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Prospective space–time surveillance with cumulative surfaces for geographical identification of the emerging cluster

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  • Thais Paiva
  • Renato Assunção
  • Taynãna Simões

Abstract

We developed a space–time prospective surveillance method when the data are point events, monitoring if there is an emerging cluster. Typical application areas are crime or disease surveillance. At each new event, a local Knox score is calculated and spatially spread to form a stochastic surface. The surfaces are accumulated sequentially until they exceed a specified threshold, causing an alarm to go off and identify the region of the probable cluster. The method requires little prior knowledge from the user and provides a way to identify locations and time of possible clusters, through the visualization of the cumulative surface. We present a simulation study for different cluster scenarios, as well as an application to a dataset of meningitis cases in Belo Horizonte, Brazil. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Thais Paiva & Renato Assunção & Taynãna Simões, 2015. "Prospective space–time surveillance with cumulative surfaces for geographical identification of the emerging cluster," Computational Statistics, Springer, vol. 30(2), pages 419-440, June.
    • Handle: RePEc:spr:compst:v:30:y:2015:i:2:p:419-440
    DOI: 10.1007/s00180-014-0541-y
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    References listed on IDEAS

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    1. William H. Woodall & J Brooke Marshall & Michael D. Joner Jr & Shannon E Fraker & Abdel‐Salam G Abdel‐Salam, 2008. "On the use and evaluation of prospective scan methods for health‐related surveillance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 223-237, January.
    2. Christian Sonesson & David Bock, 2003. "A review and discussion of prospective statistical surveillance in public health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 5-21, February.
    3. Peter A. Rogerson, 2001. "Monitoring point patterns for the development of space–time clusters," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 87-96.
    4. Steffen Unkel & C. Paddy Farrington & Paul H. Garthwaite & Chris Robertson & Nick Andrews, 2012. "Statistical methods for the prospective detection of infectious disease outbreaks: a review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(1), pages 49-82, January.
    5. Martin Kulldorff & Ulf Hjalmars, 1999. "The Knox Method and Other Tests for Space-Time Interaction," Biometrics, The International Biometric Society, vol. 55(2), pages 544-552, June.
    6. Martin Kulldorff, 2001. "Prospective time periodic geographical disease surveillance using a scan statistic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 61-72.
    7. Assuno, Renato & Correa, Thais, 2009. "Surveillance to detect emerging space-time clusters," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2817-2830, June.
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