Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty
复制标题
谁、何时筛查：不确定性下网络复发传染病的多轮主动筛查
DOI：
--
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Milind Tambe
中科院分区：
文献类型：
--
作者：
H. Ou;Arunesh Sinha;S. Suen;A. Perrault;A. Raval;Milind Tambe
控制复发性传染病是全球卫生领域的一个重要而复杂的问题。从患者被感染到最终寻求治疗的很长一段时间内，他们的密切接触者都暴露在他们所携带的疾病中，并且很容易受到感染。主动筛查（或病例发现）方法寻求通过筛查已知感染者的接触者来主动发现未确诊的病例，以减少疾病的传播。现有的主动筛查方法的实践经常筛查感染者的所有接触者，需要大量预算。在与印度的一个研究所合作，我们开发了一个模型的主动筛选问题，并提出了一个软件代理，REMEDY。该代理有助于在真实的世界预算限制和有限的联系信息下最大限度地提高主动筛选的有效性。我们的贡献是：（1）提出了一种新的基于多轮网络的不确定性筛选/接触追踪建模方法，并证明了其NP-困难性;（2）提出了两种新的算法：Fulland Fast-REMEDY。Full-REMEDY考虑了未来行动的影响，并提供了高质量的解决方案，而Fast-REMEDY在网络规模上线性扩展;（3）在模拟人类接触的几个真实世界数据集上对Fulland Fast-REMEDY进行评估，以表明它们控制疾病的效果优于基线。我们还表明，软件代理是强大的疾病参数估计错误，和不完整的信息的接触网络。我们的软件代理目前正在部署前进行审查，以提高印度地区结核病主动筛查的效率。
Controlling recurrent infectious diseases is a vital yet complicated problem in global health. During the long period of time from patients becoming infected to finally seeking treatment, their close contacts are exposed and vulnerable to the disease they carry. Active screening (or case finding) methods seek to actively discover undiagnosed cases by screening contacts of known infected people to reduce the spread of the disease. Existing practice of active screening methods often screen all contacts of an infected person, requiring a large budget. In cooperation with a research institute in India, we develop a model of the active screening problem and present a software agent, REMEDY. This agent assists maximizing effectiveness of active screening under real world budgetary constraints and limited contact information. Our contributions are: (1) A new approach to modeling multi-round network-based screening/contact tracing under uncertainty and proof of its NP-hardness; (2) Two novel algorithms, Fulland Fast-REMEDY. Full-REMEDY considers the effect of future actions and provides high solution quality, whereas Fast-REMEDY scales linearly in the size of the network; (3) Evaluation of Fulland Fast-REMEDY on several real-world datasets which emulate human contact to show that they control diseases better than the baselines. We also show that the software agent is robust to errors in estimates of disease parameters, and incomplete information of the contact network. Our software agent is currently under review before deployment as a means to improve the efficiency of district-wise active screening for tuberculosis in India.
DOI：
10.1145/3219617.3219622
发表时间：
2017-11
期刊：
Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems
影响因子：
--
作者：
Jessica Hoffmann;C. Caramanis
通讯作者：
Jessica Hoffmann;C. Caramanis