Manríquez Ronald, Guerrero-Nancuante Camilo, Taramasco Carla
Laboratorio de Investigación Lab[e]saM, Departamento de Matemática y Estadística, Universidad de Playa Ancha, Valparaíso 2340000, Chile.
Escuela de Enfermería, Universidad de Valparaíso, Viña del Mar 2520000, Chile.
Biology (Basel). 2021 Jul 15;10(7):667. doi: 10.3390/biology10070667.
Among the diverse and important applications that networks currently have is the modeling of infectious diseases. Immunization, or the process of protecting nodes in the network, plays a key role in stopping diseases from spreading. Hence the importance of having tools or strategies that allow the solving of this challenge. In this paper, we evaluate the effectiveness of the DIL-Wα ranking in immunizing nodes in an edge-weighted network with 3866 nodes and 6,841,470 edges. The network is obtained from a real database and the spread of COVID-19 was modeled with the classic SIR model. We apply the protection to the network, according to the importance ranking list produced by DIL-Wα, considering different protection budgets. Furthermore, we consider three different values for α; in this way, we compare how the protection performs according to the value of α.
网络当前具有的各种重要应用中，传染病建模是其中之一。免疫，即保护网络中节点的过程，在阻止疾病传播方面起着关键作用。因此，拥有能够应对这一挑战的工具或策略至关重要。在本文中，我们评估了DIL-Wα排序在一个具有3866个节点和6,841,470条边的边加权网络中对节点进行免疫的有效性。该网络取自一个真实数据库，并且使用经典的SIR模型对COVID-19的传播进行了建模。我们根据DIL-Wα生成的重要性排名列表，考虑不同的保护预算，对网络应用保护措施。此外，我们考虑α的三个不同值；通过这种方式，我们比较根据α值保护措施的执行情况。
