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Optimal governance and implementation of vaccination programs to contain the COVID-19 pandemic
arXiv - CS - Computer Science and Game Theory Pub Date : 2020-11-12 , DOI: arxiv-2011.06455
Mahendra Piraveenan, Shailendra Sawleshwarkar, Michael Walsh, Iryna Zablotska, Samit Bhattacharyya, Habib Hassan Farooqui, Tarun Bhatnagar, Anup Karan, Manoj Murhekar, Sanjay Zodpey, K.S. Mallikarjuna Rao, Philippa Pattison, Albert Zomaya, Matjaz Perc

Once a viable vaccine for SARS-CoV-2 has been identified, vaccination uptake will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programs for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programs will likely be scarce in many countries. Vaccine hesitancy can also be expected from some sections of the general public. We emphasize that decision making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritisation and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.

中文翻译:

疫苗接种计划的最佳治理和实施以遏制 COVID-19 大流行

一旦确定了针对 SARS-CoV-2 的可行疫苗,疫苗接种率将决定我们能否成功遏制 COVID-19 大流行。我们认为应该使用博弈论和社交网络模型来指导与疫苗接种计划有关的决策,以获得最佳结果。在引入疫苗后的几个月内,许多国家可能会缺乏疫苗的可用性和运行疫苗接种计划所需的人力资源。预计某些部分公众也会对疫苗犹豫不决。我们强调,在不确定性和不完善信息下的决策,以及只有条件最优的结果,是已建立的博弈论建模的独特优势。所以,
更新日期:2020-11-13
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