应用多标准决策分析技术和决策支持框架,为计划,准备和应对的树病毒风险评估提供信息
Segaran P Pillai1, Elizabeth Fox1, Ann M Powers2
1U.S. Department of Health and Human Services, Food and Drug Administration, Office of the Commissioner, Silver Spring, MD, United States.
Frontiers in bioengineering and biotechnology
|December 19, 2025
概括
多标准决策分析 (MCDA) 和决策支持框架 (DSF) 确定了高风险的 arbovirus. 这些方法通过评估载体传播病毒风险,为公共卫生提供了可靠的决策.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 病毒学 病毒学
背景情况:
- 载体传播病毒导致全球超过17%的人类感染,导致显著的死亡率.
- 在500种描述的树冠病毒中,有150多种导致人类疾病,需要进行风险评估.
- 蚊子和等飞行昆虫是由于高效的传播和息地扩张的关键载体.
研究的目的:
- 为了识别由飞行昆虫传播的高风险树冠病毒.
- 评估多标准决策分析 (MCDA) 和决策支持框架 (DSF) 对 arbovirus 风险评估的有用性.
- 为管理载体传播疾病的公共卫生战略提供信息.
主要方法:
- 一项文献审查评估了54种 arboviruses 与13个风险标准相比.
- 采用多标准决策分析 (MCDA) 技术,根据风险对树冠病毒进行排名.
- 一个使用逻辑树方法的决策支持框架 (DSF) 确定了除了进一步考虑之外的树病毒.
主要成果:
- 发现的突出的数据缺口包括发病率,疾病严重程度和长期影响.
- 主题专家的意见对于评估具有有限病例数据的病原体至关重要.
- MCDA证实,高死亡率/发病率病原体的风险较高,但确定风险值仍然具有挑战性.
结论:
- 无论是MCDA还是DSF方法,都得出了关于树冠病毒风险的类似结论.
- 结合的分析方法提高了树冠病毒风险评估决策的稳定性.
- 需要在疫情爆发期间进一步的实时数据来完善风险值定义.
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