Work

Monitoring Poisson time series using multi-process models

Year: 2006

Type: book

Abstract: Surveillance of infectious diseases based on routinely collected public health data is important for at least three reasons: The early detection of an epidemic may facilitate prompt interventions and the seasonal variations and long term trend may be of general epidemiological interest. Furthermore aspects of health resource management may also be addressed. In this paper we center on the detection of outbreaks of infectious diseases. This is achieved by a multi-process Poisson state space model taking autocorrelation and overdispersion into account, which has been applied to a data set concerningMycoplasma pneumoniae infections.

Source: VBN Forskningsportal (Aalborg Universitet)

Authors: Malene Dahl Skov Engebjerg, Søren Lundbye‐Christensen, B. Kjær, Henrik Carl Schønheyder

Institutions: Statens Serum Institut, Aarhus University Hospital

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2254940551

FWCI: 0.337

Cites: 15

Cited by: 1

Related to: 10