ArticleJournal of biomedical informatics2010
Comparing early outbreak detection algorithms based on their optimized parameter values.
Article in Journal of biomedical informatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cluster Detection Mechanisms for Syndromic Surveillance Systems: Systematic Review and Framework Development.JMIR public health and surveillance · 2020Pooled it
- Comparison of Three Influenza Surveillance Data Sources for Timely Detection of Epidemic Onset - Chengdu City, Sichuan Province and Beijing Municipality, China, 2017-2023.China CDC weekly · 2024Article
- Article
- Evaluation of the application of sequence data to the identification of outbreaks of disease using anomaly detection methods.Veterinary research · 2023Article
- Real-time risk ranking of emerging epidemics based on optimized moving average prediction limit-taking the COVID-19 pandemic as an example.BMC public health · 2023Article
- Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System.The Journal of international medical research · 2018Article
- How to select a proper early warning threshold to detect infectious disease outbreaks based on the China infectious disease automated alert and response system (CIDARS).BMC public health · 2017Article
- Implementation and Initial Analysis of a Laboratory-Based Weekly Biosurveillance System, Provence-Alpes-Côte d'Azur, France.Emerging infectious diseases · 2017Article
- Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study.PloS one · 2017Article
- Hand, foot and mouth disease in China: evaluating an automated system for the detection of outbreaks.Bulletin of the World Health Organization · 2014Article
- Article
- Development of ClickClinica: a novel smartphone application to generate real-time global disease surveillance and clinical practice data.BMC medical informatics and decision making · 2013Article
- Improving the performance of outbreak detection algorithms by classifying the levels of disease incidence.PloS one · 2013Article
- Epidemic features affecting the performance of outbreak detection algorithms.BMC public health · 2012Article
- Adjusting outbreak detection algorithms for surveillance during epidemic and non-epidemic periods.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- Outbreak detection algorithms for seasonal disease data: a case study using Ross River virus disease.BMC medical informatics and decision making · 2010Article
Corrections and comments
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10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany researchers have evaluated the performance of outbreak detection algorithms with recommended parameter values. However, the influence of parameter values on algorithm performance is often ignored.
methodsBased on reported case counts of bacillary dysentery from 2005 to 2007 in Beijing, semi-synthetic datasets containing outbreak signals were simulated to evaluate the performance of five outbreak detection algorithms. Parameters' values were optimized prior to the evaluation.
resultsDifferences in performances were observed as parameter values changed. Of the five algorithms, space-time permutation scan statistics had a specificity of 99.9% and a detection time of less than half a day. The exponential weighted moving average exhibited the shortest detection time of 0.1 day, while the modified C1, C2 and C3 exhibited a detection time of close to one day.
conclusionThe performance of these algorithms has a correlation to their parameter values, which may affect the performance evaluation.
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