Literature DB >> 16845909

Monitoring changes in spatio-temporal maps of disease.

Carmen L Vidal Rodeiro1, Andrew B Lawson.   

Abstract

The object of statistical surveillance is to detect a change in a process accurately and quickly as new observations keep adding to the observed part of the process. In this paper we discuss methodological issues in developing a rapid response in a spatial surveillance system. Simple exploratory statistical methods together with more sophisticated methods, based on hierarchical space-time models defined at small area level, are considered.

Mesh:

Year:  2006        PMID: 16845909     DOI: 10.1002/bimj.200510176

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  7 in total

1.  Prospective surveillance of multivariate spatial disease data.

Authors:  A Corberán-Vallet
Journal:  Stat Methods Med Res       Date:  2012-04-25       Impact factor: 3.021

2.  Conditional predictive inference for online surveillance of spatial disease incidence.

Authors:  Ana Corberán-Vallet; Andrew B Lawson
Journal:  Stat Med       Date:  2011-09-05       Impact factor: 2.373

Review 3.  Review of software for space-time disease surveillance.

Authors:  Colin Robertson; Trisalyn A Nelson
Journal:  Int J Health Geogr       Date:  2010-03-12       Impact factor: 3.918

Review 4.  Review of methods for space-time disease surveillance.

Authors:  Colin Robertson; Trisalyn A Nelson; Ying C MacNab; Andrew B Lawson
Journal:  Spat Spatiotemporal Epidemiol       Date:  2010-02-20

5.  Proof of concept of a method that assesses the spread of microbial infections with spatially explicit and non-spatially explicit data.

Authors:  Ariel L Rivas; Kevin L Anderson; Roberta Lyman; Stephen D Smith; Steven J Schwager
Journal:  Int J Health Geogr       Date:  2008-11-18       Impact factor: 3.918

6.  Geographic variation in the intended choice of adjuvant treatments for women diagnosed with screen-detected breast cancer in Queensland.

Authors:  Jeff Ching-Fu Hsieh; Susanna M Cramb; James M McGree; Nathan A M Dunn; Peter D Baade; Kerrie L Mengersen
Journal:  BMC Public Health       Date:  2015-12-02       Impact factor: 3.295

7.  Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location.

Authors:  Jeff Ching-Fu Hsieh; Susanna M Cramb; James M McGree; Nathan A M Dunn; Peter D Baade; Kerrie L Mengersen
Journal:  PLoS One       Date:  2016-05-05       Impact factor: 3.240

  7 in total

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