Surveillance System Analysis
Surveillance System Analysis
Image © FreeFoto.com

Scenario Trees to Quantify Confidence in Freedom from Disease

Introduction

Demonstrating that a population is free from disease (or from a pathogen) is a difficult task, based on probabilistic assessments of accumulated evidence. The statistical theory has been established for the design and analysis of structured surveys using random sampling to gather evidence for freedom from disease. Such surveys are often expensive and wasteful of resources as they ignore existing evidence.

Scenario tree modelling provides an alternative method of analysis of surveillance data to provide quantitative measures of the sensitivity of a surveillance system and the probability of disease freedom. This method allows complex surveillance systems (based on non-random selection) to be modeled and analysed, enabling the use of evidence from existing surveillance systems to be used to support claims of freedom from disease.

Scenario tree modelling uses stochastic simulation, and can be implemented in spreadsheets. However this task is time consuming, error prone, and requires stochastic add-in software. This site allows users to develop their own scenario tree model through a simple on-line interface, and notifies the user by email when simulations have been completed.

Getting Started

What's it about?Guide to the Methodology
How to do it?Web site User's Manual
General InformationCourses, links, downloads, examples, etc.
Documentation HomeLinks to all documentation

Log in to use on-line software is currently unavailable

If you would like to use this system please contact Evan or Angus
User name
Password

Quantifying Confidence in Disease Freedom
This site was created by and maintained by Ausvet
Project originally funded by the Australian Biosecurity Cooperative Research Centre
Project leader: Tony Martin. Project © 2004-2009
For help: Evan Sergeant or Angus Cameron (Ausvet)
Portions of code used in this site are based on TreeView v4.3 JavaScript Tree Menu
This site uses PHP, MySQL, the R statistical language and PmWiki. Images courtesy of FreeFoto.com