Methodological problems and the role of statistics in cluster response studies: A framework View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-10

AUTHORS

P.K.M. Quataert, B. Armstrong, A. Berghold, F. Bianchi, A. Kelly, M. Marchi, M. Martuzzi, A. Rosano

ABSTRACT

More and more citizens urge public health authorities to investigate reports of disease excess in their neighbourhood. These environmental concerns are legitimate and it is part of good public health practice to respond to these complaints. However, the methodological and practical problems are severe and a lot of controversy exists about the usefulness of these investigations. To clarify the possibilities and limitations in this situation, this paper proposes a typology of cluster studies. According to this framework, cluster response is distinguished from two other types of cluster studies: Cluster monitoring, screening proactively for clusters to act as an early warning system, and cluster research, scrutinizing clustering to generate and test aetiological hypotheses. To each of these three types of cluster studies corresponds a different public health context; respectively public health action, public health surveillance and public health research. Probably, part of the controversy mentioned stems from not acknowledging sufficiently the corresponding intrinsic differences in rationality and practical constraints. Cluster response is crisis management and not scientific research. In a relatively short time, an informed decision should be taken by a multidisciplinary team of experts using readily available information and knowledge. In accordance with this point of view, cluster reports should be handled stepwise and the role of statistics is to quantify a cluster exploring different points of view as an input to the decision process. More... »

PAGES

821-831

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1007537813282

DOI

http://dx.doi.org/10.1023/a:1007537813282

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036654022

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/10608362


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