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

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

333
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...
333
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

682
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...
682
Levels of Use of a GIS01:29

Levels of Use of a GIS

457
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
457
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.9K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.9K
Introduction to GIS01:28

Introduction to GIS

744
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...
744
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

1.2K
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Factors Affecting Cypriot Nurses' Roles in the Care and Education of Patients with CKD: An Interpretive Phenomenological Study.

Healthcare (Basel, Switzerland)·2025
Same author

Heatwave 1987: the Piraeus <i>versus</i> Athens case.

F1000Research·2024
Same author

2D Anatomical Structure for COVID-19 Medical Images.

Studies in health technology and informatics·2022
Same author

Motion Shield: An Automatic Notifications System for Vehicular Communications.

Sensors (Basel, Switzerland)·2022
Same author

The Contribution of Informatics to Overcoming the Covid-19 Fake News Outbreak by Learning to Navigate the Infodemic.

Studies in health technology and informatics·2022
Same author

Investigating the Impact of Misinformation Sources on Health Issues: Implications for Public Health.

Studies in health technology and informatics·2021

Related Experiment Video

Updated: Apr 7, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.9K

A Decision Support System Platform for Spatial Epidemiology.

Stelios Zimeras1, Aggelos Mechili2, Marianna Diomidous2

  • 1Department of Mathematics, University of the Aegean, Samos.

Studies in Health Technology and Informatics
|July 9, 2015
PubMed
Summary

A new information system combines patient health records with Geographical Information Systems (GIS) technology. This system acts as an advisor for managing epidemiological disease outbreaks.

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

9.3K
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

14.3K

Related Experiment Videos

Last Updated: Apr 7, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.9K
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

9.3K
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

14.3K

Area of Science:

  • Health Informatics
  • Epidemiology
  • Geographical Information Systems

Background:

  • Decision Support Systems (DSS) are crucial in healthcare for aiding medical opinions.
  • Existing systems often lack integrated geographical data for epidemiological analysis.

Purpose of the Study:

  • To develop a pilot information system integrating patient health records and GIS technology.
  • To create an advisory tool for epidemiological disease management.

Main Methods:

  • Developed a novel information system architecture.
  • Combined electronic health records data with Geographical Information Systems (GIS) data.
  • Pilot testing for advisory capabilities in disease outbreak scenarios.

Main Results:

  • Successfully developed a functional pilot information system.
  • Demonstrated the potential of integrated health and GIS data for epidemiological advisement.
  • The system provides a foundation for enhanced disease surveillance.

Conclusions:

  • Integrated health record and GIS data offer a powerful approach for epidemiological decision support.
  • The developed system can serve as a valuable advisor during disease outbreaks.
  • Future work should focus on scaling and validating the system in real-world scenarios.