Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks
Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks
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DOI：
10.1109/tac.2020.2985300
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发表时间：
2021-02-01
影响因子：
6.8
通讯作者：
Leonard, Naomi Ehrich
中科院分区：
文献类型：
--
作者：
Pagliara, Renato;Leonard, Naomi Ehrich
传染过程，如传染病、社会行为或计算机病毒的传播，影响生物、社会和技术系统。网络上的大种群和有限种群的流行模型已被用于理解和控制瞬态和稳态行为。一般认为，从感染中恢复后，每个病原体要么恢复到原来的易感状态，要么获得对再次感染的完全免疫。我们研究了网络SIRI（易感-感染-恢复-感染）模型，这是一个传染病过程在异质媒介网络上传播的流行病模型，可以调整其对再感染的易感性。该模型对现有模型进行了推广，以适应实际情况，即在首次接触感染后，主体获得部分或受损的免疫。我们证明了模型参数和网络结构区分无感染、流行、地方性和双稳态四种动态状态的充分必要条件。对于传统模型中没有考虑到的双稳态状态，我们展示了在看似趋同于无感染人群之后，流行病如何迅速复苏。我们使用该模型及其预测能力来展示如何设计控制策略来减轻有问题的传染性行为。
Contagious processes, such as spread of infectious diseases, social behaviors, or computer viruses, affect biological, social, and technological systems. Epidemic models for large populations and finite populations on networks have been used to understand and control both transient and steady-state behaviors. Typically it is assumed that after recovery from an infection, every agent will either return to its original susceptible state or acquire full immunity to reinfection. We study the network SIRI (Susceptible-Infected-Recovered-Infected) model, an epidemic model for the spread of contagious processes on a network of heterogeneous agents that can adapt their susceptibility to reinfection. The model generalizes existing models to accommodate realistic conditions in which agents acquire partial or compromised immunity after first exposure to an infection. We prove necessary and sufficient conditions on model parameters and network structure that distinguish four dynamic regimes: infection-free, epidemic, endemic, and bistable. For the bistable regime, which is not accounted for in traditional models, we show how there can be a rapid resurgent epidemic after what looks like convergence to an infection-free population. We use the model and its predictive capability to show how control strategies can be designed to mitigate problematic contagious behaviors.