Mathematical Models for Optimizing and Predicting Outcomes of Intervention Measures for the Control of Lymphatic Filariasis

Lymphatic filariasis is a debilitating disease attaching social stigma to afflicted people living in most of the tropical countries in the world. Globally about 120 million people are affected with the disease of which one-third live in India alone. With the recent advancement in diagnostic and control tools, the hope for the control of filariasis is expanding. However, due to the complex nature of the disease a number of factors are yet to be understood. In the absence of animal models little is known about the mechanisms regulating the parasite population and the development of disease in host populations; knowledge on the efficacy of the currently available drugs on parasite populations and the long-term impact of control programmes are limited. A sound quantitative understanding of the population dynamics of the parasite is important for developing and identifying the most costeffective and sustainable control strategies. This requires, however, reliable predictions of the long-term impact of alternative control strategies. Mathematical models provide the necessary quantitative framework for investigating the key issues related to parasite population dynamics and for making credible predictions of epidemiological trends and for aiding decisions about control strategies before, during and after cessation of control activities. There are several examples for the successful and practical application of mathematical models for disease control. The best example is the application of a simulation model for the onchocerciasis control programme in the West Africa.