Augmenting surveillance to minimize the burden of norovirus-like illness in Ontario: using telehealth data to detect the onset of community activity

Abstract

This thesis sets out to describe the essential elements required in the creation of a syndromic surveillance system for human infectious disease. Using this information, this thesis also presents a novel early warning syndromic surveillance system for the winter norovirus season in the province of Ontario, Canada. Telehealth data were utilized as the source of syndromic data alongside laboratory data to confirm the onset of the winter norovirus season. Syndromic methods were selected for this novel surveillance system because they can predict disease outbreaks earlier than laboratory and other traditional surveillance methods and cover a wider scope of the population. Norovirus outbreaks benefit from such methods due to the increased coverage of disease in communities, which often go unreported. A scoping review was performed to describe the current state of research of the creation of syndromic surveillance systems for human infectious disease. A narrative synthesis built upon the scoping review to describe in detail all of the essential elements required in the creation of a syndromic surveillance system for human infectious disease. Descriptive analyses were performed on three sources of Ontario norovirus data spanning 2009 to 2014: positive samples submitted for laboratory testing, institutional outbreaks, and calls to telehealth with vomiting as a chief complaint. However, it is important to note that the calls to telehealth (syndromic data source) were only used as a proxy for norovirus. The gender and age distribution, institutions most commonly affected, total outbreak counts, total positive sample counts, and seasonality of norovirus were determined. Using this information to define the winter norovirus season and out-of-season periods, Shewhart (control) chart methods were employed to create the early warning syndromic surveillance system using the telehealth data as the source of syndromic data. These data were shown to predict the laboratory results by two weeks, and annual early alarm thresholds for the winter norovirus season were devised. This thesis demonstrates the unique role of telehealth syndromic surveillance for norovirus in Ontario. Although these methods are widely used in other countries, they are not used in Ontario at the present time. The results from this study serve as a proposal for implementation and utilization in Ontario public health. In doing so, this syndromic surveillance system could strengthen current surveillance methods and help determine the true burden of norovirus in Ontario.