832Detecting spatial clusters of human salmonellosis in Victoria

Abstract

Abstract Focus of Presentation ‘Cluster Tracker’ is an automated tool for spatial cluster detection of notifiable disease data collected by the Department of Health (DH), Victoria. The tool combines R statistical software and a SaTScan cluster detection algorithm (prospective space-time permutation scan statistic) to detect notifiable disease case clusters in Victoria and is presently implemented for salmonellosis (categorised by type and/or MLVA). The objective of the tool is to conduct an initial screening of case data to improve the prioritisation of salmonellosis cases for epidemiological investigation. Findings The Cluster Tracker tool parameters have been validated using historical data from 2017-2018, comparing DH outbreak and cluster investigations identified by usual surveillance activities with clusters detected by the Cluster Tracker tool. Parameter selection considered cluster detection agreement and disagreement, disease-specific epidemiological characteristics, and operational requirements. The Cluster Tracker tool was able to provide closely-aligned agreement with existing DH outbreak and cluster investigations using the validated parameters. Implications This automated spatial cluster detection tool complements existing desktop surveillance of salmonellosis notifications to enhance public health decision making, and serves as an example of how spatial methods can improve real-time surveillance. Key messages Advanced spatial statistical tools have a role alongside traditional methods to make better use of limited epidemiological capacity and improve the timeliness and prioritisation of surveillance activities for notifiable diseases.