模拟针对不同感染动态,采样实践和监视测试中所需结果的聚合优化方法
Catharine Burgess1,2,3, Duan Sriyotee Loy4, John Dustin Loy4
1Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, USA.
概括
选择正确的疾病监测聚合战略对于成本效益至关重要. 我们的研究表明,最好的方法取决于特定的病原体,如牛病毒性腹病毒 (BVDV),以及如何收集样本.
科学领域:
- 兽医流行病学 兽医流行病学
- 诊断试验优化 诊断试验优化
- 传染病监测 传染病监测 传染病监测 传染病监测
背景情况:
- 疾病监测中的策略聚合旨在优化测试经济并降低成本.
- 针对聚合优化的流行假设的可靠性在病原体和监测设计之间有很大差异.
- 由于未知或不可预测的流行情况,低于最佳的聚合可能会导致监测计划成本增加.
研究的目的:
- 评估不同聚合优化方法在最大限度地提高测试经济性和降低成本方面的性能.
- 为了比较各种方法的有效性,在不同的监控计划中接近最佳池大小 (OPS).
- 评估聚合优化方法与监测优先事项,采样实践和病原体感染动态的兼容性.
主要方法:
- 模拟了使用蒙特卡洛模拟的不同聚合优化方法.
- 利用了牛病毒性腹病毒 (BVDV) 和东方 (Theileria orientalis) 监测提交的数据.
- 确定每个提交的真实流行率,OPS和历史流行率.
- 经过试验的固定池大小,历史流行率和流行率估计测试方法.
主要成果:
- 在BVDV和*T. orientalis*监测之间观察到相反的结果.
- 历史流行是BVDV.最可靠的优化方法.
- *T. orientalis* 监测需要显著更多的测试与历史流行相比,真正优化的聚合 (p <0.05).
结论:
- 选择聚合优化方法时,必须考虑病原体感染动态,采样实践和监测计划优先事项的相互作用.
- 没有单一的聚合优化方法是普遍优越的;需要具体的情境评估.
- 准确的流行率估计对于有效和经济的疾病监测至关重要.
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