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

271
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:
271

You might also read

Related Articles

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

Sort by
Same author

Impact of Hurricane Florence on buprenorphine transactions for opioid use disorder: A dual-perspective synthetic control study.

The journal of climate change and health·2026
Same author

How Big Is the "Gray Area"? Navigating Health-Threatening Previability Pregnancy Complications in States With Abortion Restrictions.

Annals of internal medicine·2026
Same author

Assessing mpox knowledge and sexual behaviours within high-risk populations in the Democratic Republic of the Congo.

BMJ global health·2026
Same author

Cost-Effectiveness of Community Tuberculosis Screening in South Africa.

American journal of respiratory and critical care medicine·2026
Same author

Valuing reductions in the risk of death in benefit-cost analyses of environment- and climate-health actions.

Bulletin of the World Health Organization·2026
Same author

The fiscal impact of biodiversity loss and a pathway for conservation finance.

Science (New York, N.Y.)·2026

Related Experiment Video

Updated: Nov 2, 2025

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
07:13

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

Published on: April 9, 2021

4.4K

Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms.

Gregg S Gonsalves1,2, J Tyler Copple1,2, A David Paltiel3,2

  • 1Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|June 14, 2021
PubMed
Summary

Active surveillance for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is crucial for detecting asymptomatic cases. Bandit algorithms optimize mobile testing resource deployment to identify infection hotspots efficiently.

Keywords:
SARS-CoV-2bandit algorithmsreinforcement learningsurveillancetesting

More Related Videos

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots
11:11

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Published on: February 11, 2022

4.7K
Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling
08:26

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

1.9K

Related Experiment Videos

Last Updated: Nov 2, 2025

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
07:13

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

Published on: April 9, 2021

4.4K
Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots
11:11

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Published on: February 11, 2022

4.7K
Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling
08:26

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

1.9K

Area of Science:

  • Public Health Surveillance
  • Infectious Disease Epidemiology
  • Data Science and Machine Learning

Background:

  • Continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is expected among unvaccinated populations, necessitating effective detection strategies.
  • Identifying asymptomatic SARS-CoV-2 infections is critical for controlling community transmission.
  • Current active surveillance methods lack optimized strategies for resource allocation in identifying infection hotspots.

Purpose of the Study:

  • To address the explore-exploit dilemma in active surveillance for SARS-CoV-2.
  • To optimize the deployment of mobile testing resources for maximizing the detection of new SARS-CoV-2 cases.
  • To develop and evaluate a decision-support tool for policymakers to guide targeted SARS-CoV-2 testing.

Main Methods:

  • Application of bandit algorithms, specifically Thompson sampling and a spatially extended variant, to guide active surveillance.
  • Utilized mobility data from UberMedia to identify high-frequency venues as potential testing locations.
  • Developed a web app prototype integrating these algorithms for practical use by policymakers.

Main Results:

  • Bandit algorithms offer a systematic approach to the explore-exploit tradeoff inherent in active surveillance.
  • The developed algorithms can guide the efficient deployment of mobile testing resources to maximize SARS-CoV-2 case detection.
  • The prototype web app demonstrates the feasibility of using these algorithms for targeted SARS-CoV-2 testing strategies.

Conclusions:

  • Bandit algorithms provide an effective framework for optimizing active surveillance and resource allocation in public health.
  • The implemented Thompson sampling and spatial correlation methods can enhance the identification of SARS-CoV-2 infection hotspots.
  • This approach is adaptable to various jurisdictions and can aid policymakers in strategic testing decisions.