Literature DB >> 32316882

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

Cameron Zachreson1, Kristopher M Fair1, Nathan Harding1, Mikhail Prokopenko1,2.   

Abstract

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.

Keywords:  agent-based model; antiviral prophylaxis; contact tracing; infectious disease; intervention; nonlinear dynamics

Mesh:

Substances:

Year:  2020        PMID: 32316882      PMCID: PMC7211476          DOI: 10.1098/rsif.2019.0728

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  40 in total

1.  Response to the 2009 influenza A(H1N1) pandemic in Italy.

Authors:  C Rizzo; M C Rota; A Bella; S Giannitelli; S De Santis; G Nacca; M G Pompa; L Vellucci; S Salmaso; S Declich
Journal:  Euro Surveill       Date:  2010-12-09

Review 2.  "Herd immunity": a rough guide.

Authors:  Paul Fine; Ken Eames; David L Heymann
Journal:  Clin Infect Dis       Date:  2011-04-01       Impact factor: 9.079

3.  Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model.

Authors:  Nathan Harding; Ramil Nigmatullin; Mikhail Prokopenko
Journal:  Interface Focus       Date:  2018-10-19       Impact factor: 3.906

4.  Modelling strategic use of the national antiviral stockpile during the CONTAIN and SUSTAIN phases of an Australian pandemic influenza response.

Authors:  Jodie McVernon; James M McCaw; Terence M Nolan
Journal:  Aust N Z J Public Health       Date:  2010-04       Impact factor: 2.939

5.  Spread of epidemic disease on networks.

Authors:  M E J Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-07-26

6.  Incidence of 2009 pandemic influenza A H1N1 infection in England: a cross-sectional serological study.

Authors:  Elizabeth Miller; Katja Hoschler; Pia Hardelid; Elaine Stanford; Nick Andrews; Maria Zambon
Journal:  Lancet       Date:  2010-01-21       Impact factor: 79.321

7.  Containing pandemic influenza with antiviral agents.

Authors:  Ira M Longini; M Elizabeth Halloran; Azhar Nizam; Yang Yang
Journal:  Am J Epidemiol       Date:  2004-04-01       Impact factor: 4.897

8.  Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

Authors:  Marco Ajelli; Bruno Gonçalves; Duygu Balcan; Vittoria Colizza; Hao Hu; José J Ramasco; Stefano Merler; Alessandro Vespignani
Journal:  BMC Infect Dis       Date:  2010-06-29       Impact factor: 3.090

9.  Diagnosis and antiviral intervention strategies for mitigating an influenza epidemic.

Authors:  Robert Moss; James M McCaw; Jodie McVernon
Journal:  PLoS One       Date:  2011-02-04       Impact factor: 3.240

10.  Mitigation strategies for pandemic influenza A: balancing conflicting policy objectives.

Authors:  T Déirdre Hollingsworth; Don Klinkenberg; Hans Heesterbeek; Roy M Anderson
Journal:  PLoS Comput Biol       Date:  2011-02-10       Impact factor: 4.475

View more
  5 in total

1.  Simulating Transmission Scenarios of the Delta Variant of SARS-CoV-2 in Australia.

Authors:  Sheryl L Chang; Oliver M Cliff; Cameron Zachreson; Mikhail Prokopenko
Journal:  Front Public Health       Date:  2022-02-24

2.  The effects of local homogeneity assumptions in metapopulation models of infectious disease.

Authors:  Cameron Zachreson; Sheryl Chang; Nathan Harding; Mikhail Prokopenko
Journal:  R Soc Open Sci       Date:  2022-07-13       Impact factor: 3.653

3.  Modelling transmission and control of the COVID-19 pandemic in Australia.

Authors:  Sheryl L Chang; Nathan Harding; Cameron Zachreson; Oliver M Cliff; Mikhail Prokopenko
Journal:  Nat Commun       Date:  2020-11-11       Impact factor: 14.919

4.  Modelling Excess Mortality in Covid-19-Like Epidemics.

Authors:  Zdzislaw Burda
Journal:  Entropy (Basel)       Date:  2020-10-30       Impact factor: 2.738

5.  How will mass-vaccination change COVID-19 lockdown requirements in Australia?

Authors:  Cameron Zachreson; Sheryl L Chang; Oliver M Cliff; Mikhail Prokopenko
Journal:  Lancet Reg Health West Pac       Date:  2021-07-30
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.