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Agent-based simulation for vaccination networks design and analysis: preliminary gaps
Ifac Papersonline ; 55(10):2902-2907, 2022.
Article in English | Web of Science | ID: covidwho-2126506
ABSTRACT
During an epidemic or a pandemic emergency, various approaches are undertaken to contain the infectious disease spread. Some of the most common interventions are lockdowns, social distancing, contact tracing and the use of personal protective equipment. However, whenever available, the most helpful intervention is the administration of vaccinations. Countermeasures need to be taken as quickly as possible in emergencies, but predicting their full consequences and effects is often difficult, mainly because there is no room for trial-and-error approaches. Simulation - in its different implementations - represents a useful approach for modelling and analysing reality and predicting the evolution of a real-world system. Agent-based models could be particularly beneficial as they allow for modelling each individual as a distinct entity, thereby enabling the evaluation of the effects of public policies in the field of interest. This paper reviews the existing literature on agent-based simulation for vaccine distribution and administration. This work highlights areas where agent-based simulation has been most utilised and areas that could be explored further. Specifically, the most significant gaps are the lack of application of agent-based simulations to vaccine distribution networks and the lack of consideration given to resources requirements and costs associated with alternative vaccine administration methods to citizenship. Copyright (C) 2022 The Authors.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: Ifac Papersonline Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: Ifac Papersonline Year: 2022 Document Type: Article