Suchar Vasile A, Aziz Noha, Bowe Amanda, Burke Aran, Wiest Michelle M
University of Idaho, Department of Statistical Science, 875 Perimeter Drive MS1104, Moscow, Idaho 83844-1104, USA.
Appl Geogr. 2018 Jan;90:272-281. doi: 10.1016/j.apgeog.2017.10.003. Epub 2017 Dec 6.
The purpose of this study was to investigate the utility of exploratory analytical techniques using publically available data in informing interventions in case of infectious diseases outbreaks. More exactly spatiotemporal and multivariate methods were used to characterize the dynamics of the Ebola Virus Disease (EVD) epidemic in West Africa, and propose plausible relationships with demographic/social risk factors. The analysis showed that there was significant spatial, temporal, and spatiotemporal dependence in the evolution of the disease. For the first part of the epidemic, the cases were highly clustered in a few administrative units, in the proximity of the point of origin of the outbreak, possibly offering the opportunity to stop the spread of the disease. Later in the epidemic, high clusters were observed, but only in Liberia and Sierra Leone. Although not definitely factors of risk, in the setting in which the epidemic arose, our analysis suggests infrastructure, access to and use of health services, and connectivity possibly accelerated and magnified the spread of EVD. Also, the spatial, temporal, and spatiotemporal patterns of epidemic can be clearly shown - with evident application in the early stages of management of epidemics. In particular, we found that the spatial-temporal analytic tool SaTScan may be used effectively during the evolution of an epidemic to identify areas for targeted intervention. In the case of EVD epidemic in West Africa, better data and integration local knowledge and customs may have been more useful to recognize the proper response.
本研究的目的是调查利用公开可用数据的探索性分析技术在传染病暴发时为干预措施提供信息的效用。更确切地说,运用时空和多变量方法来描述西非埃博拉病毒病(EVD)疫情的动态,并提出与人口统计学/社会风险因素之间可能存在的关系。分析表明,该疾病的演变存在显著的空间、时间和时空依赖性。在疫情的第一阶段,病例高度集中在少数几个行政单位,靠近疫情起源点,这可能为阻止疾病传播提供了机会。在疫情后期,观察到高聚集性,但仅在利比里亚和塞拉利昂。尽管不一定是风险因素,但在疫情发生的背景下,我们的分析表明基础设施、卫生服务的可及性和使用情况以及连通性可能加速并扩大了埃博拉病毒病的传播。此外,疫情的空间、时间和时空模式可以清晰显示——在疫情管理的早期阶段有明显应用。特别是,我们发现时空分析工具SaTScan在疫情演变过程中可有效用于识别有针对性干预的区域。在西非埃博拉病毒病疫情中,更好的数据以及整合当地知识和习俗可能对认识正确应对措施更有用。