A New Statistical Method to Detect Disease Outbreaks from Hospital Emergency Department Data.
Stud Health Technol Inform
; 310: 886-890, 2024 Jan 25.
Article
em En
| MEDLINE
| ID: mdl-38269936
ABSTRACT
Early detection and prediction of disease outbreaks are crucial for public health service delivery, containment response, saving patient lives, and reducing costs. We propose a new data-driven statistical methodology for outbreak detection and prediction based on routinely collected hospital Emergency Department data. The time between consecutive ED presentations matching a diagnosis of interest forms the basis of a novel index measure to signal that an outbreak has occurred. We validate the method using historical presentations of influenza-like illness made to a large sample of public hospital EDs in 2020 and compare outbreaks identified by the method with the start of the first wave of COVID-19. The method shows promise within the field of disease outbreak detection.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
COVID-19
Tipo de estudo:
Prognostic_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
/
Stud. health technol. inform.
/
Studies in health technology and informatics (Online)
Assunto da revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Austrália
País de publicação:
Holanda