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AI-GEOSTATS: Spatial-temporal clustering by chance

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  • Basil_LOH@ENV.gov.sg
    Hi everyone, In Singapore, we define a dengue cluster (referring to an outbreak when dengue fever is spreading contagiously from one person to the next) as at
    Message 1 of 2 , Oct 21, 2001
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      Hi everyone,

      In Singapore, we define a dengue cluster (referring to an outbreak when
      dengue fever is spreading contagiously from one person to the next) as at
      least 2 cases (points) within 200 m of each other and within 3 weeks of
      incidence of each other. With about 2,000 cases so far this year, I have
      about about 80 clusters according to this definition.

      However, I suspect that the occurence of some clusters (especially the ones
      with just 2 or 3 cases) may be by chance, instead of an actual disease
      transmission happening. How can I test this? Possibly, a Monte Carlo
      simulation of some kind will help. Is there any software out there that can
      help to do this? SATScan has got some promising functions, unfortunately it
      deals with areal or polygon data and not point data (I think).

      Will sum answers.

      Thanks for your attention. Cheers.

      Basil


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    • Roger Bivand
      (I have only CC ed to AI-GEOSTATS, not being subscribed to the other lists) ... One possibility are the stkhat family of functions in Splancs, including
      Message 2 of 2 , Oct 21, 2001
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        (I have only CC'ed to AI-GEOSTATS, not being subscribed to the other
        lists)

        On Mon, 22 Oct 2001 Basil_LOH@... wrote:

        > Hi everyone,
        >
        > In Singapore, we define a dengue cluster (referring to an outbreak when
        > dengue fever is spreading contagiously from one person to the next) as at
        > least 2 cases (points) within 200 m of each other and within 3 weeks of
        > incidence of each other. With about 2,000 cases so far this year, I have
        > about about 80 clusters according to this definition.
        >
        > However, I suspect that the occurence of some clusters (especially the ones
        > with just 2 or 3 cases) may be by chance, instead of an actual disease
        > transmission happening. How can I test this? Possibly, a Monte Carlo
        > simulation of some kind will help. Is there any software out there that can
        > help to do this? SATScan has got some promising functions, unfortunately it
        > deals with areal or polygon data and not point data (I think).
        >
        One possibility are the stkhat family of functions in Splancs, including
        stmctest - a Monte-Carlo test of space-time clustering, see: Diggle, P.,
        Chetwynd, A., Haggkvist, R. and Morris, S. 1995 Second-order analysis of
        space-time clustering. Statistical Methods in Medical Research, 4,
        124-136.

        Software to run this in R (www.r-project.org) is contributed as a package
        to be found on the same site (maintained by me), in S-PLUS at the original
        site: http://www.maths.lancs.ac.uk/~rowlings/Splancs/. The article is not
        very easy to get at, a further short description can be found in: Bailey,
        T. C. and Gatrell, A. C. 1995, Interactive spatial data analysis. Longman,
        Harlow, pp. 122-125.

        A student from Thailand (Wutjanun Muttitanon <nungeog@...>) also
        drew my attention to an article I think using stkhat: Exploratory
        space-time analysis of reported dengue cases during an outbreak in
        Florida,Puerto Rico,1991-1992 Author : Amy C.Morrison and et al. Journal :
        American Tropical Hygine ,Vol 58(3) pp287-298.

        If you follow up this route using the splancs package for R, I'd be very
        grateful for feedback to help improve its documentation and functionality.

        Roger

        --
        Roger Bivand
        Economic Geography Section, Department of Economics, Norwegian School of
        Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
        Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
        e-mail: Roger.Bivand@...
        and: Department of Geography and Regional Development, University of
        Gdansk, al. Mar. J. Pilsudskiego 46, PL-81 378 Gdynia, Poland.




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