV-uninfected people. The relative risk of renal disease among people with late-stage HIV infection (AIDS) was 3.32 (1.86-5.93) compared to other PLHIV. The relative risk of renal disease among PLHIV who were receiving antiretroviral therapy (ART) was 0.54 (0.29-0.99) compared to treatment-naïve PLHIV; the relative risk of renal disease among PLHIV who were treated with tenofovir was 1.56 (0.83-2.93) compared to PLHIV who were treated with non-tenofovir therapy. The risk of renal disease was also found to significantly increase with age.ConclusionPLHIV are at increased risk of renal disease, with greater risk at later stages of infection and at older ages. ART prolongs survival and decreases the risk of renal disease. However, less reduction in renal disease risk occurs for Tenofovir-containing ART than for other regimens.

Projected Demographic Profile of People Living with HIV in Australia: Planning for an Older Generation

Background Advances in HIV antiretroviral therapy (ART) has reduced mortality in people living with HIV (PLHIV), resulting in an ageing population of PLHIV. Knowledge of demographic details such as age, geographical location and sex, will aid in the planning of training and resource allocation to effectively care for the future complex health needs of PLHIV. Methods An agent-based, stochastic, geographical model was developed to determine the current and future demographic of PLHIV in Australia. Data and parameters were sourced from Australias National HIV Registry and peer reviewed literature. Processes that were simulated include progression to AIDS, mortality and internal migration. Findings The model estimates the mean age of PLHIV in Australia is increasing at a rate of 0.49 years each year. The expected proportion of PLHIV in over 55 years is estimated to increase from 25.3% in 2010 to 44.2% in 2020. Median age is lower in inner-city areas of the capital cities than in rural areas. The areas with the highest prevalence of HIV will continue to be capital cities; however, other areas will have greater percentage growth from 2010 to 2020. Conclusions The age of the population of people living with HIV is expected to increase considerably in the future. As the population of PLHIV ages, specialist clinical training and resource provision in the aged care sector will also need to be addressed.

Predicting the population impact of increased HIV testing and treatment in Australia

UNLABELLED Introduction The treatment as prevention strategy has gained popularity as a way to reduce the incidence of HIV by suppressing viral load such that transmission risk is decreased. The effectiveness of the strategy also requires early diagnosis. METHODS Informed by data on the influence of diagnosis and treatment on reducing transmission risk, a model simulated the impact of increasing testing and treatment rates on the expected incidence of HIV in Australia under varying assumptions of treatment efficacy and risk compensation. The model utilises Australias National HIV Registry data, and simulates disease progression, testing, treatment, transmission and mortality. RESULTS Decreasing the average time between infection and diagnosis by 30% is expected to reduce population incidence by 12% (~126 cases per year, 95% confidence interval (CI): 82-198). Treatment of all people living with HIV with CD4 counts <500cellsμL(-1) is expected to reduce new infections by 30.9% (95% CI: 15.9-37.6%) at 96% efficacy if no risk compensation occurs. The number of infections could increase up to 12.9% (95% CI: 20.1-7.4%) at 26% efficacy if a return to prediagnosis risk levels occur. CONCLUSION Treatment as prevention has the potential to prevent HIV infections but its effectiveness depends on the efficacy outside trial settings among men who have sex with men and the level of risk compensation. If antiretroviral therapy has high efficacy, risk compensation will not greatly change the number of infections. If the efficacy of antiretroviral therapy is low, risk compensation could lead to increased infections.

Currently available medications in resource-rich settings may not be sufficient for lifelong treatment of HIV

Objective:Combination antiretroviral therapy (cART) has greatly improved the life expectancy of people living with HIV (PLHIV). Our study aims to project the life expectancy of PLHIV in a resource-rich setting in the context of the currently available antiretroviral treatments. Methods:Patient antiretroviral treatment data were sourced from an observational cohort of 3434 predominantly male (94.2%) PLHIV in Australia over the period 1997–2010. These data were analyzed in a computer simulation model to calculate the distribution of time until exhaustion of all treatment options and expected effect on mortality. Standardized mortality ratios were used to simulate expected survival before and after treatment exhaustion. Results:We estimated that the median time until exhaustion of currently available treatment options is 45.5 years [interquartile range (IQR) 34.0–61.0 years]. However, 10% of PLHIV are expected to exhaust all currently available cART options after just 25.6 years. PLHIV who start currently available cART regimens at age 20 years are expected to live to a median age of 67.4 (IQR 53.2–77.7) years. This is a substantial improvement on no cART [27.7 (IQR 23.8–32.0) years] but is still substantially less than the median general population mortality age [82.2 (IQR 74.0–87.8) years]. The life expectancy gap between PLHIV and the general population is greatest for those infected at younger ages. Conclusion:As treatment options are exhausted, a substantial difference in life expectancy between PLHIV and the general population could be expected even in resource-rich settings, particularly for people who acquire HIV at a younger age or who are currently highly treatment experienced.

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.

Demand for HIV clinical services is increasing in Australia but supply is decreasing

BACKGROUND HIV clinical service planning requires accurate estimates of the number of people living with HIV (PLHIV) and the capacity of existing clinical services, each by geographical location. The aim of this study was to quantify current HIV clinical service capacity in Australia. METHODS This study was a retrospective analysis of records of HIV clinical service capacity in Australia. Participants were general practitioners who completed an annual survey in 2007-2009. Information on the number of hospital departments, sexual health services, antiretroviral-prescribing general practitioners (ARV-GPs) and shared-care services providing expertise in HIV management from 2007 to 2010 were also available. RESULTS From 2007 to 2009, the proportion of ARV-GP survey respondents treating 2-9 patients with HIV per week increased from 36.5% to 49.1%, with a corresponding decrease in the average proportion who saw less than one patient with HIV per week. The estimated number of PLHIV has increased by 12.5% in metropolitan areas, and 16.5% in rural and remote areas over the period 2007-2010; however, the total number of services with at least one HIV ARV-GP has decreased over the same period. CONCLUSIONS Current methods to estimate clinical service capacity reveal decreasing supply in the workforce in Australia despite increasing numbers of PLHIV. Further training of HIV clinicians and their placement in regions of greatest supply-demand deficits are required. Further studies are required to precisely quantify and locate the capacity of the HIV clinical workforce with expertise in HIV case-management to enable efficient service planning.

HIV antiretroviral prophylaxis for injecting drug users

854 www.thelancet.com Vol 382 September 7, 2013 costs, or the health-care costs avoided by preventing HIV infections. These estimates also do not include the possibility of risk compensation, which might increase the rate of risk behaviour in injecting drug users who understand that treatment can reduce the probability of transmission. Needle–syringe programmes are more cost-effective than these calculated cost-eff ectiveness ratios for pre-exposure prophylaxis. The cost per HIV infection averted by needle– syringe programmes is estimated to be

Feasible HCV targets in Egypt

13 000–1 056 034 in highincome settings, and

HIV service capacity: identifying current and future areas of clinical shortage

138–9 537 in countries where discounted tenofovir is available. The effectiveness of pre-exposure prophylaxis in populations injecting drugs would depend on attainment of adequate coverage and on suffi ciently high adherence to maintain individual effi cacy. The coverage of antiretroviral therapy among HIV-positive injecting drug users is less than 1% in many countries. Coverage of antiretrovirals among HIV-negative injecting drug users would be expected to be substantially lower. Therefore, because of expected low coverage and unimpressive cost-effectiveness ratios, we believe that pre-exposure prophylaxis is unlikely to be widely used for HIV prevention in injecting drug users.