改善对人类传播疾病风险的监测:利用多模式数据库进行空间分析
Sarah P Maxwell1, Chris Brooks2, Dohyeong Kim1
1School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX, United States.
JMIR public health and surveillance
|August 23, 2023
概括
这项研究将咬遭遇数据与犬类报告和存在的数据整合起来,以绘制传播疾病风险图. 调查结果为公共卫生官员提供了改善的县级监测.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 兽医医学 兽医医学 兽医医学
背景情况:
- 传播疾病 (TBD) 在美国的风险程度在很大程度上是未知的.
- 目前的监测方法 (主动昆虫学,被动公共卫生) 在准确性和报告方面存在局限性.
- 昆虫学测量结果不一致,被动系统报告不足,需要改进风险评估.
研究的目的:
- 使用多式联络数据源评估人类传播疾病 (TBD) 风险.
- 确定和评估各种指标作为人类TBD风险的代理.
- 从一个健康的角度来看,将咬遭遇 (TBEs) 的患者调查数据与其他相关数据库进行整合.
主要方法:
- 采用混合方法的研究策略与三角化技术.
- 进行了为期15个月的基于网络的调查 (从2020年12月开始) 来收集TBE数据.
- 分析了TBE报告 (2000-2021年) 以及狗血清学数据,存在 (Ixodes scapularis,I. pacificus) 和CDC报告的莱姆病病例.
主要成果:
- 调查数据包括30个州144个有资格县的148名受访者中的249个TBE.
- 在报告的TBE和县级官方疾病风险指标之间发现了显著的空间匹配.
- 在报告的TBE和至少一个风险指标 (犬类血清学,CDC莱姆病数据或虫存在) 之间发生了一对一的县级匹配.
结论:
- 将患者的TBE回忆与犬类血清学报告,的存在和官方TBD数据相结合,可以提供细粒度的,县级TBD风险信息.
- 这种方法可以为临床医生和公共卫生官员提供信息,补充现有的监测系统.
- 这些发现支持开发人类TBD风险评估的可靠代理.
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