Comparison of statistical algorithms for syndromic surveillance ...

Syndromic Surveillance System for the Athens 2004 Olympic Games

This paper proposes an algorithm for statistical detection of peaks. The method is based on removing long-term trends from the series of observations.

Comparison of Statistical Algorithms for the Detection of In

In the context of disease surveillance, a scoring rule can be adapted to reflect the size of outbreaks and this was done. Results indicate that the two new ...

arXiv:2101.12246v1 [cs.LG] 28 Jan 2021

In this paper, we revisit algorithms for non-specific syndromic surveillance and compare them to a broad range of anomaly detection algorithms.

Evaluation and comparison of statistical methods for early temporal ...

Data Availability: The data underlying this study are third party data and come from the “An improved algorithm for outbreak detection in multiple surveillance ...

Comparison of Statistical Algorithms for the Detection of Infectious ...

M Frisén, Evaluation of methods for statistical surveillance, Statistics ... Comparison of statistical algorithms for daily syndromic surveillance aberration ...

Outbreak detection algorithms based on generalized linear model

(2019) showed that Farrington Flexible algorithm has higher sensitivity and specificity in daily syndromic surveillance compared to methods such ...

Assessing 3 Outbreak Detection Algorithms in an Electronic ... - CDC

Comparing syndromic surveillance ... Introduction to statistical methods for biosurveillance: with an emphasis on syndromic surveillance.

A Unifying Framework and Comparative Evaluation of Statistical and ...

In an experimental comparison of different ... statistical algorithms for outbreak detection in the setting of non-specific syndromic surveillance.

Comparative Analysis of Statistical and Supervised Learning ...

Comparative Analysis of Statistical and Supervised Learning Algorithms for Outbreak Detection in the Syndromic Surveillance of Influenza‐Like Illness: A ...

Texas Syndromic Surveillance (TxS2)

Syndromic surveillance utilizes trend analysis to establish a baseline and then uses algorithms to compare the current data to that baseline and issue alerts ...

Comparison of Statistical Algorithms for the Detection of Infectious ...

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s ...

Joint assessment of temporal segmentation, time unit and detection ...

Comparison of statistical algorithms for daily syndromic surveillance aberration detection. Bioinformatics 35 (17), 3110–3118. Openshaw, S ...

Comparison of Statistical Algorithms for the Detection of Infectious ...

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s ...

Real-time Syndromic Surveillance - WHO Kobe Centre

Statistical algorithms can also be applied to the development of historical baselines, which can supplement the interpretation of syndromic data by comparing ...

Syndromic Surveillance: An Effective Tool for Detecting Bioterrorism?

Which Methods of Syndromic Surveillance Are Most Effective? ... The researchers also compared four specific detection algorithms. ... The analysis found that all of ...

A Tool for Comparing Outbreak Detection Algorithms - SpringerLink

... Comparing syndromic surveillance detection methods: EARS' versus a CUSUM-based methodology. Statistics in Medicine (17), 3407–3429 (2008). Article MathSciNet ...

Evaluating multi-purpose syndromic surveillance systems

... syndromic surveillance focuses on the use of the statistical algorithms ... Comparison of Statistical Algorithms for Daily Syndromic Surveillance Aberration.

Enhancing Public Health Surveillance: Outbreak Detection ... - Cureus

Accordingly, it is necessary to use this algorithm throughout mass gatherings and in syndromic surveillance systems to provide useful and ...

A statistical algorithm for outbreak detection in a multi-site setting

Comparison of statistical algorithms for daily syndromic surveillance aberration detection. Bioinformatics (Oxford, England) . 2019;35(17): ...

Syndromic Surveillance: Adapting Innovations to Developing Settings

comparing the data to non-outbreak expectations (trends that depart from ... • Statistical algorithms to detect unexpected elevations in indicator data.