Both Grassly et al. (2003) and Saidel et al. (2003) investigate the effect of injecting drug use (IDU) on the risk of a generalised heterosexual HIV epidemic, using modelling techniques. The difference in results is startling. While Grassly et al. find almost no effect of spread among IDUs on subsequent widespread heterosexual epidemics, Saidel et al. predict very large effects in diverse epidemic settings. We will discuss the main findings of both papers and possible reasons for the seemingly different results as well as policy implications, including the potential for using sexually transmitted infections (STIs) as an indirect indicator for the risk of generalised HIV epidemics (Lowndes et al., 2003). On the basis of the scarce available data about sexual and drug injecting behaviours in Russia, Grassly et al. investigate the risk for HIV/AIDS to expand beyond the traditional risk groups of injecting drug users and highly active sexual core groups into larger parts of the population. They discuss the possibility of a generalised epidemic in Russia, India and China, that is an epidemic that encompasses more than 1% of the adult population (UNAIDS/WHO, 2001). From their results, the authors conclude that the occurrence of a generalised epidemic cannot be ruled out. A lower bound of projected prevalence, as reflected by the 2.5th percentile, is already a staggering 5% of the adult population with HIV infection after 10 years, with the median and maximum prevalence reaching an almost unthinkable 60 and 80%, respectively. Although these projections may be seriously affected by the lack of data, they should be taken as very alarming indications of a possible worst case scenario. Less dependent on data availability than their actual prevalence estimates, and thus more reliable, are results from the sensitivity analyses. These show which parameters contribute most to the spread of HIV, and how the importance of those parameters changes with the course of the epidemic. In line with recent epidemiological data (Kral et al., 2001; Strathdee et al., 2001) and with previous modelling work (Blower, Hartel, Dowlatabadi, Anderson, & May, 1991), sexual transmission appears to gain importance in IDUs after initial rapid injection-related spread. However, the effect of epidemics in IDUs on the risk of a generalised heterosexual epidemic seems very small. In Grassly et al., mean rate of partner change explains 36 /40.9% of the variance in all-adult prevalence after 5 years, STI recovery/treatment explains 6.7 /10.9%, mixing between different sexual activity groups up to 3.9%, while needle sharing and the rate of acquiring new sharing partners among IDUs are in the range of 0.03 /1%. Moreover, random mixing between IDUs and non-IDUs has almost no effect on reaching the threshold of 5% total prevalence, as compared to random mixing of all adults, and it has only a slight effect on reaching the 0.1% total prevalence threshold, given high rates of needle sharing. These small effects occur in spite of a very high upper limit for the proportion of IDUs in the model: 10% of the adult population. Although it is stated that needle sharing remains important, the results seem to suggest a very small effect of epidemics among IDUs on the risk of generalised heterosexual spread. Saidel et al. take a different approach, focusing on the effect of IDU epidemics on the spread in sex workers and their clients, a main core group for sexual transmission. In the Asian settings described by their model there is extensive mixing between sex workers and IDUs so that the first effects of high prevalence in IDUs may indeed be expected among sex workers and clients. They use a similar compartmental model, with an IDU component and a heterosexual component, the latter describing spread due to commercial sex, casual sex and sex between spouses. To better understand the effect of * Corresponding author. E-mail address: lucas.wiessing@emcdda.eu.int (L. Wiessing). International Journal of Drug Policy 14 (2003) 99 /102