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Improving detection of outbreaks of illness or onset of seasonal changes (e.g. influenza) is an ongoing challenge for public health. New web-based interactive technology allows epidemiologists with experience in communicable disease control to interact with the data and fine tune the parameters for statistical algorithms to detect such temporal changes.
At Public Health Ontario, this methodology was applied to detect temporal changes in the rates of cyclosporiasis, giardiasis, and influenza (type A and type B). We tested this methodology using data from known outbreaks, using historical data to establish baseline disease rates. Regression models were used to model seasonality on historical data and a cumulative sum control chart was used to monitor the difference between observed and expected counts.
This presentation will discuss the steps taken in creating these algorithms as well as the comparisons of the algorithms to the traditional methods used at PHO.
Presenters: Dr. Ian Johnson, Lennon Li, Leigh Hobbs and Michael Whelan
Ian Johnson is a public health physician working as a scientific advisor at PHO.
Lennon Li has a PhD in biostatistics and works as a biostatistician at PHO.
Leigh Hobbs and Michael Whelan each have masters degrees in epidemiology and work as epidemiologists at PHO.
Public Health Ontario Grand Rounds are approved for continuing medical education from the Royal College of Physicians and Surgeons.
PHO Grand Rounds are also approved by Council of Professional Experience for professional development hours (PDHs) for members of the Canadian Institute of Public Health Inspectors (CIPHI).
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