A Risk-based Model for Predicting the Impact of using Condoms on the Spread of Sexually Transmitted Infections.

We create and analyze a mathematical model to estimate the impact of condom-use and sexual behavior on the prevalence and spread of Sexually Transmitted Infections (STIs). STIs remain a significant public health challenge globally with a high burden of some Sexually Transmitted Diseases (STDs) in both developed and undeveloped countries. Although condom-use is known to reduce the transmission of STIs, there are a few quantitated population-based studies on the protective role of condom-use in reducing the incidence of STIs. The number of concurrent partners is correlated with their risk of being infectious by a STI such as chlamydia, gonorrhea, or syphilis. We define a Susceptible-Infectious-Susceptible (SIS) model that distributes the population by the number of concurrent partners. The model captures the multi-level heterogeneous mixing through a combination of biased (preferential) and random mixing between individuals with different risks, and accounts for differences in condom-use in the low- and high-risk populations. We use sensitivity analysis to assess the relative impact of high-risk people using condom as a prophylactic to reduce their chance of being infectious, or infecting others. The model predicts the STI prevalence as a function of the number of partners that a person has, and quantifies how this distribution changes as a function of condom-use. Our results show that when the mixing is random, then increasing the condom-use in the high-risk population is more effective in reducing the prevalence than when many of the partners of high-risk people have high risk. The model quantified how the risk of being infected increases for people who have more partners, and and the need for high-risk people to consistently use condoms to reduce their risk of infection.