Literature DB >> 2117247

Guidelines for investigating clusters of health events.

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Abstract

Clusters of health events, such as chronic diseases, injuries, and birth defects, are often reported to health agencies. In many instances, the health agency will not be able to demonstrate an excess of the condition in question or establish an etiologic linkage to an exposure. Nevertheless, a systematic, integrated approach is needed for responding to reports of clusters. In addition to having epidemiologic and statistical expertise, health agencies should recognize the social dimensions of a cluster and should develop an approach for investigating clusters that best maintains critical community relationships and that does not excessively deplete resources. Health agencies should understand the potential legal ramifications of reported clusters, how risks are perceived by the community, and the influence of the media on that perception. Organizationally, each agency should have an internal management system to assure prompt attention to reports of clusters. Such a system requires the establishment of a locus of responsibility and control within the agency and of a process for involving concerned groups and citizens, such as an officially constituted advisory committee. Written operating procedures and dedicated resources may be of particular value. Although a systematic approach is vital, health agencies should be flexible in their method of analysis and tests of statistical significance. The recommended approach is a four-stage process: initial response, assessment, major feasibility study, and etiologic investigation. Each step provides opportunities for collecting data and making decisions. Although this approach may not always be followed sequentially, it provides a systematic plan with points at which the decision may be made to terminate or continue the investigation.

Entities:  

Mesh:

Year:  1990        PMID: 2117247

Source DB:  PubMed          Journal:  MMWR Recomm Rep        ISSN: 1057-5987


  14 in total

Review 1.  Investigation of clusters of adverse reproductive outcomes, an overview.

Authors:  P De Wals
Journal:  Eur J Epidemiol       Date:  1999-10       Impact factor: 8.082

2.  A method for the follow-up of clusters of adverse reproductive outcomes.

Authors:  T Niyonsenga; P De Wals
Journal:  Eur J Epidemiol       Date:  1999-10       Impact factor: 8.082

3.  Cluster morphology analysis.

Authors:  Geoffrey M Jacquez
Journal:  Spat Spatiotemporal Epidemiol       Date:  2009 Oct-Dec

4.  Heterogeneous geographic distribution of patients with aortic valve stenosis: arguments for new aetiological hypothesis.

Authors:  G Le Gal; V Bertault; E Bezon; J-C Cornily; J-A Barra; J-J Blanc
Journal:  Heart       Date:  2005-02       Impact factor: 5.994

5.  Improving the power of chronic disease surveillance by incorporating residential history.

Authors:  Justin Manjourides; Marcello Pagano
Journal:  Stat Med       Date:  2011-05-11       Impact factor: 2.373

6.  Use of insurance claims data to determine prevalence and confirm a cluster of sarcoidosis cases in Vermont.

Authors:  Lori A Cragin; A Scott Laney; Cortland J Lohff; Brennan Martin; John A Pandiani; Lynn Z Blevins
Journal:  Public Health Rep       Date:  2009 May-Jun       Impact factor: 2.792

7.  Epidemiology of necrotizing enterocolitis temporal clustering in two neonatology practices.

Authors:  Jareen Meinzen-Derr; Ardythe L Morrow; Richard W Hornung; Edward F Donovan; Kim N Dietrich; Paul A Succop
Journal:  J Pediatr       Date:  2008-12-25       Impact factor: 4.406

8.  Stop and listen to the people: an enhanced approach to cancer cluster investigations.

Authors:  Brian W Simpson; Patti Truant; Beth A Resnick
Journal:  Am J Public Health       Date:  2014-05-15       Impact factor: 9.308

Review 9.  Cancer clusters in the USA: what do the last twenty years of state and federal investigations tell us?

Authors:  Michael Goodman; Joshua S Naiman; Dina Goodman; Judy S LaKind
Journal:  Crit Rev Toxicol       Date:  2012-04-21       Impact factor: 5.635

10.  Visual analytics for epidemiologists: understanding the interactions between age, time, and disease with multi-panel graphs.

Authors:  Kenneth K H Chui; Julia B Wenger; Steven A Cohen; Elena N Naumova
Journal:  PLoS One       Date:  2011-02-15       Impact factor: 3.240

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