ArticleFrontiers in public health2024
Comparing circular and flexibly-shaped scan statistics for disease clustering detection.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Detection of Acute Hepatitis C Outbreaks in California Using SaTScan: Statewide Spatiotemporal Analysis.JMIR public health and surveillance · 2026Article
- Integrating disease mapping and flexible scan statistics to identify and visualize spatial clusters.PloS one · 2026Article
- Spatiotemporal distribution and detection of spatial clusters of tuberculosis in Hubei Province, China using FleXScan (2017-2023).BMC public health · 2025Article
- From infectious diseases to chronic diseases: the paradigm shift of spatial epidemiology in disease prevention and control.Frontiers in public health · 2025Review
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6 authors.
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Abstract
The accuracy of spatial clustering detection is crucial for public health policy development and identifying etiological clues. Circular and flexibly-shaped scan statistics are widely used for disease cluster detection, but differences in results arise mainly due to parameter sensitivity and variations in the scanning window shapes. This study aims to analyze the impact of parameter settings on the results of these methods and compare their performance in disease clustering detection. Using tuberculosis data from Wuhan, China (2015-2019), the study identified the optimal parameter settings-MSWS and
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