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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Space-time cluster detection techniques for infectious diseases: A systematic review.

Yu Lan1, Eric Delmelle2

  • 1Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.

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Summary

Geospatial technologies aid public health, but infectious disease surveillance needs better space-time clustering methods. Many studies use flawed approaches, risking false positives and limiting data sharing for replicability.

Keywords:
Cluster detectionInfectious disease surveillanceScan statisticsSpace-timeSpatial statistics

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Area of Science:

  • Epidemiology
  • Geographic Information Systems (GIS)

Background:

  • Public health increasingly uses geospatial technologies for disease surveillance and health promotion.
  • Space-time clustering is a key technique for understanding infectious disease patterns.

Approach:

  • A systematic review of 2,887 articles was conducted using PubMed, Web of Science, and Scopus.
  • 354 studies met inclusion criteria, focusing on infectious disease surveillance methods.

Key Points:

  • Airborne and vector-borne diseases dominated the research landscape.
  • Many studies employed aggregated data and repeated spatial methods, risking false positives.
  • Limited data availability in most studies hinders scientific replicability.

Conclusions:

  • The application of space-time clustering for infectious diseases has grown rapidly, especially during the COVID-19 pandemic.
  • There is a need for improved, "true" space-time detection approaches and greater data transparency in public health research.