一个方法框架,用于将动物疾病的负担归因于特定的原因
Revue scientifique et technique (International Office of Epizootics)
|September 2, 2024
概括
本研究为评估动物疾病负担提供了一个框架,考虑生产损失和卫生成本. 它解决了疾病分类和数据收集方面的挑战,以更好地规划动物健康计划.
科学领域:
- 兽医流行病学 兽医流行病学
- 动物健康经济学 动物健康经济学
- 公共卫生 公共卫生
背景情况:
- 衡量全球动物疾病负担对于了解对养殖动物种群的影响至关重要.
- 现有的框架往往缺乏全面的方法来估计农场一级的疾病负担,包括生产损失和卫生支出.
- 识别动物疾病对经济和人类健康的影响需要强大的分析工具.
研究的目的:
- 引入一个分析框架来衡量养殖动物种群的整体健康状况.
- 估计农场一级的疾病负担,包括生产损失和卫生支出.
- 确定动物疾病对人类健康和经济的更广泛影响.
主要方法:
- 制定一个框架,将疾病负担归因于特定原因.
- 解决方法上的挑战:疾病分类,术语含糊性,数据可用性和并发症调整.
- 使用布鲁塞拉 spp. 作为框架应用案例研究的小反动物感染.
主要成果:
- 该框架允许估计农场一级的疾病负担,包括发病率,死亡率和卫生支出.
- 实践示例展示了使用动物传染病Brucella spp.框架的应用. 在小型反动物中.
- 具体因果归因捕捉了动物疾病负担的时间和空间趋势.
结论:
- 准确估计农场一级的疾病负担对于有效的动物健康管理至关重要.
- 拟议的框架提供了一种因果特定归因的方法,有助于规划和评估干预措施.
- 了解疾病负担趋势对于改善动物健康计划和减轻经济和人类健康影响至关重要.
相关概念视频
01:21Causality in Epidemiology
349
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
349
01:28Criteria for Causality: Bradford Hill Criteria - II
248
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
248
01:30Criteria for Causality: Bradford Hill Criteria - I
239
The Bradford Hill criteria are a group of principles that provide a framework to determine a causal relationship between a specific factor and a disease. There are nine criteria that are pivotal in assessing causality in epidemiological studies. Here's a closer look at Strength, Consistency, Specificity, and Temporality criteria with definitions and examples:
239
01:18Steps in Outbreak Investigation
114
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:
114
01:29Bias in Epidemiological Studies
180
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
180
01:25Strategies for Assessing and Addressing Confounding
87
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
87