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

Principles of Disease Surveillance

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...

Investigation of Disease Outbreaks

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...

You might also read

Related Articles

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

Sort by

Same author

Evaluating vectors for the design of a spillover-disrupting Lassa virus transmissible vaccine.

PLoS computational biology·2026

Same author

Using Serosurveys to Optimize Surveillance for Zoonotic Pathogens.

EcoHealth·2026

Same author

Comparative susceptibility of Old World and New World bat cell lines to Zika virus: Insights into viral replication and inflammatory responses.

PLoS neglected tropical diseases·2026

Same author

Interepidemic Rift Valley fever in East Africa: the recent risk landscape and projected impacts of global change.

Proceedings. Biological sciences·2026

Same author

Protocol to produce a systematic Arenavirus and Hantavirus host-pathogen database: Project ArHa.

Wellcome open research·2025

Same author

Time-varying reproductive number estimation for practical application in structured populations.

Epidemiologic methods·2025

Search research articles

Related Experiment Video

Updated: May 6, 2026

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

Published on: November 28, 2016

Using serosurveys to optimize surveillance for zoonotic pathogens.

E Clancey¹, S L Nuismer², S N Seifert¹

¹Paul G. Allen School for Global Health, Washington State University, Pullman, WA 99164 USA.

Biorxiv : the Preprint Server for Biology

|April 2, 2024

Summary

Identifying animal reservoirs for zoonotic pathogens is crucial. This study presents a model using serosurveillance data to predict peak pathogen prevalence, optimizing field sampling for elusive viruses like Ebolavirus.

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 Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings

Author Spotlight: A Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings

Published on: August 18, 2023

Related Experiment Videos

Last Updated: May 6, 2026

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

Published on: November 28, 2016

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 Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings

Author Spotlight: A Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings

Published on: August 18, 2023

Area of Science:

Epidemiology
Wildlife Health
Disease Ecology

Background:

Zoonotic pathogens pose significant global health risks, causing diseases, epidemics, and pandemics.
Identifying animal reservoirs for zoonotic pathogens is challenging, especially when pathogen prevalence is seasonal.
Effective surveillance requires optimized field sampling strategies.

Purpose of the Study:

To develop a general statistical model for predicting peak pathogen prevalence in animal populations.
To optimize field sampling efforts for detecting elusive zoonotic pathogens.
To guide future surveillance and potentially predict spillover events.

Main Methods:

Developed a general statistical model leveraging routine serosurveillance data.
Validated the model using simulated datasets to assess its reliability in predicting peak prevalence.
Applied the model to publicly available serosurveillance data from Ebolavirus reservoir bat species (Eidolon helvum and Hypsignathus monstrosus).

Main Results:

The developed methodology reliably identifies time windows of expected peak pathogen prevalence.
The model successfully predicted peak prevalence periods using simulated and real-world bat serosurveillance data.
Demonstrated the model's applicability to Ebolavirus reservoirs.

Conclusions:

The model provides a broadly applicable and simple method for optimizing field sampling for elusive pathogens.
Predicting seasonal peaks in prevalence can enhance the detection of active infections in reservoir species.
The methodology can inform strategies to mitigate zoonotic disease risks and potentially forecast spillover events.