Related Experiment Video
Updated: Mar 25, 2026
05:59
Nasal Wipes for Influenza A Virus Detection and Isolation from Swine
Published on: December 4, 2015
10.0K
Modeling Classical Swine Fever Outbreak-Related Outcomes
Shankar Yadav1, Nicole J Olynk Widmar2, Hsin-Yi Weng1
1Department of Comparative Pathobiology, Purdue University , West Lafayette, IN , USA.
Frontiers in Veterinary Science
|February 13, 2016
Summary
This study simulated classical swine fever (CSF) outbreaks to predict epidemic duration and infected premises. Findings highlight the impact of initial outbreak characteristics and the importance of vaccination strategies for control.
Area of Science:
- Veterinary Epidemiology
- Disease Modeling
- Risk Assessment
Background:
- Classical swine fever (CSF) poses a significant threat to swine populations globally.
- Estimating outbreak-related outcomes is crucial for effective disease control and preparedness.
- Previous models often lack detailed scenario-based risk assessments.
Purpose of the Study:
- To estimate classical swine fever (CSF) outbreak-related outcomes, including epidemic duration and the number of infected premises.
- To utilize defined most likely CSF outbreak scenarios based on empirical risk metrics.
- To inform swine producers and government authorities for better management and preparedness.
Main Methods:
- Development of risk metrics using empirical data to select likely CSF outbreak scenarios in Indiana.
- Simulation of selected single-site and multiple-site outbreak scenarios using a stochastic between-premises disease spread model.
- Classification of multiple-site scenarios into clustered and non-clustered groups for comparative analysis.
Main Results:
- Median epidemic durations varied across scenarios: 224 days (single-site), 190 days (clustered multiple-site), and 210 days (non-clustered multiple-site).
- Median infected premises estimates were 323 (single-site), 529 (clustered multiple-site), and 465 (non-clustered multiple-site).
- The number and spatial distribution of index premises significantly influenced outcome estimates; vaccination's role in depopulation was emphasized.
Conclusions:
- Routinely collected surveillance data can generate timely outbreak information based on initial characteristics.
- Findings support informed decision-making for swine producers to minimize losses during CSF outbreaks.
- Results aid government authorities in developing robust emergency preparedness plans for CSF control.
Related Concept Videos
01:18Steps in Outbreak Investigation
694
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:
694
01:23Investigation of Disease Outbreaks
34
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...
34