ArticleBioinformatics (Oxford, England)2019
Comparison of statistical algorithms for daily syndromic surveillance aberration detection.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Early Detection Intervals for Evaluating Event-Based Surveillance System: Reference Dataset Development Study.JMIR public health and surveillance · 2026Article
- Cells, tissues, and vigilance: navigating the complex landscape of biovigilance in India.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Evaluation and Comparison of Statistical Methods for Early Detection of Respiratory Symptom Outbreaks: A Real-World Observational Study From Iran.Health science reports · 2025Article
- An integrated framework for modelling respiratory disease transmission and designing surveillance networks using a sentinel index.Royal Society open science · 2025Article
- Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in Brazil.Lancet regional health. Americas · 2025Article
- Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records.BMC medical research methodology · 2025Article
- Evaluation of Rolling Surveillance Methods in Context of Prior Aberrations: A Simulation Study With Routine Data From Low- and Middle-Income Countries.Statistics in medicine · 2025Article
- Retrospective case-case study investigation of a significant increase inEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
- Adapting the Flexible Farrington Algorithm for daily situational awareness and alert system to support public health decision-making during the SARS-CoV-2 epidemic in England.Epidemiology and infection · 2025Article
- Article
- Early warning system using primary health care data in the post-COVID-19 pandemic era: Brazil nationwide case-study.Cadernos de saude publica · 2024Article
- Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern: a retrospective analysis.Journal of the Royal Society, Interface · 2023Article
- Outbreak detection algorithms based on generalized linear model: a review with new practical examples.BMC medical research methodology · 2023Review
- Comparison of statistical methods for the early detection of disease outbreaks in small population settings.IJID regions · 2023Article
- Performance of discrete wavelet transform-based method in the detection of influenza outbreaks in Iran: An ecological study.Health science reports · 2023Article
- A statistical algorithm for outbreak detection in multisite settings: an application to sick leave monitoring.Bioinformatics advances · 2023Article
- Cluster detection with random neighbourhood covering: Application to invasive Group A Streptococcal disease.PLoS computational biology · 2022Article
- Examination of Gender Difference in Heart Disease-Related Excess Deaths during COVID-19 Pandemic Era: Findings from the United States.Reviews in cardiovascular medicine · 2022Article
- 3Journal of preventive medicine and hygiene · 2022Article
- Article
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Authors and funding
7 authors.
Funding
Abstract
motivationPublic health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the 'rising activity, multilevel mixed effects, indicator emphasis' (RAMMIE) method and the improved quasi-Poisson regression-based method known as 'Farrington Flexible' both currently used at Public Health England, and the 'Early Aberration Reporting System' (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data.
resultsWe conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2-3 days earlier. AVAILABILITY AND IMPLEMENTATION: R codes developed for this project are available through https://github.com/FelipeJColon/AlgorithmComparison. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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