Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
Introduction to GIS01:28

Introduction to GIS

Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
Manipulation and Analysis01:21

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Hearing the deaf nursing student: Navigating inclusive nurse education in ableist learning environments.

Nurse education in practice·2026
Same author

Challenges and Opportunities Developing Mathematical Models of Shared Pathogens of Domestic and Wild Animals.

Veterinary sciences·2018
Same author

Decision-making for foot-and-mouth disease control: Objectives matter.

Epidemics·2016
Same author

Assessing the risk of highly pathogenic avian influenza H5N1 transmission through poultry movements in Bali, Indonesia.

Preventive veterinary medicine·2014
Same author

Effective surveillance strategies following a potential classical Swine Fever incursion in a remote wild pig population in North-Western Australia.

Transboundary and emerging diseases·2013
Same author

Salmonella infection in a remote, isolated wild pig population.

Veterinary microbiology·2012
Same journal

Highly pathogenic avian influenza H5N1 virus outbreak among common terns (Sterna hirundo) in Namibia, 2025-2026.

Veterinaria italiana·2026
Same journal

Investigating Seasonal and Host Sex-Age Effects on Endoparasites in a Captive population of the Vulnerable Barbary sheep (North Algeria).

Veterinaria italiana·2026
Same journal

Bluetongue virus serotype 8 (BTV-8) in Serbia, 2025.

Veterinaria italiana·2026
Same journal

Hantaviruses in the One Health era: strengthening surveillance before the next spillover.

Veterinaria italiana·2026
Same journal

First comprehensive histopathological and seroepidemiological investigations of Toxoplasma gondii infection in meat goats in Algeria.

Veterinaria italiana·2026
Same journal

A One Health systematic review and meta-analysis of Coxiella burnetii prevalence in humans, animals, and vectors in Algeria.

Veterinaria italiana·2026
See all related articles

Related Experiment Video

Updated: Jun 13, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Simulating disease spread within a geographic information system environment.

Samuel Beckett1, M Graeme Garner

  • 1Department of Agriculture, Fisheries and Forestry, GPO Box 858, Canberra, ACT 2601, Australia. Beckett@Broadleaf.com.au

Veterinaria Italiana
|April 28, 2010
PubMed
Summary
This summary is machine-generated.

Simulation modelling helps assess exotic disease control strategies. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses unique, spatially explicit geographic information system (GIS) models for disease surveillance and eradication.

More Related Videos

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field
10:49

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field

Published on: March 16, 2019

Related Experiment Videos

Last Updated: Jun 13, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field
10:49

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field

Published on: March 16, 2019

Area of Science:

  • Veterinary epidemiology
  • Ecological modeling
  • Agricultural science

Background:

  • Simulation modelling is crucial for evaluating exotic disease control, eradication, and surveillance strategies.
  • The Australian Government Department of Agriculture, Fisheries and Forestry (DAFF) has over a decade of experience in disease simulation modelling.
  • Initial focus was on foot and mouth disease, with current development expanding to avian influenza and classical swine fever.

Purpose of the Study:

  • To detail the development and capabilities of DAFF's advanced spatial simulation models for exotic disease management.
  • To highlight the integration of geographic information system (GIS) technology in disease modelling.
  • To showcase the incorporation of diverse transmission pathways and spatial data layers.

Main Methods:

  • Development of spatially explicit simulation models within a geographic information system (GIS) environment (MapBasic/MapInfo).
  • Incorporation of multiple animal species, production types, and various disease transmission pathways (e.g., animal movements, windborne, feral animals).
  • Utilization of diverse spatial data layers including farm locations, land cover, water bodies, and elevation.

Main Results:

  • DAFF's spatial models are uniquely developed in a GIS environment, simplifying spatial coding and data handling.
  • The models effectively integrate complex spatial data layers, enhancing the analysis of disease spread.
  • The GIS platform provides robust mapping and tabular output capabilities for informed decision-making.

Conclusions:

  • Spatially explicit simulation models developed within a GIS framework offer a powerful tool for assessing exotic disease strategies.
  • The integration of detailed spatial data and multiple transmission pathways improves the realism and utility of disease models.
  • DAFF's modelling approach enhances the capacity for effective exotic disease surveillance, control, and eradication planning.