Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records

Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records

Abstract Background Methods that enable early outbreak detection represent powerful tools in epidemiological surveillance, allowing adequate planning and timely response to disease surges. Syndromic surveillance data collected from primary healthcare encounters can be used as a proxy for the inciden...

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Main Authors: Dérick G. F. Borges, Eluã R. Coutinho, Thiago Cerqueira-Silva, Malú Grave, Adriano O. Vasconcelos, Luiz Landau, Alvaro L. G. A. Coutinho, Pablo Ivan P. Ramos, Manoel Barral-Netto, Suani T. R. Pinho, Marcos E. Barreto, Roberto F. S. Andrade
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Medical Research Methodology
Subjects:
Syndromic surveillance
Outbreak detection
Primary healthcare data
Machine learning
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Online Access:https://doi.org/10.1186/s12874-025-02542-0
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https://doi.org/10.1186/s12874-025-02542-0

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