Use of mathematical modeling in predicting the impact of a disease: An example of measles dynamic model

Protecting children from vaccine-preventable diseases, such as measles, is among primary goals of public health professionals worldwide. Since vaccination turned out to be the most effective strategy against major childhood diseases, developing a mathematical model that would predict an optimal vaccine coverage level needed to control the spread of these diseases becomes a challenge for various experts Worldwide as well designed mathematical model could be extremely helpful for the daily routine practice. Elaborating a mathematical model could be extremely helpful for the daily routine practice. Elaborating a mathematical models for monitoring of measles with its vaccination coverage and predicting the impact of this disease in population is the basic objective of this paper. The model was elaborated with the population of B&H as at the census of 1971-just before the obligatory vaccination was introduced-used as a theoretical population. The epidemiological classification of the population was performed for all of the age groups. In this paper we assume that all vaccinated individuals develop antibody following vaccination. Known variables of susceptible, sick and immune population to create a mathematical model of the dynamics of measles showing spread within a population to design this model were used. A dynamic model expressed by a global model with its sub-model based on the dynamics of measles infection was created. The model, which fully incorporates elements of measles dynamics relevant for the spread of the disease is quantitative and dynamic. It facilitates long-term projections of the spread of the disease and identifies the possibilities for an efficient protection. The model shows percentage of the immune persons at any given immunisation level and morbidity and lethality that can be expected at that level of immunisation.