A decision-support framework to optimize border control for global outbreak mitigation

The introduction and spread of emerging infectious diseases is increasing in both prevalence and scale. Whether naturally, accidentally or maliciously introduced, the substantial uncertainty surrounding the emergence of novel viruses, specifically where they may come from and how they will spread, demands robust and quantifiably validated outbreak control policies that can be implemented in real time. This work presents a novel mathematical modeling framework that integrates both outbreak dynamics and outbreak control into a decision support tool for mitigating infectious disease pandemics that spread through passenger air travel. An ensemble of border control strategies that exploit properties of the air traffic network structure and expected outbreak behavior are proposed. A stochastic metapopulation epidemic model is developed to evaluate and rank the control strategies based on their effectiveness in reducing the spread of outbreaks. Sensitivity analyses are conducted to illustrate the robustness of the proposed control strategies across a range of outbreak scenarios, and a case study is presented for the 2009 H1N1 influenza pandemic. This study highlights the importance of strategically allocating outbreak control resources, and the results can be used to identify the most robust border control policy that can be implemented in the early stages of an outbreak.

[1]  Igor Linkov,et al.  Resilience management during large-scale epidemic outbreaks , 2017, Scientific Reports.

[2]  S. Riley.  Large-Scale Spatial-Transmission Models of Infectious Disease , 2007, Science.

[3]  J. Brownstein,et al.  Empirical Evidence for the Effect of Airline Travel on Inter-Regional Influenza Spread in the United States , 2006, PLoS medicine.

[4]  Piet Van Mieghem,et al.  Epidemic processes in complex networks , 2014, ArXiv.

[5]  D. Helbing,et al.  The Hidden Geometry of Complex, Network-Driven Contagion Phenomena , 2013, Science.

[6]  Zhongyuan Ruan,et al.  Integrated travel network model for studying epidemics: Interplay between journeys and epidemic , 2015, Scientific reports.

[7]  S. Rewar,et al.  Outbreak of swine-origin influenza A (H1N1) virus infection - Mexico, March-April 2009. , 2009, MMWR. Morbidity and mortality weekly report.

[8]  Zhen Jin,et al.  Pattern transitions in spatial epidemics: Mechanisms and emergent properties , 2016, Physics of Life Reviews.

[9]  S. Sarkar,et al.  Vector status of Aedes species determines geographical risk of autochthonous Zika virus establishment , 2017, PLoS neglected tropical diseases.

[10]  Jinde Cao,et al.  Edge-based epidemic spreading in degree-correlated complex networks. , 2018, Journal of theoretical biology.

[11]  Lin Wang,et al.  Characterizing the dynamics underlying global spread of epidemics , 2018, Nature Communications.

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

[13]  Joshua M. Epstein,et al.  Controlling Pandemic Flu: The Value of International Air Travel Restrictions , 2007, PloS one.

[14]  Nan Chen,et al.  Bilevel Optimization Model for the Development of Real-Time Strategies to Minimize Epidemic Spreading Risk in Air Traffic Networks , 2016 .

[15]  Alessandro Vespignani,et al.  Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm , 2012, BMC Medicine.

[16]  Ashlynn R. Daughton,et al.  An approach to and web-based tool for infectious disease outbreak intervention analysis , 2017, Scientific Reports.

[17]  Yi Wang,et al.  Global analysis of an SIS model with an infective vector on complex networks , 2012 .

[18]  James Chirombo,et al.  Effectiveness of screening for Ebola at airports , 2015, The Lancet.

[19]  Alessandro Vespignani,et al.  The role of the airline transportation network in the prediction and predictability of global epidemics , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[20]  David Rey,et al.  Multiscale Network Model for Evaluating Global Outbreak Control Strategies , 2017 .

[21]  Alessandro Vespignani,et al.  Reaction–diffusion processes and metapopulation models in heterogeneous networks , 2007, cond-mat/0703129.

[22]  Alessandro Vespignani,et al.  Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic , 2011, PloS one.

[23]  T. Geisel,et al.  Forecast and control of epidemics in a globalized world. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Richard D. Smith.  Responding to global infectious disease outbreaks: Lessons from SARS on the role of risk perception, communication and management , 2006, Social Science & Medicine.

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

[26]  Linda A. Selvey,et al.  Evaluation of Border Entry Screening for Infectious Diseases in Humans , 2015, Emerging infectious diseases.

[27]  George J. Pappas,et al.  Analysis and Control of Epidemics: A Survey of Spreading Processes on Complex Networks , 2015, IEEE Control Systems.

[28]  Tom Britton,et al.  Epidemic modelling: aspects where stochasticity matters. , 2008, Mathematical biosciences.

[29]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[30]  Claudio Castellano,et al.  Thresholds for epidemic spreading in networks , 2010, Physical review letters.

[31]  Michael G. Baker,et al.  Screening for Influenza A(H1N1)pdm09, Auckland International Airport, New Zealand , 2012, Emerging infectious diseases.

[32]  J. H. Ellis,et al.  Modeling the Spread of Annual Influenza Epidemics in the U.S.: The Potential Role of Air Travel , 2004, Health care management science.

[33]  Cécile Viboud,et al.  Human mobility and the spatial transmission of influenza in the United States , 2017, PLoS Comput. Biol..

[34]  W. Edmunds,et al.  Delaying the International Spread of Pandemic Influenza , 2006, PLoS medicine.

[35]  A. Nizam,et al.  Containing Pandemic Influenza at the Source , 2005, Science.

[36]  D. Cummings,et al.  Strategies for containing an emerging influenza pandemic in Southeast Asia , 2005, Nature.

[37]  Sahotra Sarkar,et al.  Global risk of Zika virus depends critically on vector status of Aedes albopictus. , 2016, The Lancet. Infectious diseases.

[38]  Jacco Wallinga,et al.  A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. , 2008, Mathematical biosciences.

[39]  A. Fauci,et al.  The challenge of emerging and re-emerging infectious diseases , 2004, Nature.

[40]  Alessandro Vespignani,et al.  Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations. , 2007, Journal of theoretical biology.

[41]  Lin Wang,et al.  Spatial epidemiology of networked metapopulation: an overview , 2014, bioRxiv.

[42]  Claude Thibeault,et al.  Prevention of spread of communicable disease by air travel. , 2009, Aviation, space, and environmental medicine.

[43]  A. Flahault,et al.  Strategies for containing a global influenza pandemic. , 2006, Vaccine.

[44]  Paul Cosford.  Advantages of airport screening for Ebola , 2014, BMJ : British Medical Journal.

[45]  A Vespignani,et al.  Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic. , 2014, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[46]  D. Cummings,et al.  Strategies for mitigating an influenza pandemic , 2006, Nature.

[47]  Adam Warren,et al.  Airports, localities and disease: Representations of global travel during the H1N1 pandemic , 2010, Health & Place.

[48]  Wenguo Weng,et al.  Evaluation of containment and mitigation strategies for an influenza A pandemic in China , 2015, Simul..

[49]  Alain Barrat,et al.  Global disease spread: statistics and estimation of arrival times. , 2008, Journal of theoretical biology.

[50]  N. Ferguson,et al.  Will travel restrictions control the international spread of pandemic influenza? , 2006, Nature Medicine.

[51]  V. Isham,et al.  Modeling infectious disease dynamics in the complex landscape of global health , 2015, Science.

[52]  O. Bjørnstad,et al.  Chapter 17 , 2019 .

[53]  Alessandro Vespignani,et al.  Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions , 2007, PLoS medicine.

[54]  R. Mikolajczyk,et al.  Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases , 2008, PLoS medicine.

[55]  A. Lloyd,et al.  Nine challenges for deterministic epidemic models , 2014, Epidemics.

[56]  Cecile Viboud,et al.  Correction: Stochastic Processes Are Key Determinants of Short-Term Evolution in Influenza A Virus , 2006, PLoS Pathogens.

[57]  D. Gillen,et al.  Aviation security: Costing, pricing, finance and performance , 2015 .

[58]  I. Hanski.  Metapopulation dynamics , 1998, Nature.

[59]  Alessandro Vespignani,et al.  Multiscale mobility networks and the spatial spreading of infectious diseases , 2009, Proceedings of the National Academy of Sciences.

[60]  Alessandro Vespignani,et al.  Modeling the spatial spread of infectious diseases: The GLobal Epidemic and Mobility computational model , 2010, J. Comput. Sci..

[61]  M. Halloran,et al.  The Global Transmission and Control of Influenza , 2011, PloS one.