Contacts' temporal ordering and dynamics, such as their order and timing, are crucial for understanding the transmission of infectious diseases. Using path-preserving temporal networks, we evaluate the effect of spatial pods (social distancing pods) and temporal pods (meetings' rate reduction) on the spread of the disease. We use our interaction-driven contagion model, instantiated for COVID-19, over history-maintaining random temporal networks as well as over real-world contacts. We find that temporal pods significantly reduce the overall number of infected individuals and slow the spread of the disease. This result is robust under changing initial conditions, such as initial patients' numbers and locations. Social distancing (spatial) pods perform well only at the initial phase of the disease, i.e., with a minimal number of initial patients. Using real-life contact information and extending our interaction-driven model to consider the exposures, we demonstrate the beneficial effect of reducing the temporal density on overall infection rates. We further show that slow-spreading pathogens spread almost as fast-spreading pathogens in dense topologies. Our results show that given the same transmission level, there is a decrease in the disease's rate and spread in less dense networks. Thus, reducing the rate of encounters is more effective than social distancing.

中文翻译：

---

时间网络上基于交互的传染模型表明，降低时间网络密度会降低总感染率

接触者的时间顺序和动态，例如他们的顺序和时间，对于了解传染病的传播至关重要。使用路径保留时间网络，我们评估了空间豆荚（社交距离豆荚）和时间豆荚（会议率降低）对疾病传播的影响。我们使用我们为 COVID-19 实例化的交互驱动的传染模型，通过历史维护随机时间网络以及真实世界的接触。我们发现时间豆荚显着减少了感染个体的总数并减缓了疾病的传播。这个结果在不断变化的初始条件下是稳健的，例如初始患者的数量和位置。社交距离（空间）吊舱仅在疾病的初始阶段表现良好，即，初始患者数量最少。使用现实生活中的联系信息并扩展我们的交互驱动模型以考虑暴露，我们证明了降低时间密度对总体感染率的有益影响。我们进一步表明，在密集拓扑中，缓慢传播的病原体几乎与快速传播的病原体一样传播。我们的研究结果表明，在相同的传播水平下，疾病的发病率和在密度较低的网络中的传播会降低。因此，降低相遇率比保持社交距离更有效。我们进一步表明，在密集拓扑中，缓慢传播的病原体几乎与快速传播的病原体一样传播。我们的研究结果表明，在相同的传播水平下，疾病的发病率和在密度较低的网络中的传播会降低。因此，降低相遇率比保持社交距离更有效。我们进一步表明，在密集拓扑中，缓慢传播的病原体几乎与快速传播的病原体一样传播。我们的研究结果表明，在相同的传播水平下，疾病的发病率和在密度较低的网络中的传播会降低。因此，降低相遇率比保持社交距离更有效。