Geographic accessibility reflects the opportunity or potential for a specific region to connect with other regions for related socio-economic activities and can be used to evaluate the fairness and rationality of public service facilities. However, most existing healthcare accessibility calculation methods remain at the macro level. They fail to consider changes in residents’ medical strategies or the dynamics based on medical resources, and thus cannot accurately simulate real-world medical behavior. We propose a Geographic Multi-Agent Accessibility (GMAA) method to tackle the Micro Individuals oriented Geographic Accessibility (MIGA) problem. Solving the MIGA problem is not a trivial task because: (1) It is challenging to construct a medical social system from the bottom up at the micro level that can perform heterogeneous modeling of residents and hospitals. (2) Designing strategy update rules for individual residents so that their strategic learning behavior can more realistically simulate the imitation behavior in human society is difficult. (3) It is necessary to redefine healthcare accessibility based on a complex system of individuals. To address these challenges, we first introduced the GMAA method to calculate healthcare accessibility by simulating individual behaviors. Then, we designed a utility function to simulate residents’ behavior, combining evolutionary game theory and The First Law of Geography. Finally, real data from a city in China are collected and compared with classic baseline methods to verify the effectiveness of our method. Our code is available online for reproducibility.
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