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

You might also read

Related Articles

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

Sort by
Same author

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
Same author

Disease severity among hospitalized children during the COVID-19 pandemic in Israel.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology·2026
Same author

From microbes to animals: a review on prey choice and prey-predator dynamics across organismal scales.

FEMS microbiology reviews·2026
Same author

Hybrid and vaccination immunity against severe COVID-19 in the postpandemic era: author's response.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2025
Same author

Hybrid and vaccination immunity against severe COVID-19 in the post-pandemic era-a retrospective cohort study.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2025
Same author

Estimating Mean Viral Load Trajectory From Intermittent Longitudinal Data and Unknown Time Origins.

Statistics in medicine·2025

Related Experiment Video

Updated: Oct 26, 2025

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

DOPE: D-Optimal Pooling Experimental design with application for SARS-CoV-2 screening.

Yair Daon1,2, Amit Huppert1,3, Uri Obolski1,2

  • 1School of Public Health, Tel Aviv University, Tel Aviv, Israel.

Journal of the American Medical Informatics Association : JAMIA
|August 3, 2021
PubMed
Summary

A new D-Optimal Pooling Experimental design (DOPE) strategy improves COVID-19 testing accuracy and efficiency. This novel Bayesian approach reduces error rates and test usage compared to traditional methods, aiding pandemic control efforts.

Keywords:
BayesianCOVID-19Monte-CarloRT-PCRepidemiology

More Related Videos

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification
07:54

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification

Published on: March 31, 2021

4.9K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
09:05

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

89

Related Experiment Videos

Last Updated: Oct 26, 2025

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
Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification
07:54

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification

Published on: March 31, 2021

4.9K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
09:05

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

89

Area of Science:

  • Epidemiology
  • Biostatistics
  • Infectious Disease Modeling

Background:

  • Accurate and rapid testing for SARS-CoV-2 is critical for controlling COVID-19 transmission.
  • Current pooling strategies for mass testing face limitations in speed and accuracy.
  • Efficient diagnostic testing is essential for managing infectious disease outbreaks.

Purpose of the Study:

  • To introduce a novel Bayesian pooling strategy, D-Optimal Pooling Experimental design (DOPE).
  • To enhance the accuracy and throughput of diagnostic testing for infectious diseases.
  • To provide a flexible framework for optimizing pooled testing strategies.

Main Methods:

  • Developed a Bayesian formulation for pooled testing, maximizing mutual information between data and infection states.
  • Employed Monte-Carlo sampling for mutual information estimation.
  • Utilized a discrete optimization heuristic to identify optimal pooling designs.

Main Results:

  • DOPE demonstrated superior performance over existing pooling strategies and individual testing.
  • The strategy achieved lower error rates and required fewer tests across various infection prevalence levels.
  • DOPE provides probabilistic infection outcomes, unlike binary classifications from other methods.

Conclusions:

  • DOPE offers significant improvements in accuracy and efficiency for COVID-19 testing.
  • The method naturally incorporates prior information and can be adapted for new data.
  • DOPE is a valuable tool for combating current pandemics and preparing for future ones.