Complex System Approaches for Animal Health Surveillance
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Summary
A more holistic analytical approach borrowed from complex system science that considers animal disease to be a product of the complex interactions between the many individuals, organizations and other factors that are involved in, or influence food production systems is proposed.
- Type
- article
- Published
- 2019-05-16
- Cited by
- 8
- References
- 93
- Access
- Open access
- OpenAlex
- https://openalex.org/W31157247
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:155093305
Keywords
Computer science
References
- Systems Science Methods in Public Health
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- Sustainability spaces for complex agri-food systems
- Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data
- A model of nursing as a complex adaptive system.
- Conceptualising the technical relationship of animal disease surveillance to intervention and mitigation as a basis for economic analysis
- Complex system modelling for veterinary epidemiology.
- A review of unsupervised feature learning and deep learning for time-series modeling
- Livestock trade networks for guiding animal health surveillance
- A conceptual approach to design livestock production systems for robustness to enhance sustainability
- Bias--is it a problem, and what should we do?
- How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study
- Physical approach to complex systems
Cited by
- Heart rate as a measure of emotional arousal in evolutionary biology
- Modelling multi-player strategic decisions in animal healthcare: A scoping review.
- Guidance for evaluating integrated surveillance of antimicrobial use and resistance
- A qualitative analysis of health information-sharing networks in the Indonesian poultry sector.
- The Application of an Infrared-Based ECG Acquisitor in an Online Healthy Assessment System: The Effect of Temperature on Cardiac Function in Carp (Cyprinus carpio)
- Using herd frailty estimates from survival models in a mortality-based syndromic surveillance system.
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