BACKGROUND The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on a...

Surveillance is a critical component of disease control programmes but is often poorly resourced, particularly in developing countries lacking good infrastructure and especially for zoonoses which require combined veterinary and medical capacity and collaboration. Here we examine how successful control, and ultimately disease elimination, depends on effective surveillance. We estimated that det...

Syndromic surveillance systems, especially software systems, have emerged as the leading outbreak detection mechanisms. Early outbreak detection systems can assist with medical and logistic decision support. One important concern for effectively testing these systems in practice is the scarcity of authentic outbreak health data. Because of this shortage, creating suitable geotemporal test clust...

We describe an outbreak of Burkholderia stabilis associated with contaminated washing gloves, a commercially available Class I medical device. Triggered by an increase in Burkholderia cepacia complex (BCC) bacteremias and the detection of BCC in unopened packages of washing gloves, an ad hoc national outbreak committee comprising representatives of a public health organisation, a regulatory age...

There are some existing evaluation methods, such as the AMOC curve [1], which focus on evaluating the timeliness of alerting algorithms. As the AMOC curve is typically applied in biosurveillance, it plots the expected time to computer-based detection (since the outbreak began) as a function of the false alert rate. In an EWT curve, we add a clinician model and plot the expected time that an alg...

BACKGROUND Spatial outbreak detection algorithms using routinely collected healthcare data have been developed since the late 90s to identify and locate disease outbreaks. However, current well-received spatial algorithms assume only one outbreak cluster present at the same point of time which may not be valid during a pandemic when several clusters of geographic areas concurrently occur. Based...

BACKGROUND In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identifica...

OBJECTIVE To evaluate the performance of China's infectious disease automated alert and response system in the detection of outbreaks of hand, foot and mouth (HFM) disease. METHODS We estimated size, duration and delay in reporting HFM disease outbreaks from cases notified between 1 May 2008 and 30 April 2010 and between 1 May 2010 and 30 April 2012, before and after automatic alert and respo...

A dynamic risk model is developed to track the occurrence and evolution of a drinking-water-borne cryptosporidiosis outbreak. The model characterizes and integrates the various environmental, medical, institutional, and behavioral factors that determine outbreak development and outcome. These include contaminant delivery and detection, water treatment efficiency, the timing of interventions, an...