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- HIV, human immunodeficiency virus
- IDU, injecting drug user
- STD, sexually transmitted disease
- STI, sexually transmitted infection
Since the turn of the century insights into sexually transmitted disease (STD)/HIV epidemiology and prevention have proliferated. Accumulating empirical data and mathematical modelling efforts interactively point to a number of grounded generalisations that enhance our understanding of the spread of STIs including HIV in populations. These insights have important implications for the design and implementation of prevention programmes: they can guide expectations around the magnitude and shape of STI/HIV epidemics in the absence of prevention and control programmes; they can guide thoughts about when to implement prevention strategies, which subgroups to target and how to define required coverage; and they can help interpret programme successes and failures.1
An important generalisation is about the central role of population-level parameters in determining the magnitude and shape of STI epidemics. Whereas individual-level parameters may influence which individuals in a given population acquire infection, it is population-level parameters that affect the presence and prevalence of infection to be acquired.
Sexual structure is a population-level parameter which increasingly emerges as an important determinant of whether major epidemics emerge in populations. The size and distribution of high-risk groups, or core groups, is an aspect of sexual structure that has received attention over the years.2–5 High-risk groups include sex workers, clients of sex workers, injecting drug users (IDUs) and men having sex with men. In specific areas other groups such as truck drivers or miners may also be defined as high-risk groups. A recent analysis suggests that the number of infected sex workers in a country, measured as a percentage of the total female adult population age 15–49 years, is highly positively correlated with country-wide HIV/AIDS prevalence levels.6 Although this analysis probably overstates the importance of sex work in determining the size of epidemics in southern Africa, in much of the world the …
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