Epidemic spread on patch networks with community structure
Epidemic spread on patch networks with community structure
复制标题
具有社区结构的补丁网络上的疫情传播
DOI：
10.1016/j.mbs.2023.108996
复制
发表时间：
2023-04-27
影响因子：
4.3
通讯作者：
Gardner, Allison M.
中科院分区：
文献类型：
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作者：
Lieberthal, Brandon;Soliman, Aiman;Gardner, Allison M.
预测和准备疾病流行的轨迹依赖于对影响地方和全球空间尺度传播率的环境和社会经济因素的了解。本文讨论了具有社区结构的人类集合种群网络上的流行病爆发的模拟，例如国家边界内的城市，其感染率在社区内和社区之间都不同。通过下一代矩阵，我们在数学上证明了这些社区的结构，抛开所有其他因素，如疾病毒力和人类决策，对整个网络的疾病繁殖率有着深远的影响。在高模块化网络中，相邻社区之间的隔离程度很高，疾病流行往往在高风险社区迅速传播，而在其他社区传播非常缓慢，而在低模块化网络中，流行病在整个网络中以稳定的速度传播，很少考虑感染率的变化。网络模块化和有效繁殖数之间的相关性在人口流动率高的人群中更强。这意味着社区结构、人类扩散率和疾病繁殖数量都是相互交织的，它们之间的关系可能会受到缓解策略的影响，例如限制高风险社区之间和内部的流动。然后，我们通过数值模拟测试的有效性，运动限制和疫苗接种策略，在减少疫情的高峰流行和传播面积。我们的研究结果表明，这些策略的有效性取决于网络的结构和疾病的属性。例如，疫苗接种策略在具有高扩散率的网络中最有效，而移动限制策略在具有高模块化和高感染率的网络中最有效。最后，我们为流行病建模者提供了关于理想空间分辨率的指导，以平衡准确性和数据收集成本。
Predicting and preparing for the trajectory of disease epidemics relies on a knowledge of environmental and socioeconomic factors that affect transmission rates on local and global spatial scales. This article discusses the simulation of epidemic outbreaks on human metapopulation networks with community structure, such as cities within national boundaries, for which infection rates vary both within and between communities. We demonstrate mathematically, through next-generation matrices, that the structures of these communities, setting aside all other considerations such as disease virulence and human decision-making, have a profound effect on the reproduction rate of the disease throughout the network. In high modularity networks, with high levels of separation between neighboring communities, disease epidemics tend to spread rapidly in high-risk communities and very slowly in others, whereas in low modularity networks, the epidemic spreads throughout the entire network as a steady pace, with little regard for variations in infection rate. The correlation between network modularity and effective reproduction number is stronger in population with high rates of human movement. This implies that the community structure, human diffusion rate, and disease reproduction number are all intertwined, and the relationships between them can be affected by mitigation strategies such as restricting movement between and within high-risk communities. We then test through numerical simulation the effectiveness of movement restriction and vaccination strategies in reducing the peak prevalence and spread area of outbreaks. Our results show that the effectiveness of these strategies depends on the structure of the network and the properties of the disease. For example, vaccination strategies are most effective in networks with high rates of diffusion, whereas movement restriction strategies are most effective in networks with high modularity and high infection rates. Finally, we offer guidance to epidemic modelers as to the ideal spatial resolution to balance accuracy and data collection costs.