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Objective measures for sentinel surveillance in network epidemiology

机译:网络流行病学哨兵监测的客观措施

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Assume one has the capability of determiningwhether a node in a network is infectious or not by probing it. Then problem of optimizing sentinel surveillance in networks is to identify the nodes to probe such that an emerging disease outbreak can be discovered early or reliably. Whether the emphasis should be on early or reliable detection depends on the scenario in question. We investigate three objective measures from the literature quantifying the performance of nodes in sentinel surveillance: the time to detection or extinction, the time to detection, and the frequency of detection. As a basis for the comparison, we use the susceptible-infectious-recovered model on static and temporal networks of human contacts. We show that, for some regions of parameter space, the three objectivemeasures can rank the nodes very differently. Thismeans sentinel surveillance is a class of problems, and solutions need to chose an objectivemeasure for the particular scenario in question. As opposed to other problems in network epidemiology, we draw similar conclusions from the static and temporal networks. Furthermore, we do not find one type of network structure that predicts the objective measures, i.e., that depends both on the data set and the SIR parameter values.
机译:假设具有通过探测网络中的网络中的节点的能力。然后在网络中优化Sentinel监控的问题是识别探测节点,从而可以提前或可靠地发现新兴疾病爆发。重点是早期还是可靠的检测取决于有问题的情景。我们从文献中调查了三种客观措施,这些措施量化了Sentinel监视中节点的性能:检测或灭绝的时间,检测时间和检测频率。作为比较的基础,我们使用易受感染的恢复模型对人为触点的静态和时间网络。我们展示了,对于参数空间的某些区域,三个ObjectiveMeasures可以非常不同地对节点进行排名。 Thismeans Sentinel监视是一类问题,解决方案需要为有问题的特定情景选择一个目标。与网络流行病学中的其他问题相反,我们从静态和时间网络中得出类似的结论。此外,我们没有找到一种类型的网络结构,该网络结构预测客观度量,即,这取决于数据集和SIR参数值。

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