Interfering with influenza: nonlinear coupling of reactive and static mitigation strategies

When new, highly infectious strains of influenza emerge, global pandemics can occur before an effective vaccine is developed. Without a strain-specific vaccine, pandemics can only be mitigated by employing combinations of low-efficacy pre-pandemic vaccines and reactive response measures that are carried out as the pandemic unfolds. Unfortunately, the application of reactive interventions can lead to unintended consequences that may exacerbate unpredictable spreading dynamics and cause more drawn-out epidemics. Here, we employ a detailed model of pandemic influenza in Australia to simulate the combination of pre-pandemic vaccination and reactive antiviral prophylaxis. This study focuses on population-level coupling effects between the respective methods, and the associated spatio-temporal fluctuations in pandemic dynamics produced by reactive strategies. Our results show that combining strategies can produce either mutual improvement of performance or interference that reduces the effectiveness of each strategy when they are used together. We demonstrate that these coupling effects between intervention strategies are extremely sensitive to delay times, compliance rates and the type of contact targeting used to administer prophylaxis.

[1]  John M. Drake,et al.  Theory of early warning signals of disease emergenceand leading indicators of elimination , 2013, Theoretical Ecology.

[2]  J. McVernon,et al.  Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context , 2016, BMC Infectious Diseases.

[3]  Alessandro Vespignani,et al.  Phase transitions in contagion processes mediated by recurrent mobility patterns , 2011, Nature physics.

[4]  C. Macken,et al.  Mitigation strategies for pandemic influenza in the United States. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[5]  N. Andrews,et al.  Incidence of 2009 pandemic influenza A H1N1 infection in England: a cross-sectional serological study , 2010, The Lancet.

[6]  M. Newman Spread of epidemic disease on networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Alessandro Vespignani,et al.  Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models , 2010, BMC infectious diseases.

[8]  M. Keeling,et al.  Epidemiological consequences of household-based antiviral prophylaxis for pandemic influenza , 2013, Journal of The Royal Society Interface.

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

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

[11]  Mark A. Miller,et al.  Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza , 2006, Science.

[12]  J. McVernon,et al.  Modelling strategic use of the national antiviral stockpile during the CONTAIN and SUSTAIN phases of an Australian pandemic influenza response , 2010, Australian and New Zealand journal of public health.

[13]  Alex Arenas,et al.  Spreading Processes in Multiplex Metapopulations Containing Different Mobility Networks , 2018, Physical Review. X.

[14]  Mikhail Prokopenko,et al.  Phase Transitions in Spatial Connectivity during Influenza Pandemics , 2020, Entropy.

[15]  M. Prokopenko,et al.  Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks , 2013, PloS one.

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

[17]  V. Colizza,et al.  Metapopulation epidemic models with heterogeneous mixing and travel behaviour , 2014, Theoretical Biology and Medical Modelling.

[18]  Thomas D Szucs,et al.  Stockpiling prepandemic influenza vaccines: a new cornerstone of pandemic preparedness plans. , 2008, The Lancet. Infectious diseases.

[19]  Mikhail Prokopenko,et al.  Criticality and Information Dynamics in Epidemiological Models , 2017, Entropy.

[20]  S. Salmaso,et al.  Response to the 2009 influenza A(H1N1) pandemic in Italy. , 2010, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[21]  Matt J Keeling,et al.  Contact tracing and disease control , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[22]  Ken Eames,et al.  "Herd immunity": a rough guide. , 2011, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[23]  Dawei Zhao,et al.  Statistical physics of vaccination , 2016, ArXiv.

[24]  C. Bauch,et al.  Modelling mitigation strategies for pandemic (H1N1) 2009 , 2009, Canadian Medical Association Journal.

[25]  Mikhail Prokopenko,et al.  The Effects of Imitation Dynamics on Vaccination Behaviours in SIR-Network Model , 2019, International journal of environmental research and public health.

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

[27]  J. McVernon,et al.  Pandemic controllability: a concept to guide a proportionate and flexible operational response to future influenza pandemics , 2013, Journal of public health.

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

[29]  Reuven Cohen,et al.  Efficient immunization strategies for computer networks and populations. , 2002, Physical review letters.

[30]  Mikhail Prokopenko,et al.  Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model , 2018, Interface Focus.

[31]  Alessandro Vespignani,et al.  Measurability of the epidemic reproduction number in data-driven contact networks , 2018, Proceedings of the National Academy of Sciences.

[32]  Philip D. O'Neill,et al.  Mathematical Tools for Understanding Infectious Disease Dynamics by O. Diekmann, H. Heesterbeek and T. Britton Princeton University Press, pp. 516, ISBN 978-0-691-15539-5 , 2013 .

[33]  M. Lipsitch,et al.  The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis , 2009, PLoS medicine.

[34]  J. McVernon,et al.  Diagnosis and Antiviral Intervention Strategies for Mitigating an Influenza Epidemic , 2011, PloS one.

[35]  Mikhail Prokopenko,et al.  Investigating Spatiotemporal Dynamics and Synchrony of Influenza Epidemics in Australia: An Agent-Based Modelling Approach , 2018, Simul. Model. Pract. Theory.

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

[37]  Sandra Mounier-Jack,et al.  Pandemic influenza preparedness in the Asia–Pacific region , 2006, The Lancet.

[38]  Laura M. Glass,et al.  Targeted Social Distancing Designs for Pandemic Influenza , 2006, Emerging infectious diseases.

[39]  Jodie McVernon,et al.  Prophylaxis or treatment? Optimal use of an antiviral stockpile during an influenza pandemic. , 2007, Mathematical biosciences.

[40]  A. Fauci Seasonal and pandemic influenza preparedness: science and countermeasures. , 2006, The Journal of infectious diseases.

[41]  S. Nee,et al.  Imperfect vaccination: some epidemiological and evolutionary consequences , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[42]  Sigrún Andradóttir,et al.  Reactive strategies for containing developing outbreaks of pandemic influenza , 2011, BMC public health.

[43]  G. Milne,et al.  The Cost Effectiveness of Pandemic Influenza Interventions: A Pandemic Severity Based Analysis , 2013, PloS one.

[44]  Joel C. Miller Spread of infectious disease through clustered populations , 2008, Journal of The Royal Society Interface.

[45]  T. Déirdre Hollingsworth,et al.  Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives , 2011, PLoS Comput. Biol..

[46]  Oliver M. Cliff,et al.  Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model , 2018, Science Advances.

[47]  Julia E. Aledort,et al.  Non-pharmaceutical public health interventions for pandemic influenza: an evaluation of the evidence base , 2007, BMC public health.