The objective of this paper is to examine the utility of Emergency Department and Telehealth data for Syndromic Surveillance. This works attempts to minimize false outbreak detection. It also demonstrates that these two data sources contain independent information which is useful for outbreak detection.
To evaluate whether joint monitoring of laboratory test orders and outpatient visits improves the sensitivity and timeliness of alerting during seasonal increases in respiratory illness.
I examine the nature and expression of the null hypothesis often used in spatial surveillance. I also show an example of how incorrect specification of the null can lead to excess signals without interesting outbreaks, and argue that this may be a cause of excess signals when using spatial surveillance in public health applications.
Using New York CityÃs dead bird surveillance for West Nile Virus (WNV), this paper presents two explorations of the spatial cluster detection problem in which lagged test results are available for a random subset of observations. First, we establish a framework for the direct evaluation of methods and identify the optimal parameterization over a large family of models. We then investigate ways in which the lagged test results and other covariates might be used prospectively to extend the family of models by refining the baseline.
To determine the feasibility of using BioSense laboratory data to do surveillance on Clostridium difficile infection (CDI) and calculate overall and facility rates of disease.
We evaluated several classifications of emergency department (ED) syndromic data to ascertain best syndrome classifications for ILI.
This paper evaluates the operating characteristics of limited baseline aberration detection methods using different lengths (7-28 days) and end dates (1-7 days prior to the current day) for the baseline period using simulated outbreaks added to real data and simulated data representative of real data.
To determine whether preprocessing chief complaints before automatically classifying them into syndromic categories improves classification performance.
A retrospective chart review was performed to examine chief complaint, syndrome classification and discharge diagnoses of laboratory confirmed Salmonella Enteritidis phage type (PT) 13 cases who visited the Emergency Departments (ED) of two local hospitals during a province-wide outbreak in Ontario in the fall of 2005. This assessment was used to assess the sensitivity of the ED syn-dromic surveillance system to detect a local foodborne outbreak, and to modify syndrome classification.
To measure the impact, within administrative geographic areas, of household income on rates of visits due influenza and RSV among children using real-time syndromic surveillance.