mathematical model, R0 = cD (May and Anderson, 1987; Anderson, 1991). In this model, R0, the reproductive rate of infection, represents the average number of secondary cases of STDs that arise from a new case; c is the mean rate of sexual partner change within the population; is the mean probability of transmission per exposure; and D is the mean duration of infectiousness of newly infected persons. Thus, interventions can prevent the spread of an STD within a population by reducing the rate of exposure to an STD; lowering the rate of partner change; reducing the efficiency of transmission; or shortening the duration of infectiousness for that STD. An extremely important conclusion from this model is that, for communicable diseases such as STDs, if R0 remains less than 1, the infection eventually disappears from the population. A sustained prevention program can drive the infection to extinction in the entire population, even when these interventions are provided only to individuals and social networks with the highest rates of transmission (Anderson, 1991).
Anderson and May (1991) have highlighted differences in the epidemiology of communicable and noncommunicable diseases that have important implications for prevention of STDs. First, rates of partner change within the population and patterns of partner mixing greatly influence the spread of STDs. In essence, individuals with the highest rates of partner change, referred to as "core" groups or transmitters, disproportionately increase the rate of spread. Furthermore, mathematical models show that patterns of sex partner mixing and the characteristics of sexual networks are important determinants of the rate of spread of STDs. For example, if individuals with many partners tend to have sex with others who have