Adapting connections: integrating adaptive behavior into epidemiological multilayer network models
Speaker: Fabio Sanchez, University of Costa Rica
Abstract: The evolution of infectious diseases requires innovative modeling strategies that accurately capture the complex, adaptive behaviors underlying human interactions and their implications for disease transmission. We introduce a novel approach to epidemiological modeling by integrating adaptive behavior into multilayer network models, offering a more nuanced understanding of how diseases spread through human populations. By examining multiple dimensions of human contact networks, from physical interactions to digital communications, the goal is to highlight how individuals modify their behaviors in response to perceived disease risks and how these changes can influence the trajectory and evolution of an epidemic.
Bio: Fabio Sanchez has a Ph.D. in Biological Mathematics from Cornell University in New York. Currently, he works as a teacher and researcher at the School of Mathematics-CIMPA of the University of Costa Rica (UCR). His research interests lie in the modeling of infectious diseases, with greater emphasis on those that are transmitted by vectors such as dengue, chikungunya, and Zika. Nonlinear systems of differential equations are used to model this dynamic. These predictive models are used to study the spread of this type of disease in a population. In addition, with these models, prevention and/or control strategies can be developed for public health officials.