Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    A simple spatio-temporal algorithm for disease surveillance using routinely collected data

    Access Status
    Fulltext not available
    Authors
    Watkins, Rochelle
    Eagleson, Serryn
    Veenendaal, Bert
    Wright, Graeme
    Plant, Aileen
    Date
    2006
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Watkins, Rochelle and Eagleson, Serryn and Veenendaal, Bert and Wright, Graeme and Plant, Aileen. 2006. A simple spatio-temporal algorithm for disease surveillance using routinely collected data, in Paul White (ed), GeoHealth 2006 Methods in Practise, Nov 28 2006, pp. 58-59. Nelson, New Zealand: Ministry of Health.
    Source Title
    Proceedings of GeoHealth 2006
    Source Conference
    GeoHealth 2006 Methods in Practise
    ISBN
    0-478-30096-4
    Faculty
    Australian Biosecurity Cooperative Research Centre
    Faculty of Science and Engineering
    School
    Australian Biosecurity CRC- Emerging Infectious Diseases (CRC-Core)
    URI
    http://hdl.handle.net/20.500.11937/47191
    Collection
    • Curtin Research Publications
    Abstract

    In Australia diagnostic data from medical practitioners and laboratories for over 60 different notifiable diseases are reported at a national level and compiled into the National Notifiable Diseases Surveillance System (NNDSS). Considerable time and resources are invested in the collection of these disease notification data. Due to the large number of diseases under surveillance, the performance of comprehensive daily analyses for the early detection of disease outbreaks is a time-consuming process. We aim to develop tools to allow epidemiologists to make better use of existing disease surveillance data. We explore the application of automated spatio-temporal algorithms for disease surveillance to assist epidemiologists to monitor large volumes of routinely collected data. A simple surveillance algorithm based on a Bayesian space-time hidden Markov model was developed to identify spatio-temporal aberrations in surveillance data. The algorithm monitors the distribution of notified cases of disease based on the date of diagnosis and post code of residence, and uses probability concepts to expressthe uncertainty associated with the likelihood of an outbreak. To illustrate the method developed we apply the algorithm to hepatitis A diagnoses as a case study, and assess the ability of the algorithm to identify events of concern to epidemiologists. This paper describes the algorithm developed and evaluates the ability of the algorithm to detect disease outbreaks before they become widespread.

    Related items

    Showing items related by title, author, creator and subject.

    • Neonatal deaths in a rural area of Bangladesh: an assessment of causes, predictors and health care seeking using verbal autopsy
      Chowdhury, Md. Hafizur Rahman (2008)
      Poor neonatal health is a major contributor to mortality in under-five children in developing countries, accounting for more than two thirds of all deaths in the first year of life, and for about half of all deaths in ...
    • A GIS prototype for the automated detection and visualisation of disease outbreaks in Australia
      Eagleson, Serryn; Watkins, Rochelle; Veenendaal, Bert; Wright, Graeme; Plant, Aileen (2006)
      Disease outbreaks are difficult to detect. Some diseases appear rapidly, while others take time to gestate and become apparent over long time intervals. This research project aims to develop new technology to extend the ...
    • Features of adenoma and colonoscopy associated with recurrent colorectal neoplasia based on a large community-based study
      Van Heijningen, E.; Lansdorp_Vogelaar, Iris; Kuipers, E.; Dekker, E.; Lesterhuis, W.; Ter Borg, F.; Vecht, J.; De Jonge, V.; Spoelstra, P.; Engels, L.; Bolwerk, C.; Timmer, R.; Kleibeuker, J.; Koornstra, J.; Van Ballegooijen, M.; Steyerberg, E. (2013)
      Background & Aims: We investigated adenoma and colonoscopy characteristics that are associated with recurrent colorectal neoplasia based on data from community-based surveillance practice. Methods: We analyzed data of ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.