Gross Bnaya, Havlin Shlomo
Department of Physics, Bar-Ilan University, 52900 Ramat-Gan, Israel.
Appl Netw Sci. 2020;5(1):95. doi: 10.1007/s41109-020-00337-4. Epub 2020 Nov 26.
Epidemic spread on networks is one of the most studied dynamics in network science and has important implications in real epidemic scenarios. Nonetheless, the dynamics of real epidemics and how it is affected by the underline structure of the infection channels are still not fully understood. Here we apply the susceptible-infected-recovered model and study analytically and numerically the epidemic spread on a recently developed spatial modular model imitating the structure of cities in a country. The model assumes that inside a city the infection channels connect many different locations, while the infection channels between cities are less and usually directly connect only a few nearest neighbor cities in a two-dimensional plane. We find that the model experience two epidemic transitions. The first lower threshold represents a local epidemic spread within a city but not to the entire country and the second higher threshold represents a global epidemic in the entire country. Based on our analytical solution we proposed several control strategies and how to optimize them. We also show that while control strategies can successfully control the disease, early actions are essentials to prevent the disease global spread.
网络上的疫情传播是网络科学中研究最多的动态之一，在实际疫情场景中具有重要意义。尽管如此，实际疫情的动态以及它如何受到感染渠道底层结构的影响仍未得到充分理解。在此，我们应用易感-感染-康复模型，并对最近开发的模仿一个国家城市结构的空间模块化模型上的疫情传播进行解析和数值研究。该模型假设在一个城市内部，感染渠道连接许多不同地点，而城市之间的感染渠道较少，并且通常在二维平面中仅直接连接少数几个相邻城市。我们发现该模型经历两次疫情转变。第一个较低阈值代表城市内部的局部疫情传播，但不会扩散到整个国家，第二个较高阈值代表整个国家的全球疫情。基于我们的解析解，我们提出了几种控制策略以及如何对其进行优化。我们还表明，虽然控制策略可以成功控制疾病，但早期行动对于防止疾病全球传播至关重要。
