Related Experiment Video

Updated: Jun 30, 2026

Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes
10:11

Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes

Published on: September 27, 2014

A Metagenomic Biosurveillance Network for Emerging Infectious Diseases: A Simulation-Based Model

Isabel Meusel1, David Manheim1, Oscar Delaney1

  • 1Isabel Meusel, MD, was a Research Fellow, Existential Risk Alliance, Cambridge, United Kingdom; and is now a PhD Researcher, Department of Primary and Long-Term Care, University Medical Center Groningen, Groningen, the Netherlands. David Manheim, PhD, is Director of Policy and Research, Association for Long Term Existence and Resilience (ALTER), Rehovot, Israel; and a Visiting Lecturer, Technion - Israel Institute of Technology, Haifa, Israel. Oscar Delaney is a Research Manager, Existential Risk Alliance, Cambridge, United Kingdom. Daniel Greene, PhD, was a Senior Analyst at Gryphon Scientific, Takoma Park, MD; and is now a Technical Staff member at Mirror Biology Dialogues Fund, New York, NY. Rona Tobolsky is a Researcher, ALTER, Rehovot, Israel; and a Graduate Student, School of Public Health, Tel Aviv University, Tel Aviv, Israel. Hanna Palya was a Research Fellow, Existential Risk Alliance, Cambridge, United Kingdom; and is now a PhD Researcher, Institute for Global Pandemic Planning, University of Warwick, Coventry, United Kingdom. Naham Shapiro, MPH, is a Public Health Lead, ALTER, Rehovot, Israel; and a Research Assistant, School of Public Health, Hebrew University of Jerusalem, Jerusalem, Israel. Siddhanth Sharma, MD, MPH, was a Public Health Registrar, Metropolitan Communicable Disease Control Perth, Perth, Australia; and is now a Public Health Specialist, Burnet Institute, Melbourne, Australia.

Health Security
|June 29, 2026
PubMed
Summary

Early detection of novel respiratory pathogens in Israel is possible with a metagenomic next-generation sequencing (mNGS) system. This surveillance approach, utilizing an SEIR model, could identify outbreaks within 68 days, aiding containment efforts.

Keywords:
Early warning systemsInfectious diseasesMetagenomicsPandemic preparedness/responsePathogen detection

Related Concept Videos

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...
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:
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...
Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
Microbial Biosensors01:17

Microbial Biosensors

Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...
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...