From lwaller@sph.emory.edu Mon Oct 22 06:33:13 2001 Received: from mailscan2.cac.washington.edu (mailscan2.cac.washington.edu [140.142.33.16]) by lists.u.washington.edu (8.11.6+UW01.08/8.11.6+UW01.08) with SMTP id f9MDXCN84384 for ; Mon, 22 Oct 2001 06:33:12 -0700 Received: FROM mxu1.u.washington.edu BY mailscan2.cac.washington.edu ; Mon Oct 22 06:33:12 2001 -0700 Received: from gator.sph.emory.edu (root@gator.sph.emory.edu [170.140.4.2]) by mxu1.u.washington.edu (8.11.6+UW01.08/8.11.6+UW01.08) with ESMTP id f9MDXBw17354 for ; Mon, 22 Oct 2001 06:33:11 -0700 Received: from viper.sph.emory.edu (root@viper.sph.emory.edu [170.140.4.1]) by gator.sph.emory.edu (8.12.1/8.12.1) with ESMTP id f9MDX8Hb010205 for ; Mon, 22 Oct 2001 09:33:09 -0400 (EDT) Received: from sph.emory.edu (sph142.sph.emory.edu [170.140.5.31]) by viper.sph.emory.edu (8.12.1/8.12.1) with ESMTP id f9MDX6j8016259 for ; Mon, 22 Oct 2001 09:33:06 -0400 (EDT) Message-ID: <3BD42112.4A06EFA6@sph.emory.edu> Date: Mon, 22 Oct 2001 09:37:22 -0400 From: Lance Waller X-Mailer: Mozilla 4.73 [en] (Win98; U) X-Accept-Language: en MIME-Version: 1.0 To: waphgis@u.washington.edu Subject: Re: Spatial-temporal clustering by chance References: Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Basil: Given that you have definitions of a critical distance in space (200m) and a critical distance in time (3 weeks), you could apply the Knox test (sort of the "classic" for this situation). Diggle et al. (1995) provide a more flexible version using K-functions (requiring more involved computation). A few notes on the Knox test: - In the discussion of the Knox paper, M.S. Bartlett offers an insightful comment regarding testing for space-time clusters: "Of course, even when one has demonstrated the existence of an interaction (read 'cluster'), say by some such method as he (Knox) suggests, one has, as I remarked at the meeting, to be on one's guard against spurious effects, such as the detection of one case leading to greater efforts, perhaps by a particular doctor, to find further cases in the same locality." - The Knox test has an implicit assumption of a constant population at risk, a feature explored and discussed in detail (along with other space-time tests) by Kulldorff and Hjalmars (1999) Hope this helps, Lance References: Knox, E.G. (1964) The detection of space-time interactions. (with discussion). Applied Statistics, 13, 25-30. Barlett, M.S. (1964) Discussion of Knox. Applied Statistics, 13, 30. Kulldorff, M., and Hjalmars, U. (1999) The Knox method and other tests for space-time interactions. Biometrics 55, 544-552. Diggle, P.J., Chetwynd, A.G, Haggkvist, R., and Morris, S.E. (1995) Second-order analysis of space-time clustering. Statistical Methods in Medical Research 4, 124-136. Basil_LOH@env.gov.sg 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). > > Will sum answers. > > Thanks for your attention. Cheers. > > Basil .