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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/29026

Title: Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach
Authors: Angulo Ibáñez, José Miguel
Yu, Hwa-Lung
Langousis, Andrea
Kolovos, Alexander
Wang, Jinfeng
Madrid García, Ana Esther
Christakos, George
Issue Date: 2013
Abstract: 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.
Sponsorship: J.M. Angulo and A.E. Madrid have been partially supported by grants MTM2009-13250 and MTM2012-32666 of SGPI, and P08-FQM-3834 of the Andalusian CICE, Spain. H-L Yu has been partially supported by a grant from National Science Council of Taiwan (NSC101-2628-E-002-017-MY3 and NSC102-2221-E-002-140-MY3). A. Kolovos was supported by SpaceTimeWorks, LLC. G. Christakos was supported by a Yongqian Chair Professorship (Zhejiang University, China).
Publisher: Public Library of Science
Keywords: Population dynamics
Infectious disease
Disease susceptibility
Modeling
Control
Covariance
Spatial distribution
Evolutionary modeling
URI: http://hdl.handle.net/10481/29026
ISSN: 1932-6203
Citation: Angulo, J.; et al. Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach. Plos One, 8(9): e72168 (2013). [http://hdl.handle.net/10481/29026]
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