From Basil_LOH@env.gov.sg Fri Jul 13 20:44:27 2001 Received: from mxu4.u.washington.edu (mxu4.u.washington.edu [140.142.33.8]) by lists.u.washington.edu (8.11.2+UW01.01/8.11.2+UW01.04) with ESMTP id f6E3iP014988 for ; Fri, 13 Jul 2001 20:44:25 -0700 Received: from mars.gems2.gov.sg (mars.gems2.gov.sg [160.96.65.1]) by mxu4.u.washington.edu (8.11.2+UW01.01/8.11.2+UW01.04) with ESMTP id f6E3iNs30666 for ; Fri, 13 Jul 2001 20:44:24 -0700 Received: from sehubm001.gems2.gov.sg ([10.235.129.12]) by mars.gems2.gov.sg (8.11.3/8.9.3) with ESMTP id f6E3jOp107456 for ; Sat, 14 Jul 2001 11:45:24 +0800 Subject: RE: Dengue & population To: waphgis@u.washington.edu X-Mailer: Lotus Notes Release 5.0.2b (Intl) 16 December 1999 Message-ID: From: Basil_LOH@env.gov.sg Date: Sat, 14 Jul 2001 11:45:08 +0800 X-MIMETrack: Serialize by Router on SEHUBM001/GOV/H/SINEXTRA(Release 5.0.6a |January 17, 2001) at 07/14/2001 11:43:13 AM MIME-Version: 1.0 Content-type: text/plain; charset=us-ascii Hi Richard, Thanks so much! I always appreciate your great helpfulness :) Yes, I remember you teaching us about SATScan last Oct. This will be a good time to apply it. I'm afraid I don't understand much about Poisson and Bernoulli modeeling though. But I will read up on it. Thanks again. Best wishes. Basil "Richard Hoskins" > cc: Sent by: Subject: RE: Dengue & population WAPHGIS-owner@u.wash ington.edu 14-07-2001 03:49 Please respond to waphgis Basil: I think one very effective way to get the information you need is to use a spatial scan statistic approach. Your data is made for it. You do not need to test the hypothesis of E vs W, and of course likely, there are more cases where there are more people - I suspect the mossies like areas where there is lots of food(people). I think you need to know where the rates are higher than anywhere else, if the idea is to deal with those areas first. Also it can tell you where areas are lower than expected and give an easy to understand way to determine if the rates are really elevated or not. The spatial scan statistic can be easily calculated. The background is http://www.sph.umich.edu/~lestberg/GeoMed/Scan/ScMain.htm http://sun2539.sph.umich.edu:2000/geomed/stats/kullscan/scan.html http://sun2539.sph.umich.edu:2000/geomed/stathelp/advisor.html http://dcp.nci.nih.gov/bb/SaTScan.html has free software and there is a commercial product now which does cluster calculations http://www.terraseer.com/clusterseer.html which has a whole lot of cluster tests bundled in one place. A link directly to ArcView http://www.phrl.org/REGS/Order.htm Dick Hoskins WA State Dept of Health -----Original Message----- From: WAPHGIS-owner@u.washington.edu [mailto:WAPHGIS-owner@u.washington.edu]On Behalf Of Basil_LOH@env.gov.sg Sent: Friday, July 13, 2001 1:36 AM To: waphgis@u.washington.edu; ai-geostats@unil.ch; fnpbb@diamond.mahidol.ac.th; getis@mail.sdsu.edu; owner-health-gis@who.ch Subject: Dengue & population Hi list members, I am new to geo/spatial statistics and I don't have any expert spatial epidemiologist in my country. So I thought I'd run through what I have done with you all, and check whether I am on the right track. If anyone has any better ideas, please feel free to let me know too! I am working on the following questions: How can I test the hypothesis that most of the dengue cases are located where most of the population are? How can I test the hypothesis that significantly more dengue cases are located in the east than in the west of my country? How can I detect if there are any clustering or any other spatial trends of dengue in relation to population? .