Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach Angulo Ibáñez, José Miguel Yu, Hwa-Lung Langousis, Andrea Kolovos, Alexander Wang, Jinfeng Madrid García, Ana Esther Christakos, George Population dynamics Infectious disease Disease susceptibility Modeling Control Covariance Spatial distribution Evolutionary modeling This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China. 2013-11-05T11:12:41Z 2013-11-05T11:12:41Z 2013 info:eu-repo/semantics/article Angulo, J.; et al. Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach. Plos One, 8(9): e72168 (2013). [http://hdl.handle.net/10481/29026] 1932-6203 doi: 10.1371/journal.pone.0072168 http://hdl.handle.net/10481/29026 eng info:eu-repo/semantics/openAccess Public Library of Science