Mechanisms for Integrating Real Data into Search Game Simulations: An Application to Winter Health Service Pressures and Preventative Policies
Mechanisms for Integrating Real Data into Search Game Simulations: An Application to Winter Health Service Pressures and Preventative Policies
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将真实数据集成到搜索游戏模拟中的机制：冬季卫生服务压力和预防政策的应用
DOI：
10.1101/2023.09.14.23295499
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Chapman M
中科院分区：
文献类型：
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作者：
Chapman M
虽然建模和模拟是探索复杂现象的强大技术，但如果没有适当的现实数据，所获得的任何结果都可能需要广泛的验证。我们认为这个问题的背景下，搜索游戏建模，并建议人口和行为数据被用来配置某些模型参数。我们通过使用超过150，000人的组合数据集来配置特定的搜索游戏模型，该模型捕获与冬季卫生服务压力相关的环境，人口，干预措施和个人行为，从而在实践中展示了这种整合。这些数据的存在使我们能够更准确地探索服务压力干预的潜在影响，我们使用该模型的计算版本进行了33，000次模拟。我们发现，政府的建议是最好的表现在模拟干预，在改善健康，减少健康不平等，从而减少对卫生服务利用的压力。
While modelling and simulation are powerful techniques for exploring complex phenomena, if they are not coupled with suitable real-world data any results obtained are likely to require extensive validation. We consider this problem in the context of search game modelling, and suggest that both demographic and behaviour data are used to configure certain model parameters. We show this integration in practice by using a combined dataset of over 150,000 individuals to configure a specific search game model that captures the environment, population, interventions and individual behaviours relating to winter health service pressures. The presence of this data enables us to more accurately explore the potential impact of service pressure interventions, which we do across 33,000 simulations using a computational version of the model. We find government advice to be the best-performing intervention in simulation, in respect of improved health, reduced health inequalities, and thus reduced pressure on health service utilisation.