Jove
Visualize
Contact Us

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:
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
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...
Rapid Identification of Pathogens01:25

Rapid Identification of Pathogens

MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...
Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...
Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:

You might also read

Related Articles

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

Sort by
Same author

Evaluation of an automated feedback intervention to improve antibiotic prescribing among primary care physicians (OPEN Stewardship): a multinational controlled interrupted time-series study.

Microbiology spectrum·2024
Same author

An Evaluation of the Impact of an OPEN Stewardship Generated Feedback Intervention on Antibiotic Prescribing among Primary Care Veterinarians in Canada and Israel.

Animals : an open access journal from MDPI·2024
Same author

Validation of myocarditis diagnoses in the Swedish patient register for analyses of potential adverse reactions to COVID-19 vaccines.

Upsala journal of medical sciences·2023
Same author

Syndromic surveillance system during mass gathering of Panchkroshi Yatra festival, Ujjain, Madhya Pradesh, India.

New microbes and new infections·2023
Same author

Comparison of years of life lost to 1,565 suicides versus 10,650 COVID-19 deaths in 2020 in Sweden: four times more years of life lost per suicide than per COVID-19 death.

Upsala journal of medical sciences·2022
Same author

SARS-CoV-2 Vaccination and Myocarditis in a Nordic Cohort Study of 23 Million Residents.

JAMA cardiology·2022
Same journal

An explainable machine learning model for predicting high phosphorus risk in patients on maintenance hemodialysis: a multicenter retrospective study.

BMC medical informatics and decision making·2026
Same journal

Physicians' preferences for the use of clinical decision support systems in the context of acutely ill children presenting to ambulatory care: a focus group study.

BMC medical informatics and decision making·2026
Same journal

Machine learning prediction of postoperative pulmonary infection in patients who underwent thoracoscopic lung cancer resection: a retrospective case-control study.

BMC medical informatics and decision making·2026
Same journal

Establishing development strategies and improvement paths for decision coach competencies in shared decision-making using an integrated accessibility-performance analysis and network relation map approach.

BMC medical informatics and decision making·2026
Same journal

Inflammatory marker-driven deep learning model for postoperative gastric cancer prognosis.

BMC medical informatics and decision making·2026
Same journal

Does clinical documentation reflect how parents and clinicians share decisions about surgery?

BMC medical informatics and decision making·2026
See all related articles
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 Experiment Video

Updated: Jun 15, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

CASE: a framework for computer supported outbreak detection.

Baki Cakici1, Kenneth Hebing, Maria Grünewald

  • 1Swedish Institute for Infectious Disease Control (SMI), 171 82 Solna, Sweden. baki.cakici@smi.se

BMC Medical Informatics and Decision Making
|March 16, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a computer-supported outbreak detection framework using statistical methods to identify excess disease cases. The open-source CASE framework encourages collaborative development for enhanced infectious disease surveillance.

Related Experiment Videos

Last Updated: Jun 15, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

Area of Science:

  • Epidemiology
  • Public Health Informatics
  • Computer Science

Background:

  • Traditional outbreak detection relies on statistical methods applied to case data, with human experts verifying potential outbreaks.
  • The Swedish Institute for Infectious Disease Control developed a technical framework for computer-supported infectious disease outbreak detection.
  • This system processes a database of case reports for numerous infectious diseases using user-selected statistical methods.

Observation:

  • The framework enables the application of various statistical algorithms for outbreak detection at both disease and subtype levels.
  • It allows independent configuration of algorithm parameters for different diagnoses via a graphical interface.
  • Input generators and output parsers are integrated for all supported algorithms, with email notifications for detected outbreaks.

Findings:

  • The implemented framework facilitates automated detection of potential disease outbreaks using statistical analysis.
  • Configurable algorithms and user-friendly interface enhance the efficiency and specificity of outbreak detection.
  • Automated email notifications streamline the response process for identified outbreaks.

Implications:

  • The open-source nature of the CASE framework promotes wider adoption and collaborative development in infectious disease surveillance.
  • This system can improve the timeliness and accuracy of outbreak detection, aiding public health responses.
  • Encouraging contributions to the CASE framework can accelerate advancements in computer-supported epidemiological surveillance systems.