Disease cluster detection methods: recent developments and public health implications

Research output: Contribution to journalArticle

Abstract

Methods for detecting spatial and spatiotemporal clusters of health and disease have advanced significantly in the past decade. This article reviews recent advances in four areas: spatial search processes, network-based methods, statistical analysis and modelling of local clusters and space-time cluster detection. I then turn to a more critical discussion of the implications of hotspot mapping for public health policy and intervention, highlighting the need to incorporate process-based understandings that impact spatial and social inequalities in ill health for particular health issues in particular geographic contexts.

Original languageEnglish (US)
Pages (from-to)127-133
Number of pages7
JournalAnnals of GIS
Volume21
Issue number2
DOIs
StatePublished - Apr 3 2015

Keywords

  • public health
  • space-time
  • spatial cluster detection

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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