Spreading processes with mutations over multilayer networks.
Spreading processes with mutations over multilayer networks.
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DOI：
10.1073/pnas.2302245120
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发表时间：
2023-06-13
影响因子：
11.1
通讯作者：
Poor, H. Vincent
中科院分区：
文献类型：
--
作者：
Sood, Mansi;Sridhar, Anirudh;Eletreby, Rashad;Wu, Chai Wah;Levin, Simon A.;Yagan, Osman;Poor, H. Vincent
在这项工作中，我们提供了一个数学框架，根据非药物干预措施（例如减少不同社会环境（例如学校和办公室）中身体接触的封锁）来分析变异传染病引发的传播过程。为此，我们分析了多层接触网络上的多菌株传播，其中网络层代表不同的社会环境。我们的结果强调，应根据其对新菌株出现的影响来评估对不同网络层施加/取消干预措施的影响。此外，对现有模型的简化不能同时考虑传染病菌株和网络层的异质性，可能会导致对流行病爆发可能性的错误预测。新型传染病爆发期间的一个关键科学挑战是预测在限制人群互动的对策下流行病的进程如何变化。大多数流行病学模型没有考虑突变和异质性在接触事件类型中的作用。然而，病原体具有因环境变化而发生突变的能力，特别是由于人群对现有菌株的免疫力增强而引起突变，而新病原体菌株的出现对公众健康构成持续威胁。此外，鉴于不同聚集场所（例如学校和办公室）的传播风险不同，可能需要采取不同的缓解策略来控制感染的传播。我们通过同时考虑 i）导致新病原体菌株出现的病原体突变途径，以及 ii）不同环境中的不同传播风险（建模为网络层）来分析多层多菌株模型。假设菌株之间完全交叉免疫，即从任何感染中恢复可以防止感染任何其他病毒（应对 COVID-19 或流感需要放宽这一假设），我们得出了多层多菌株框架的关键流行病学参数。我们证明，对现有模型进行简化以降低应变或网络层的异质性可能会导致错误的预测。我们的结果强调，针对不同接触网络层实施/取消缓解措施（例如学校停课或在家工作政策）的影响应结合其对新病毒株出现可能性的影响进行评估。
In this work, we provide a mathematical framework to analyze spreading processes triggered by mutating contagions in the light of nonpharmaceutical interventions such as lockdowns that reduce physical contact in different social settings (e.g., schools and offices). To this end, we analyze multistrain spreading on multilayer contact networks, where network layers represent different social settings. Our results highlight that imposing/lifting interventions in different network layers should be evaluated in connection with their effect on the emergence of new strains. Moreover, reductions to existing models that do not simultaneously account for heterogeneity in the contagions strains and network layers may lead to incorrect predictions of the likelihood of the emergence of an epidemic outbreak. A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under countermeasures that limit interaction in the population. Most epidemiological models do not consider the role of mutations and heterogeneity in the type of contact events. However, pathogens have the capacity to mutate in response to changing environments, especially caused by the increase in population immunity to existing strains, and the emergence of new pathogen strains poses a continued threat to public health. Further, in the light of differing transmission risks in different congregate settings (e.g., schools and offices), different mitigation strategies may need to be adopted to control the spread of infection. We analyze a multilayer multistrain model by simultaneously accounting for i) pathways for mutations in the pathogen leading to the emergence of new pathogen strains, and ii) differing transmission risks in different settings, modeled as network layers. Assuming complete cross-immunity among strains, namely, recovery from any infection prevents infection with any other (an assumption that will need to be relaxed to deal with COVID-19 or influenza), we derive the key epidemiological parameters for the multilayer multistrain framework. We demonstrate that reductions to existing models that discount heterogeneity in either the strain or the network layers may lead to incorrect predictions. Our results highlight that the impact of imposing/lifting mitigation measures concerning different contact network layers (e.g., school closures or work-from-home policies) should be evaluated in connection with their effect on the likelihood of the emergence of new strains.
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影响因子：
29.9
作者：
Aleta A;Martín-Corral D;Pastore Y Piontti A;Ajelli M;Litvinova M;Chinazzi M;Dean NE;Halloran ME;Longini IM Jr;Merler S;Pentland A;Vespignani A;Moro E;Moreno Y
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影响因子：
12.5
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Gleeson, J. P.
影响因子：
3.9
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影响因子：
5.2
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影响因子：
1.9
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通讯作者：
Levin, SA