美国大陆以外的国际旅行和传染病影响快速查看工具

Courtney Corley, Mary J. Lancaster, R. Brigantic, Brenda Kunkel, George A. Muller, Taylor McKenzie
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引用次数: 1

摘要

本文描述了一种工具,该工具将允许公共卫生分析人员估计国家一级的传染病风险,作为不同国际运输模式的功能。该模型的重点是源自拉丁美洲或加勒比地区的霍乱疫情,但它也可以扩展到考虑其他病原体。这项工作利用了以前与疾病控制和预防中心合作的工作,开发了国际旅行社区影响(it - ci)模型,该模型分析和评估潜在的国际疾病爆发,然后估计对美国社区和整个国家的相关影响,并将其定位为美国大陆以外的使用(OCONUS)。为简洁起见,我们将此改进后的模型称为oil - ci。首先,我们开发了拉丁美洲和加勒比地区二级行政级别边界的可操作元人口空间霍乱模型。其次,我们开发了一个鲁棒的人类航空函数,这对于近似元种群模型中的混合模式至关重要。在目前介绍的原型版本中,OIT-CI模拟了起源于拉丁美洲或加勒比国家并通过航空运输路线传播的霍乱疫情。疾病传播在国家一级使用具有基于人口、地理空间和人类交通数据的连通性函数的补丁模型进行建模。我们还确定了用于估计每个国家的水和卫生相关基础设施能力的数据,以包括对疾病传播的这种潜在影响。国际霍乱组织利用这些数据和建模结构来估计每个国家一致的霍乱风险,作为发病率的函数。这一估计将通过提供霍乱暴发在二级边界(即州或行政区域)拉丁美洲和加勒比国家内部起源并向其蔓延的数量级风险估计(例如1%、10%、50%、100%)来完成。为了创造一个既有用又令人满意的产品,OIT-CI最终用户的反馈将被纳入模型软件和可视化设计中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Outside the continental United States international travel and contagion impact quick look tool
This paper describes a tool that will allow public health analysts to estimate infectious disease risk at the country level as a function of different international transportation modes. The prototype focuses on a cholera epidemic originating within Latin America or the Caribbean, but it can be expanded to consider other pathogens as well. This effort leverages previous work in collaboration with the Centers for Disease Control and Prevention to develop the International Travel to Community Impact (IT-CI) model, which analyzes and assesses potential international disease outbreaks then estimates the associated impacts to U.S. communities and the nation as a whole and orient it for use Outside the Continental United States (OCONUS). For brevity, we refer to this refined model as OIT-CI. First, we developed an operationalized meta-population spatial cholera model for Latin America and the Caribbean at the secondary administrative-level boundary. Secondly, we developed a robust function of human airline critical to approximating mixing patterns in the meta-population model. In the prototype version currently presented here, OIT-CI models a cholera epidemic originating in a Latin American or Caribbean country and spreading via airline transportation routes. Disease spread is modeled at the country level using a patch model with a connectivity function based on demographic, geospatial, and human transportation data. We have also identified data to estimate the water and health-related infrastructure capabilities of each country to include this potential impact on disease transmission. OIT-CI utilizes these data and modeling constructs to estimate the cholera risk, as a function of attack rate, for each country consistent [1]. This estimation will be completed by providing an order of magnitude risk estimate (e.g., 1 percent, 10 percent, 50 percent, 100 percent) for a cholera outbreak originating within and spreading to Latin American and Caribbean countries at secondary level boundaries (i.e., states or administrative districts). To create a product that is both useful and desirable, feedback from end users of OIT-CI will be incorporated into the model software and visualization design.
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