Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records
Identifying trends in time series data related to primary healthcare encounters indicated the possibility of developing a reliable method for the early detection of outbreaks. MMAING demonstrated consistent identification capabilities across various scenarios, outperforming established reference methods.
Authors
- Marcos Barreto (ORCID: https://orcid.org/0000-0002-7818-1855)
- Luiz Landau (ORCID: https://orcid.org/0000-0001-7857-9946)
- Malú Grave (ORCID: https://orcid.org/0000-0002-7697-0658)
- Thiago Cerqueira Silva (ORCID: https://orcid.org/0000-0003-4534-2509)
- Álvaro L. G. A. Coutinho (ORCID: https://orcid.org/0000-0002-4764-1142)
- Roberto F. S. Andrade (ORCID: https://orcid.org/0000-0002-9323-1400)
- Suani T. R. Pinho (ORCID: https://orcid.org/0000-0003-1404-3485)
- Manoel Barral‐Netto (ORCID: https://orcid.org/0000-0002-5823-7903)
- Eluã Ramos Coutinho (ORCID: https://orcid.org/0000-0003-2350-4319)
- Pablo Ivan Pereira Ramos (ORCID: https://orcid.org/0000-0002-9075-7861)
- Alzemira Pantoja Canuto de Vasconcelos (ORCID: https://orcid.org/0000-0002-0271-8599)
- Dérick G. F. Borges (ORCID: https://orcid.org/0000-0001-7627-4452)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Universidade Federal da Bahia (BR)
- Universidade Federal Fluminense (BR)
- Knowledge Integration (United Kingdom) (GB)
- Prefeitura Municipal de Rio das Ostras (BR)
- Fundação Oswaldo Cruz (BR)
- London School of Economics and Political Science (GB)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1186/s12874-025-02542-0
- Citations
- 4
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 5.42
Funders
- Rockefeller Foundation
- Royal Society
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Oswaldo Cruz