Sexually transmitted diseases (STDs) are a major global health concern. Not all STDs are deadly, but if left untreated, they can often cause chronic disease, other health problems, or even death, as is the case in many developing or underdeveloped countries. Thus, it is important for medical science and operations researchers to study trends in the spread of STDs and examine the types of factors and interventions that affect their spread. Scientists have used computer simulations to analyze and make predictions about the spread of STDs in Nairobi, Kenya. The data and analysis from these simulations help health care decision-makers develop policies and interventions to reduce the incidence of STDs in Nairobi.

The spread of STDs results from many factors ranging across demography, sexual behavior, transmission, natural history, and level of health care. Ten years of data were collected from the population of Nairobi, including health care professionals as well as the general population. The data were then entered into the simulation program, STDSIM. The program simulated 50 years of sexual activity and transmission of STDs. All types of transmission scenarios were simulated and recorded, all of which were generated from data gathered in previous years.

The simulation program also has the capacity to simulate different interventions with the simulated population and output their results. General STD screenings, mass treatment, health care effectiveness, condom use, education, and communication are the most common interventions. Researchers studied the effects of different interventions and combinations of interventions on the simulated populations.

The results from these intervention simulations indicate that immediate and permanent increases in condom use and health care effectiveness would lower the number of infected persons. Using results from models developed using STDSIM aided policy makers in choosing the most appropriate interventions for a given population.

Van der Ploeg, C. P.B., C. Van Vliet, S. J.De Vlas, J. O. Ndinya-Achola, L. Fransen, G. J. Van Oortmarssen, J. D. F. Habbema. "STDSIM: A Micro-simulation Model for Decision Support in STD Control." INTERFACES, 28:3 (1998), 84-100.