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Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach

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  • Jose Angulo
  • Hwa-Lung Yu
  • Andrea Langousis
  • Alexander Kolovos
  • Jinfeng Wang
  • Ana Esther Madrid
  • George Christakos

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.

Suggested Citation

  • Jose Angulo & Hwa-Lung Yu & Andrea Langousis & Alexander Kolovos & Jinfeng Wang & Ana Esther Madrid & George Christakos, 2013. "Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-12, September.
  • Handle: RePEc:plo:pone00:0072168
    DOI: 10.1371/journal.pone.0072168
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    References listed on IDEAS

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    1. Birgit Schrödle & Leonhard Held & Håvard Rue, 2012. "Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases," Biometrics, The International Biometric Society, vol. 68(3), pages 736-744, September.
    2. B. T. Grenfell & O. N. Bjørnstad & J. Kappey, 2001. "Travelling waves and spatial hierarchies in measles epidemics," Nature, Nature, vol. 414(6865), pages 716-723, December.
    3. Neil M. Ferguson & Matt J. Keeling & W. John Edmunds & Raymond Gani & Bryan T. Grenfell & Roy M. Anderson & Steve Leach, 2003. "Planning for smallpox outbreaks," Nature, Nature, vol. 425(6959), pages 681-685, October.
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    Cited by:

    1. Mario J. Crucini & Oscar O'Flaherty, 2020. "Stay-at-Home Orders in a Fiscal Union," NBER Working Papers 28182, National Bureau of Economic Research, Inc.
    2. Junyu He & George Christakos & Jiaping Wu & Piotr Jankowski & Andreas Langousis & Yong Wang & Wenwu Yin & Wenyi Zhang, 2019. "Probabilistic logic analysis of the highly heterogeneous spatiotemporal HFRS incidence distribution in Heilongjiang province (China) during 2005-2013," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 13(1), pages 1-28, January.

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