Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Steps in Outbreak Investigation

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:

You might also read

Related Articles

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

Sort by

Same author

OGN inhibits apoptosis and ferroptosis via FSHR in human granulosa cells: implications for polycystic ovary syndrome.

Cytotechnology·2026

Same author

Progress and Prospects of Nanodelivery Systems in Metabolism-Regulated mRNA Vaccines.

Biotechnology journal·2026

Same author

iRGD-modified peptide-drug conjugate improves brain delivery and antitumor efficacy in glioblastoma.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026

Same author

Amentoflavone Suppresses Stemness of Retinoblastoma Cell via Targeting Smoothened (SMO) Protein.

Stem cells international·2026

Same author

scHILL: deciphering individual-level immune cell heterogeneity with single-cell RNA sequencing data.

Briefings in bioinformatics·2026

Same author

Synergistic Ni doping and F-carbon coating of Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> for high-performance sodium-ion batteries over a wide voltage range.

Journal of colloid and interface science·2026

Search research articles

Related Experiment Video

Updated: Jun 10, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

Machine Learning Early Detection of SARS-CoV-2 High-Risk Variants.

Lun Li^1,2, Cuiping Li^1,2, Na Li^1,2

¹China National Center for Bioinformation, Beijing, 100101, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

|October 14, 2024

Summary

A new machine learning algorithm, HiRisk-Detector, can computationally detect high-risk severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants early. This tool aids in epidemic control by identifying dangerous strains days before official announcements.

Keywords:

SARS‐CoV‐2 haplotype network high‐risk variant machine learning pre‐warning

More Related Videos

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

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

Published on: June 23, 2022

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jun 10, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

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

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

Published on: June 23, 2022

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Published on: September 8, 2023

Area of Science:

Virology and Bioinformatics
Epidemiology and Public Health
Computational Biology

Background:

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants pose ongoing public health challenges, necessitating rapid identification of high-risk strains.
Traditional methods for detecting and characterizing novel SARS-CoV-2 variants are often slow, hindering timely epidemic control efforts.
Early warning systems are crucial for managing infectious disease outbreaks and mitigating their impact.

Purpose of the Study:

To develop and validate a machine learning algorithm, HiRisk-Detector, for the early computational detection of high-risk SARS-CoV-2 variants.
To assess the effectiveness, robustness, and generalizability of HiRisk-Detector using a large dataset of viral genomes.
To demonstrate the utility of HiRisk-Detector in identifying emerging threats, including Omicron sub-lineages.

Main Methods:

Development of HiRisk-Detector, a machine learning algorithm utilizing haplotype networks for variant analysis.
Validation using over 7.6 million high-quality SARS-CoV-2 genomes and associated metadata.
Performance evaluation through empirical data analysis, simulated reduced sequencing intensity, and application to Omicron sub-lineages.

Main Results:

HiRisk-Detector successfully identified all 13 high-risk SARS-CoV-2 variants, on average 27 days before World Health Organization declarations.
The algorithm maintained effectiveness with reduced sequencing data, showing only a minor delay of 3.8 days.
High performance metrics (ROC-AUC and PR-AUC) were achieved when applied to SARS-CoV-2 Omicron variant sub-lineages.

Conclusions:

HiRisk-Detector offers a powerful computational tool for the early detection of high-risk SARS-CoV-2 variants.
The algorithm's speed and accuracy provide significant advantages over traditional detection methods for epidemic preparedness.
HiRisk-Detector has broad applicability for public health emergencies involving novel infectious agents.