Epidemic Spread and Variation of Peak Times in Connected Regions Due to Travel-Related Infections - Dynamics of an Antigravity-Type Delay Differential Model

National boundaries have never prevented infectious diseases from reaching distant territories; however, the speed at which an infectious agent can spread around the world via the global airline transportation network has significantly increased during recent decades. We introduce an SEAIR-based, antigravity model to investigate the spread of an infectious disease in two regions which are connected by transportation. As a submodel, an age-structured system is constructed to incorporate the possibility of disease transmission during travel, where age is the time elapsed since the start of the travel. The model is equivalent to a large system of differential equations with dynamically defined delayed feedback. After describing fundamental but biologically relevant properties of the system, we detail the calculation of the basic reproduction number and obtain disease transmission dynamics results in terms of $\mathcal{R}_0$. We parametrize our model for influenza and use real demographic and air travel data ...

[1]  N. Ferguson,et al.  Time lines of infection and disease in human influenza: a review of volunteer challenge studies. , 2008, American journal of epidemiology.

[2]  Alessandro Vespignani,et al.  influenza A(H1N1): a Monte Carlo likelihood analysis based on , 2009 .

[3]  O Diekmann,et al.  The construction of next-generation matrices for compartmental epidemic models , 2010, Journal of The Royal Society Interface.

[4]  J. Watmough,et al.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. , 2002, Mathematical biosciences.

[5]  Sally Blower,et al.  Calculating the potential for within-flight transmission of influenza A (H1N1) , 2009, BMC medicine.

[6]  Y. Nakata,et al.  Global analysis for spread of infectious diseases via transportation networks , 2013, Journal of Mathematical Biology.

[7]  L. A. Rvachev,et al.  Computer modelling of influenza epidemics for the whole country (USSR) , 1971, Advances in Applied Probability.

[8]  O. Diekmann,et al.  On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations , 1990, Journal of mathematical biology.

[9]  Modeling Disease Spread via Transport-Related Infection By a Delay Differential Equation , 2008 .

[10]  Yukihiko Nakata,et al.  On the global stability of a delayed epidemic model with transport-related infection , 2011, Nonlinear Analysis: Real World Applications.

[11]  D. Earn,et al.  Cholera Epidemic in Haiti, 2010: Using a Transmission Model to Explain Spatial Spread of Disease and Identify Optimal Control Interventions , 2011, Annals of Internal Medicine.

[12]  A. Nizam,et al.  Containing pandemic influenza with antiviral agents. , 2004, American journal of epidemiology.

[13]  J. Lei Monotone Dynamical Systems , 2013 .

[14]  Xiao-Qiang Zhao,et al.  An Age-Structured Epidemic Model in a Patchy Environment , 2005, SIAM J. Appl. Math..

[15]  David Buckeridge,et al.  Estimated epidemiologic parameters and morbidity associated with pandemic H1N1 influenza , 2010, Canadian Medical Association Journal.

[16]  Xianning Liu,et al.  Spread of disease with transport-related infection and entry screening. , 2006, Journal of theoretical biology.

[17]  S. Ruan The effect of global travel on the spread of SARS. , 2005, Mathematical biosciences and engineering : MBE.

[18]  K. Khan,et al.  Spread of a novel influenza A (H1N1) virus via global airline transportation. , 2009, The New England journal of medicine.

[19]  Hal L. Smith,et al.  Monotone Dynamical Systems: An Introduction To The Theory Of Competitive And Cooperative Systems (Mathematical Surveys And Monographs) By Hal L. Smith , 1995 .

[20]  A. Roddam Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation O Diekmann and JAP Heesterbeek, 2000, Chichester: John Wiley pp. 303, £39.95. ISBN 0-471-49241-8 , 2001 .

[21]  L. A. Rvachev,et al.  A mathematical model for the global spread of influenza , 1985 .

[22]  Y. Takeuchi,et al.  Spreading disease with transport-related infection. , 2006, Journal of theoretical biology.

[23]  K. Khan,et al.  An analysis of Canada's vulnerability to emerging infectious disease threats via the global airline transportation network , 2009 .

[24]  Xianning Liu,et al.  Global dynamics of SIS models with transport-related infection , 2007 .

[25]  J. Arino,et al.  A multi-city epidemic model , 2003 .

[26]  Gergely Röst,et al.  Multiregional SIR model with infection during transportation , 2012 .

[27]  Julien Arino,et al.  Diseases in metapopulations , 2009 .

[28]  M. Kretzschmar,et al.  Choosing pandemic parameters for pandemic preparedness planning: a comparison of pandemic scenarios prior to and following the influenza A(H1N1) 2009 pandemic. , 2013, Health policy.

[29]  Merete Kile Holtermann [The cholera epidemic in Haiti]. , 2013, Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke.

[30]  Hal L. Smith,et al.  An introduction to delay differential equations with applications to the life sciences / Hal Smith , 2010 .

[31]  Murray E. Alexander,et al.  A Delay Differential Model for Pandemic Influenza with Antiviral Treatment , 2007, Bulletin of mathematical biology.

[32]  Diána H. Knipl Fundamental properties of differential equations with dynamically defined delayed feedback , 2013 .

[33]  Sebastian Bonhoeffer,et al.  This PDF file includes: SOM Text , 2022 .