Testing for Recent Infection to Estimate HIV Incidence from Single Cross-Sectional Surveys

The first SACEMA Quarterly update of 2010 was devoted to the topic of HIV incidence (the rate of occurrence of new infections in a population). Incidence will always remain a crucial measure in epidemiology, providing a direct and current indication of the spread of disease. Prevalence (the fraction of the population with a condition at a point in time) is a metric more commonly measured, but is less informative as it emerges from historic incidence, demography and survival dynamics. South Africa has the largest HIV-positive population, exceeding 5 million individuals in 2011 (1). This year the government will launch its second 5-year National Strategic Plan (NSP) against HIV for 2012-2016. The headline goal of the first 5-year NSP (2007 – 2011) was to halve incidence, but it will be difficult to assess whether this goal has been achieved. There are a number of approaches for estimating HIV incidence, with varying tractability, complexity and limitations. (i) In a prospective longitudinal study of a cohort of initially uninfected subjects, infection events are directly counted. However, such studies can be costly and prone to unrepresentative sampling. (ii) HIV prevalence, measured in sentinel or general populations, is often modelled to estimate incidence. For example, in age groups with low HIV mortality, differences in prevalence by age may be attributed to new infections. Alternatively, prevalence, measured at multiple time points in the past, could be used to estimate historic incidence. However, prevalence data has become increasingly complex to interpret as epidemics mature, and knowledge of post-infection mortality is often limited. (iii) Alternatively, back-calculation from AIDS cases involves estimating the historic HIV incidence that produced the observed AIDS incidence. However, this method provides little indication of recent incidence. An extension of this method utilises reported HIV diagnoses too. (iv) There are also a number of detailed ‘microscopic’ models, such as the UNAIDS Modes of Transmission model (see SACEMA Quarterly, March 2010), and dynamical models. These typically explicitly model the mechanisms of transmission of the virus through the population, requiring a number of quantitative assumptions. Additionally, in recent years, there has been considerable interest in estimating HIV incidence from single cross-sectional surveys testing for ‘recent infection’ through laboratory-measured host or viral biomarkers (2). In a survey, the sizes of the HIV-negative, ‘recently infected’ and ‘non-recently infected’ populations can be measured, and incidence estimated using knowledge of the dynamics of the ‘recent infection’ biomarker (3,4,5). Given the potential benefits arising from using single cross-sectional surveys for incidence estimation, this approach has been applied in numerous studies, and has caught the attention of prominent organisations worldwide. The World Health Organisation (WHO) Technical HIV Incidence Assay Working Group (HIVIWG) produced an extensive guide on the use of biomarkers for ‘recent infection’ for incidence estimation. The Centers for Disease Control and Prevention (CDC) continues to actively improve laboratory tests used to measure biomarkers that identify ‘recent infection’, and, earlier this year, supported the WHO’s efforts by hosting the latest HIVIWG meeting (August 2011). Notably, the Bill and Melinda Gates Foundation (BMGF) awarded the Health Protection Agency (HPA) a grant to assess, compare and optimise recent infection tests. The group working on this three-year project (20112013) is called CEPHIA, the Consortium for the Evaluation and Performance of HIV Incidence Assays, and comprises HPA, Blood Systems Research Institute (BSRI); University of California, San Francisco (UCSF); and SACEMA. Two key obstacles to cross-sectional biomarkerbased incidence surveillance remain: the (i) lack of standardisation of terminology and methodology, and (ii) poor characteristics, and characterisation, of currently available tests.