The impact of sexual mixing patterns on the spread of AIDS.

It has previously been demonstrated that the distribution of sexual partner change rates may not be sufficient behavioral information to predict the spread of AIDS. A more adequate description of the sexual network through which AIDS may spread will require information on who mixes with whom. Previous models indicated that a highly "assortive" pattern of sexual mixing, in which people of high partner change rates nearly always partner similar people, would result in a relatively rapid epidemic but one that would ultimately be rather small as it would be largely confined to those with high partner change rates. However, in earlier models it was necessary to arbitrarily vary either the partnering patterns or the distribution of partner change rates as the epidemic progressed in order to ensure consistency in the partnering patterns. Consequently, the "pure" effects of assortiveness on the size of the epidemic could not be assessed. In this paper a new model is described in which consistency in partnering patterns is maintained as the epidemic selectively depletes those with higher partner change rates. However, this model maintains consistency without arbitrary adjustments to either the assortive nature of partnering or important features of the distribution of the partner change rate. It is then possible to test the effects of assortiveness on the outcome of the epidemic without important confounding effects from the mathematical device used to maintain consistency in partnering. A practical sensitivity test on the impact of assortiveness on model predictions shows that, contrary to expectations, increasing assortiveness can, under certain circumstances, lead to larger epidemics.

Modelling AIDS reduction strategies.

BACKGROUND: Mathematical models of the AIDS epidemic have not been able to give accurate predictions about the size of the epidemic because it is not possible to obtain sufficiently accurate measurements of the factors that enable HIV transmission. The uncertainties inherent in models of the AIDS epidemic appear to limit their relevance to epidemiologists. However, it is shown here that the uncertainties need not prevent models being used to make reliable decisions about which preventive strategy will be most effective. METHOD: A range of strategies are simulated in a model of the AIDS epidemic. The simulations are repeated as the value of what seems to be the most important uncertain factor, is varied. The effect of this variation on the effectiveness of each strategy is noted. In principle, the process could be repeated whilst all other uncertain factors are varied as well. RESULTS: Although varying one uncertain factor created enormous variation in the size of the epidemic, it is remarkable that for most preventive strategies the relative effectiveness of the strategies was barely altered. Hence for the most part the ranking of strategies in order of effectiveness is not affected by the area of uncertainty explored here. The results also highlight the potential effectiveness not only of general condom promotion, but also the use of circumcision and spermicides and general screening or targetted screening in sexually transmitted disease clinics. CONCLUSIONS: Epidemiological modelling may accurately rank the effectiveness of interventions although it may fail to predict the size of the epidemic.

Assessment of sexual mixing patterns.

The manner in which people with varying partner change rates choose their partners may have important implications for the future of the AIDS epidemic. A relatively rapid but small epidemic can be expected if sexual mixing patterns are highly assortative so that those with high partner change rates nearly always choose partners with similar rates. Direct estimation of sexual mixing is exceedingly difficult. On the other hand, information on the way people mix is implicitly contained in the epidemiology of other sexually transmitted diseases (STDs). If mixing is highly assortative, one might expect gonorrhea to be largely confined to a small subsection of the population who would frequently contract the disease repeatedly. In this paper a model of gonorrhea transmission in which partner change rates and preference are dealt with as continuous variables is used to extract information on mixing from data on an Australian heterosexual population. It was found that in this population mixing is not far from random with respect to partner change rates.

Modeling AIDS as a function of other sexually transmitted disease.

The spread of AIDS, as with any sexually transmitted disease, will depend on the pattern of sexual activity. Both the proportion of the population who have high partner exchange rates and the extent to which that proportion interacts with the remainder of the population are likely to be important determinants of the AIDS epidemic. However, it does not seem likely that surveys could obtain sufficiently reliable information of this nature for use in an accurate model of the AIDS epidemic. On the other hand, such information is implicitly contained in the epidemiology of other sexually transmitted diseases (STDs). Therefore a method is suggested of calculating the parameters of a model of the AIDS epidemic by comparing it with the epidemiology of another STD. The result is a model that predicts the likelihood of infection by the AIDS virus as a function of time and an individual's history of STD. It is suggested that further work along these lines may lead to a quantitative approach to assessing the importance of various STDs as cofactors in the spread of AIDS.

Further investigation of a strabismus model.

Computer models of strabismus have been available for about ten years. Such models are computer programs which perform a set of calculations based on an interpretation of the oculomotor system as a system of two spheres each with six adjustable springs. The effects of pathology and surgery can be simulated by altering the parameters of the springs. However, such models have not yet met with wide practical acceptance. One reason for this lack of interest is that previous investigators have neglected to apply strabismus models to concomitant strabismus. In this paper the application of a strabismus model to concomitant strabismus is demonstrated and data are generated which should be clinically useful. Another reason for lack of acceptance of computer models results from the expectation that they may be unreliable because of biological variability. The model developed here is tested for its sensitivity to a wide range of biological variations and proves to be very robust. Therefore, information on concomitant squint surgery given by the model should be applicable to most patients.