Literature DB >> 9132900

Surveillance of clustering near point sources.

N D Le1, A J Petkau, R Rosychuk.   

Abstract

Health authorities are often alerted to suspected cancer clusters near the vicinity of potential point sources by members of the public. A surveillance system, where administrative regions around the potential point sources are regularly monitored for high disease rates, would allow for responses which are easier to obtain, timelier, and less expensive than individual thorough investigations. The monitoring could be done by using the so-called 'focused' tests for detecting disease clustering. However, these tests, generally designed to detect clusters of a fixed size around the foci, are not particularly effective when dealing with administrative regions with substantial differences in populations. In this work, an approach which overcomes the problem to a certain extent is described. Here the selected cluster sizes are based on the populations of the administrative regions under examination. The approach is used to investigate whether cancer clustering appears in the vicinity of the pulp and paper mills in British Columbia for the years 1983-1989. The results indicate that the approach performs reasonably well in identifying cancer sites for which elevated risks have also been suggested in the epidemiologic literature. Consequently, this methodology could be utilized to provide guidance for further investigation even in the absence of local reports. Similarly, it could be readily utilized to provide timely responses to local reports.

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Year:  1996        PMID: 9132900     DOI: 10.1002/(sici)1097-0258(19960415)15:7/9<727::aid-sim244>3.0.co;2-x

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  5 in total

1.  Central nervous system (CNS) tumor trends in children in a western Canadian province: a population-based 22-year retrospective study.

Authors:  Rhonda J Rosychuk; Adrienne Witol; Bev Wilson; Kent Stobart
Journal:  J Neurol       Date:  2011-11-23       Impact factor: 4.849

2.  An exact test to detect geographic aggregations of events.

Authors:  Rhonda J Rosychuk; Jason L Stuber
Journal:  Int J Health Geogr       Date:  2010-06-07       Impact factor: 3.918

3.  Identifying geographic areas with high disease rates: when do confidence intervals for rates and a disease cluster detection method agree?

Authors:  Rhonda J Rosychuk
Journal:  Int J Health Geogr       Date:  2006-10-18       Impact factor: 3.918

4.  Spatio-temporal effects of estimated pollutants released from an industrial estate on the occurrence of respiratory disease in Maptaphut Municipality, Thailand.

Authors:  Somchai Jadsri; Pratap Singhasivanon; Jaranit Kaewkungwal; Rattana Sithiprasasna; Somkiat Siriruttanapruk; Supawadee Konchom
Journal:  Int J Health Geogr       Date:  2006-11-08       Impact factor: 3.918

5.  Spatial event cluster detection using an approximate normal distribution.

Authors:  Mahmoud Torabi; Rhonda J Rosychuk
Journal:  Int J Health Geogr       Date:  2008-12-12       Impact factor: 3.918

  5 in total

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