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Epidemics Modeling by Spatiotemporal Constraint Data

  • Living reference work entry
  • First Online:
Encyclopedia of GIS

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Synonyms

Epidemics; Infectious diseases; Moving objects; Spatio-temporal data

Historical Background

Infectious disease outbreaks are critical threats to public health and national security (Damianos et al., 2002; Hufnagel et al., 2004). With greatly expanded travel and trade, infectious diseases can quickly spread across large areas causing major epidemics. Efficient computerized reasoning about epidemics is essential to detect their outbreak and nature, to provide fast medical aid to affected people and animals, and to prevent their further spread.

Epidemiological data are spatiotemporal data, that is, they have a spatial distribution that changes over time (Clements and Pfeiffer, 2009; Ozdenerol et al., 2013; Sintchenko and Gallego, 2009). Epidemiological data are also recursive in nature. That means that the best predictions of the spread of infections are based on earlier situations. These characteristics of epidemics make them special in terms of geographic information systems,...

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA

    Peter Z Revesz

  2. Department of Mathematics, Computer Science and Physics, Spring Arbor University, Spring Arbor, MI, USA

    Shasha Wu

Authors
  1. Peter Z Revesz
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  2. Shasha Wu
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Corresponding author

Correspondence to Peter Z Revesz .

Editor information

Editors and Affiliations

  1. Minneapolis, Minnesota, USA

    Shashi Shekhar

  2. Rutgers Business School, Newark, New Jersey, USA

    Hui Xiong

  3. The University of Iowa Tippie College of Business, Iowa City, Iowa, USA

    Xun Zhou

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© 2016 Springer International Publishing Switzerland

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Revesz, P.Z., Wu, S. (2016). Epidemics Modeling by Spatiotemporal Constraint Data. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-23519-6_1611-1

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  • DOI: https://doi.org/10.1007/978-3-319-23519-6_1611-1

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  • Publisher Name: Springer, Cham

  • Online ISBN: 978-3-319-23519-6

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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