Advertisement

The European Physical Journal Special Topics

, Volume 226, Issue 9, pp 1845–1856 | Cite as

Climate impact on spreading of airborne infectious diseases

Complex network based modeling of climate influences on influenza like illnesses
  • Frank Brenner
  • Norbert Marwan
  • Peter Hoffmann
Regular Article
Part of the following topical collections:
  1. Recent Advances in Nonlinear Dynamics and Complex Structures: Fundamentals and Applications

Abstract

In this study we combined a wide range of data sets to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human. The basis is a complex network whose structures are inspired by global air traffic data (from openflights.org) containing information about airports, airport locations, direct flight connections and airplane types. Disease spreading inside every node is realized with a Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. Disease transmission rates in our model are depending on the climate environment and therefore vary in time and from node to node. To implement the correlation between water vapor pressure and influenza transmission rate [J. Shaman, M. Kohn, Proc. Natl. Acad. Sci. 106, 3243 (2009)], we use global available climate reanalysis data (WATCH-Forcing-Data-ERA-Interim, WFDEI). During our sensitivity analysis we found that disease spreading dynamics are strongly depending on network properties, the climatic environment of the epidemic outbreak location, and the season during the year in which the outbreak is happening.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    J. Shaman, M. Kohn, Proc. Natl. Acad. Sci. 106, 3243 (2009)ADSCrossRefGoogle Scholar
  2. 2.
    N. Zhong, B. Zheng, Y. Li, L. Poon, Z. Xie, K. Chan, P. Li, S. Tan, Q. Chang, J. Xie, et al., The Lancet 362, 1353 (2003)CrossRefGoogle Scholar
  3. 3.
    J.G. Breugelmans, P. Zucs, K. Porten, S. Broll, M. Niedrig, A. Ammon, G. Krause, Emerging Infectious Diseases 10, 1502 (2004)CrossRefGoogle Scholar
  4. 4.
    G.J. Smith, D. Vijaykrishna, J. Bahl, S.J. Lycett, M. Worobey, O.G. Pybus, S.K. Ma, C.L. Cheung, J. Raghwani, S. Bhatt, et al., Nature 459, 1122 (2009)ADSCrossRefGoogle Scholar
  5. 5.
    G. Neumann, T. Noda, Y. Kawaoka, Nature 459, 931 (2009)ADSCrossRefGoogle Scholar
  6. 6.
    A. Mangili, M.A. Gendreau, The Lancet 365, 989 (2005)CrossRefGoogle Scholar
  7. 7.
    D. Balcan, V. Colizza, B. Gonçalves, H. Hu, J.J. Ramasco, A. Vespignani, Proc. Natl. Acad. Sci. 106, 21484 (2009)ADSCrossRefGoogle Scholar
  8. 8.
    J.A. Patz, P.R. Epstein, T.A. Burke, J.M. Balbus, Jama 275, 217 (1996)CrossRefGoogle Scholar
  9. 9.
    K.D. Lafferty, Ecology 90, 888 (2009)CrossRefGoogle Scholar
  10. 10.
    A. Trilla, G. Trilla, C. Daer, Clinical infectious diseases 47, 668 (2008)CrossRefGoogle Scholar
  11. 11.
    WHO Influenza, fact sheet n211. http://www.who.int/mediacentre/factsheets/2003/fs211/en/. Accessed: 2017-20
  12. 12.
    A.I. Barreca, J.P. Shimshack, Am. J. Epidemiol. 176, S114 (2012)CrossRefGoogle Scholar
  13. 13.
    C. Fuhrmann, Geography Compass 4, 718 (2010)CrossRefGoogle Scholar
  14. 14.
    A.C. Lowen, S. Mubareka, J. Steel, P. Palese, PLoS Pathogens 3, e151 (2007)CrossRefGoogle Scholar
  15. 15.
    S.F. Dowell, Emerging infectious diseases 7, 369 (2001)CrossRefGoogle Scholar
  16. 16.
    B.A. Walther, P.W. Ewald, Biol. Rev. 79, 849 (2004)CrossRefGoogle Scholar
  17. 17.
    E. Lofgren, N.H. Fefferman, Y.N. Naumov, J. Gorski, E.N. Naumova, J. Virol. 81, 5429 (2007)CrossRefGoogle Scholar
  18. 18.
    R. Guimera, S. Mossa, A. Turtschi, L.N. Amaral, Proc. Natl. Acad. Sci. 102, 7794 (2005)ADSCrossRefGoogle Scholar
  19. 19.
    M.J. Keeling, P. Rohani, Modeling infectious diseases in humans and animals (Princeton University Press, 2008)Google Scholar
  20. 20.
    L. Allen, F. Brauer, P. Van den Driessche, J. Wu, Lecture Notes in Mathematics 1945, 81 (2008)CrossRefGoogle Scholar
  21. 21.
    R. Pastor-Satorras, A. Vespignani, Phys. Rev. Lett. 86, 3200 (2001)ADSCrossRefGoogle Scholar
  22. 22.
    D. Brockmann, D. Helbing, Science 342, 1337 (2013)ADSCrossRefGoogle Scholar
  23. 23.
    F. Schaffer, M. Soergel, D. Straube, Arch. Virol. 51, 263 (1976)CrossRefGoogle Scholar
  24. 24.
    G. Harper, J. Hygiene 59, 479 (1961)CrossRefGoogle Scholar
  25. 25.
    R. Williams, N. Rankin, T. Smith, D. Galler, P. Seakins, Critical care medicine 24, 1920 (1996)CrossRefGoogle Scholar
  26. 26.
    K. Engvall, P. Wickman, D. Norbäck, Indoor air 15, 120 (2005)CrossRefGoogle Scholar
  27. 27.
    E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, et al., Bull. Amer. Meteorol. Soc. 77, 437 (1996)ADSCrossRefGoogle Scholar
  28. 28.
    G.P. Weedon, G. Balsamo, N. Bellouin, S. Gomes, M.J. Best, P. Viterbo, Water Resou. Res. 50, 7505 (2014)ADSCrossRefGoogle Scholar
  29. 29.
    C. Viboud, W.J. Alonso, L. Simonsen, PLoS Med. 3, e89 (2006)CrossRefGoogle Scholar
  30. 30.
    S. Prachayangprecha, P. Vichaiwattana, S. Korkong, J.A. Felber, Y. Poovorawan, SpringerPlus 4, 356 (2015)CrossRefGoogle Scholar

Copyright information

© EDP Sciences and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Potsdam Institute for Climate Impact ResearchPotsdamGermany

Personalised recommendations