Interrupted time series segmented regression analysis for detecting waterborne disease outbreaks by syndromic surveillance
- 28 February 2023
- journal article
- research article
- Published by Australian Government Department of Health and Aged Care in Communicable Diseases Intelligence
Abstract
IntroductionPathogens can enter the drinking water supply and cause gastroenteritis outbreaks. Such events can affect many people in a short time, making them a high risk for public health. In Australia, the Victoria State Government Department of Health is deploying a syndromic surveillance system for drinking water contamination events. We assessed the utility of segmented regression models for detecting such events and determined the number of excess presentations needed for such methods to signal a detection. MethodsThe study involved an interrupted time series study of a past lapse in water treatment. The baseline period comprised the four weeks before the minimum incubation period of suspected pathogens, set at two days post-event. The surveillance period comprised the week after. We used segmented linear regression to compare the count of gastroenteritis presentations to public hospital emergency departments (EDs) between the surveillance and baseline periods. We then simulated events result-ing in varying excess presentations. These were superimposed onto the ED data over fifty different dates across 2020. Using the same regression, we calculated the detection probability at p < 0.05 for each outbreak size.ResultsIn the retrospective analysis, there was strong evidence for an increase in presentations shortly after the event. In the simulations, with no excess presentations (i.e., with the ED data as is) the models signalled 8% probability of detection. The models returned 50% probability of detection with 28 excess presentations and 100% probability of detection with 78 excess presentations.ConclusionsThe transient increase in presentations after the event may be attributed to microbiological hazards or increased health-seeking behaviour following the issuing of boil water advisories. The simulations demonstrated the ability for segmented regressions to signal a detection, even without a large excess in presentations. The approach also demonstrated high specificity and should be considered for informing Victoria's syndromic surveillance system.Keywords
This publication has 16 references indexed in Scilit:
- Waterborne Disease Outbreak Detection: A Simulation-Based StudyInternational Journal of Environmental Research and Public Health, 2018
- ICARES: a real-time automated detection tool for clusters of infectious diseases in the NetherlandsBMC Infectious Diseases, 2017
- A Study of Failure Events in Drinking Water Systems as a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse SchemesEnvironmental Health Insights, 2015
- Drug sales data analysis for outbreak detection of infectious diseases: a systematic literature reviewBMC Infectious Diseases, 2014
- Public health and pipe breaks in water distribution systems: Analysis with internet search volume as a proxyWater Research, 2014
- Syndromic surveillance for local outbreak detection and awareness: evaluating outbreak signals of acute gastroenteritis in telephone triage, web-based queries and over-the-counter pharmacy salesEpidemiology and Infection, 2013
- The remarkable adaptability of syndromic surveillance to meet public health needsJournal of Epidemiology and Global Health, 2013
- Reported waterborne outbreaks of gastrointestinal disease in Australia are predominantly associated with recreational exposureAustralian and New Zealand Journal of Public Health, 2010
- Review of syndromic surveillance: implications for waterborne disease detectionJournal of Epidemiology and Community Health, 2006
- A large community outbreak of waterborne giardiasis- delayed detection in a non-endemic urban areaBMC Public Health, 2006