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Outbreaks source: A new mathematical approach to identify their possible location

Author

Listed:
  • Buscema, Massimo
  • Grossi, Enzo
  • Breda, Marco
  • Jefferson, Tom

Abstract

Classical epidemiology has generally relied on the description and explanation of the occurrence of infectious diseases in relation to time occurrence of events rather than to place of occurrence. In recent times, computer generated dot maps have facilitated the modeling of the spread of infectious epidemic diseases either with classical statistics approaches or with artificial “intelligent systems”. Few attempts, however, have been made so far to identify the origin of the epidemic spread rather than its evolution by mathematical topology methods.

Suggested Citation

  • Buscema, Massimo & Grossi, Enzo & Breda, Marco & Jefferson, Tom, 2009. "Outbreaks source: A new mathematical approach to identify their possible location," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4736-4762.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:22:p:4736-4762
    DOI: 10.1016/j.physa.2009.07.034
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    Citations

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    Cited by:

    1. Paolo Massimo Buscema & Guido Ferilli & Christer Gustafsson & Pier Luigi Sacco, 2020. "The Complex Dynamic Evolution of Cultural Vibrancy in the Region of Halland, Sweden," International Regional Science Review, , vol. 43(3), pages 159-202, May.
    2. Guido Ferilli & Pier Luigi Sacco & Massimo Buscema & Giorgio Tavano Blessi, 2015. "Understanding Cultural Geography as a Pseudo-Diffusion Process: The Case of the Veneto Region," Economies, MDPI, vol. 3(2), pages 1-28, June.
    3. Buscema, Massimo & Ferilli, Guido & Gustafsson, Christer & Massini, Giulia & Sacco, Pier Luigi, 2022. "A nonlinear, data-driven, ANNs-based approach to culture-led development policies in rural areas: The case of Gjakove and Peć districts, Western Kosovo," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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