The pilot near real time surveillance system ASTER, which currently monitors the French Forces in Djibouti and French Guiana [1], has been especially designed for inter-allied interoperability. This paper briefly describes the rationale of this system's interoperability framework and components, and its results from a 4 years long experience.
The Activity Monitoring Operating Characteristic (AMOC) curve is a useful and popular method for assessing the performance of algorithms that detect outbreaks of disease [1]. As it is typically applied in biosurveillance, the AMOC curve plots the expected time to detection (since the outbreak began) as a function of the false alert rate. An ideal algorithm has zero false alerts and a detection time of zero. An al-ternative, conceptually equivalent version of the AMOC curve plots (T – detection_time) as a function of the false alert rate, where T is a maximum mean-ingful detection time. We focus on this version.
Objective
We introduce a new measure for evaluating alerting algorithms, which is a generalization of the AMOC curve [1]. For a given rate of false positives alerts, the new measure estimates the time between when an alert is raised and when clinicians are expected to detect the outbreak on their own. We call this measure the Expected Warning Time (EWT).
This abstract describes a suite of software utilities that have been developed for systematically evaluating the detection performance and robustness of univariate temporal alerting algorithms used in syndromic surveillance systems.
A time periodic geographic disease surveillance system based on a cylindrical space-time scan statistic proposed by Kulldorff [1] has been used extensively for disease surveillance along with the SaTScan software. This statistic is based on a circular spatial scan statistic. On the other hand, many different tests have been proposed to detect purely spatial disease clusters. In particular, some spatial scan statistics such as those developed by Duczmal and Assuncao(2004), Patil and Taillie (2004), and Tango and Takahashi(2005) are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. However, due to the unlimited geometric freedom of cluster shapes, these statistics have a risk to detect quite large and unlikely peculiarly shaped clusters. A flexible spatial scan statistic proposed by Tango and Takahashi[2], which has been used along with the FleXScan software[3], has a parameter K as the pre-set maximum length of neighbors to be scanned, to be avoid detecting a cluster of unlikely peculiar shape. The flexible spatial scan statistic can be easily extended to space-time alerting methods in syndromic surveillance. Objective: This paper proposes a flexible space-time scan statistic for early detection of disease outbreaks.
The purpose of this study is to depict a local county health departmentÃs analysis and dissemination algorithm of surveillance system (SS) aberration (alarm) to designated stakeholders within the community.
Objective: To enable improved health surveillance and clinical decision support within ambulatory Electronic Health Record (EHR) systems.
Multiple surveillance activities have been conducted in Great Britain (GB) with the objective of estimating the occurrence of scrapie, a fatal neurological infectious disease of small ruminants: statutory reporting of clinical cases, annual surveys on sections of the population and occasional anonymous postal surveys. None of the surveillance sources is either unbiased or comprehensive and if the progress of control schemes is to be closely monitored, better estimates of disease occurrence are required. With this objective, the Department for Food, Environment and Rural Affairs (Defra) funded a project to: i)provide estimates of the frequency of scrapie that integrate currently available surveillance data; and ii)inform the most effective surveillance strategies that will result in sensitive systems for the detection of changes in disease prevalence in time. To make this review as comprehensive as possible it should also: i)consider clinical disease and infection at both individual animal and holding level; ii) subject to data availability, extend all analyses to the recently detected atypical form of scrapie and iii) in a context of scarce and competitive resources, approach the problem efficiently. The approaches used within this project, outlined below, describe the efficient use and integration of all existing sources to evaluate the surveillance effort. Three surveillance attributes were of particular interest in the evaluation process: sensitivity, representativeness and cost.
This paper describes a comparison between two statistics ñ SaTScan and FleXScan, applying to a data of absentees in primary school in Japan.
To compare locally-developed influenza-like syndrome definitions (derived from emergency department (ED) chief complaints) when applied to data from two ISDS DiSTRIBuTE Project participants: Boston and New York City (NYC) [1].
To compare the completeness of emergency department (ED) visit and hospital admissions data collected electronically for syndromic surveillance and data collected manually for a field surveillance exercise.