Adressing population heterogenity in epidemics models using cellular automata

LOPEZ L, GIOVANINI L; BURGUERNER G

BMC Research Notes

Biomedical Central

Año: 2014 vol. 7 p. 234 - 245

1756-0500

Background:The spread of an infectious disease is determined by biological and  social factors. Models based oncellular automata are adequate to describe such natural systems consisting of a massive collection of simpleinteracting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode theindividual behaviour and the transmission dynamic. Methods:An epidemic is characterized trough an individual?based?model built upon cellular automata. In theproposed model, each individual of the population is represented by a cell of the automata. This way of modeling anepidemic situation allows to individually define the characteristic of each individual, establish different scenarios andimplement control strategies. Results:A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics andsocial factors that determine the dynamic of the desease. Different assumptions made to built the classical modelwere evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions: The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play acentral role in the dynamics of the desease.