SPATIAL EPIDEMIOLOGICAL MODELS OF INFECTIOUS DISEASE TRANSMISSION

DAMIAN KNOPOFF; CUSIMANO, NICOLE; STOLLENWERK, NICO; AGUIAR, MAÍRA

Congreso; 13th Conference on Dynamical Systems Applied to Biology and Natural Sciences ? DSABNS; 2022

In this talk, I will provide a mathematical and computational framework to the modeling and simulationof the spatial dynamics of infectious disease contagion, spreading, control and prevention.Starting from lattice-based models, I will present a stochastic cellular automata disease model based onthe SHAR (Susceptible-Hospitalized-Asymptomatic-Recovered) compartmentalisation of the population,show some simulation results, and relate them to real-life data for influenza and COVID-19 provided by theHealth Department and the Health Services of the Basque Country. By means of stochastic simulations, Iwill present a numerical study to have an insight into the critical threshold of the SHAR percolating system,as well as some numerical tools to seek infection clusters (groups of connected individuals who have beeninfected by the same index case), count them and monitor their sizes [1, 4].Then, some concepts on network theory will be discussed in order to show how networks can be em-ployed as a valuable tool to model spatial spreading. In particular, two models will be discussed: a kineticmodel for the spread of a respiratory disease considering heterogeneous populations [2, 3] and a compart-mental model accounting for bacterial antibiotic resistance [5], focusing on the role of the network structureand connectivity on the overall dynamics.