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• W4317809330 startingPage "78" @default.
• W4317809330 abstract "For viruses that can be transmitted by contacts of people, efficiently screening infected individuals is beneficial for controlling outbreaks rapidly and avoiding widespread diffusion, especially during the early stage of a pandemic. The process of virus transmission can be described as virus diffusion in complex networks such as trajectory networks. We propose a strategy formulation framework (SFF) for generating various screening strategies to identify influential nodes in networks. We propose two types of metrics to measure the nodes’ influence and three types of screening modes. Then, we can obtain six combinations, i.e., six strategies. To verify the efficiencies of the strategies, we build a scenario model based on the multi-agent modelling. In this model, people can move according to their self-decisions, and a virtual trajectory network is generated by their contacts. We found that (1) screening people will have a better performance based on their contact paths if there is no confirmed case yet, and (2) if the first confirmed case has been discovered, it is better to screen people sequentially by their influences. The proposed SFF and strategies can provide support for decision makers, and the proposed scenario model can be applied to simulate and forecast the virus-diffusion process." @default.
• W4317809330 created "2023-01-24" @default.
• W4317809330 creator A5004296607 @default.
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• W4317809330 date "2023-01-21" @default.
• W4317809330 modified "2023-09-26" @default.
• W4317809330 title "A Strategy Formulation Framework for Efficient Screening during the Early Stage of a Pandemic" @default.
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• W4317809330 doi "https://doi.org/10.3390/tropicalmed8020078" @default.
• W4317809330 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36828494" @default.
• W4317809330 hasPublicationYear "2023" @default.
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