Center for Infectious Disease Dynamics, Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA.
BMC Med. 2013 Feb 12;11:35. doi: 10.1186/1741-7015-11-35.
Infectious disease outbreaks in communities can be controlled by early detection and effective prevention measures. Assessing the relative importance of each individual community member with respect to these two processes requires detailed knowledge about the underlying social contact network on which the disease can spread. However, mapping social contact networks is typically too resource-intensive to be a practical possibility for most communities and institutions.
Here, we describe a simple, low-cost method - called collocation ranking - to assess individual importance for early detection and targeted intervention strategies that are easily implementable in practice. The method is based on knowledge about individual collocation which is readily available in many community settings such as schools, offices, hospitals, and so on. We computationally validate our method in a school setting by comparing the outcome of the method against computational predictions based on outbreak simulations on an empirical high-resolution contact network. We compare collocation ranking to other methods for assessing the epidemiological importance of the members of a population. To this end, we select subpopulations of the school population by applying these assessment methods to the population and adding individuals to the subpopulation according to their individual rank. Then, we assess how suited these subpopulations are for early detection and targeted intervention strategies.
Likelihood and timing of infection during an outbreak are important features for early detection and targeted intervention strategies. Subpopulations selected by the collocation ranking method show a substantially higher average infection probability and an earlier onset of symptoms than randomly selected subpopulations. Furthermore, these subpopulations selected by the collocation ranking method were close to the optimum.
Our results indicate that collocation ranking is a highly effective method to assess individual importance, providing critical low-cost information for the development of sentinel surveillance systems and prevention strategies.
社区中的传染病暴发可以通过早期检测和有效的预防措施来控制。评估每个社区成员在这两个过程中的相对重要性，需要详细了解疾病传播所依赖的潜在社会接触网络。然而，绘制社会接触网络通常需要大量资源，对于大多数社区和机构来说，这是不切实际的。
在这里，我们描述了一种简单、低成本的方法——称为共现排序，用于评估个体在早期检测和有针对性的干预策略方面的重要性，这些策略在实践中易于实施。该方法基于个体共现的知识，这种知识在许多社区环境中（如学校、办公室、医院等）很容易获得。我们通过将该方法的结果与基于经验高分辨率接触网络上的暴发模拟的计算预测进行比较，在学校环境中对我们的方法进行了计算验证。我们将共现排序与评估人群中成员的流行病学重要性的其他方法进行了比较。为此，我们通过将这些评估方法应用于人群并根据个体排名向子群体添加个体，选择学校人群的子群体。然后，我们评估这些子群体在早期检测和有针对性的干预策略方面的适用性。
在暴发期间感染的可能性和时间是早期检测和有针对性的干预策略的重要特征。共现排序方法选择的子群体的平均感染概率和症状出现时间明显高于随机选择的子群体。此外，这些通过共现排序方法选择的子群体非常接近最优。
我们的结果表明，共现排序是一种评估个体重要性的高效方法，可以为哨兵监测系统和预防策略的制定提供关键的低成本信息。
