The central theme of this first SACEMA Quarterly Epidemiological Update of 2010 is the rate of occurrence of new HIV infections – also known as HIV incidence. The issue is examined through three distinct perspectives: 1) Recent advances in measuring the HIV incidence in a population, and/or how it changes over time, 2) estimating the relative importance of various ‘modes of transmission’ in contributing to new cases of HIV infection, and 3) the use of antiretroviral treatment of infected individuals to curb their infectivity and hence reduce HIV incidence.
Prevalence and incidence are the two most important indicators of the state of an epidemic. The most common way in which incidence is measured is by follow-up of an initially uninfected cohort. For infections with a relatively short duration, another method for estimating incidence is available using a cross-sectional survey. Unfortunately, HIV has a long asymptomatic phase before the onset of immune failure and AIDS. In this article a way to estimate HIV incidence using biomarkers in cross-sectional surveys is described and the challenges of this approach are discussed.
Effective planning and delivery of HIV prevention programs depends on an understanding of where new infections are occurring and on the behaviours associated with those infections. A simple mathematical model developed by the UNAIDS Reference Group for Estimates, Modelling and Projections helps countries estimate the proportion of new infections that occur through key transmission modes. This type of in-country analysis could be used to inform the planning of appropriately targeted intervention programmes. However, improved biological and behavioural surveillance in countries is needed to provide more reliable data for input into such analyses.
In Swaziland the risk of getting HIV infected is significantly higher among young women compared to young men. These differences cannot be explained by anatomical and hormonal factors that make young women particularly vulnerable to HIV infection. In this article the results of a secondary analysis of the Swaziland Demographic and Health Survey 2006-2007 data is described. In particular, trends and variability in age differences between young men and their female sexual partners are explored. In addition the magnitude of the age difference between sexual partners and the association with consistent condom use is examined.