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GeoSurveillance: a GIS-based system for the detection and monitoring of spatial clusters

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  • Ikuho Yamada
  • Peter Rogerson
  • Gyoungju Lee

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  • Ikuho Yamada & Peter Rogerson & Gyoungju Lee, 2009. "GeoSurveillance: a GIS-based system for the detection and monitoring of spatial clusters," Journal of Geographical Systems, Springer, vol. 11(2), pages 155-173, June.
    • Handle: RePEc:kap:jgeosy:v:11:y:2009:i:2:p:155-173
    DOI: 10.1007/s10109-009-0080-1
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    References listed on IDEAS

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    1. O'Campo, P. & Xue, X. & Wang, M.-C. & Brien Caughy, M.O., 1997. "Neighborhood risk factors for low birthweight in Baltimore: A multilevel analysis," American Journal of Public Health, American Public Health Association, vol. 87(7), pages 1113-1118.
    2. Eisner, V. & Brazie, J.V. & Pratt, M.W. & Hexter, A.C., 1979. "The risk of low birthweight," American Journal of Public Health, American Public Health Association, vol. 69(9), pages 887-893.
    3. Roberts, E.M., 1997. "Neighborhood social environments and the distribution of low birthweight in Chicago," American Journal of Public Health, American Public Health Association, vol. 87(4), pages 597-603.
    4. Julian Besag & James Newell, 1991. "The Detection of Clusters in Rare Diseases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(1), pages 143-155, January.
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    Cited by:

    1. Juan Duque & Jared Aldstadt & Ermilson Velasquez & Jose Franco & Alejandro Betancourt, 2011. "A computationally efficient method for delineating irregularly shaped spatial clusters," Journal of Geographical Systems, Springer, vol. 13(4), pages 355-372, December.
    2. Harper, Michael & Anderson, Ben & James, Patrick A.B. & Bahaj, AbuBakr S., 2019. "Onshore wind and the likelihood of planning acceptance: Learning from a Great Britain context," Energy Policy, Elsevier, vol. 128(C), pages 954-966.
    3. Chris Brunsdon & Martin Charlton, 2011. "An Assessment of the Effectiveness of Multiple Hypothesis Testing for Geographical Anomaly Detection," Environment and Planning B, , vol. 38(2), pages 216-230, April.
    4. M. R. Martines & R. V. Ferreira & R. H. Toppa & L. M. Assunção & M. R. Desjardins & E. M. Delmelle, 2021. "Detecting space–time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities," Journal of Geographical Systems, Springer, vol. 23(1), pages 7-36, January.

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