Intelligent Optimization of Diversified Community Prevention of COVID-19 using Traditional Chinese Medicine

TL;DR

This paper introduces an intelligent optimization approach to create diversified Traditional Chinese Medicine prevention programs tailored to community residents, enhancing COVID-19 prevention effectiveness through clustering and expert-driven customization.

Contribution

It proposes a novel combination of fuzzy clustering and heuristic optimization to develop personalized TCM prevention strategies for communities, addressing limitations of uniform programs.

Findings

Effective differentiation of community residents based on health characteristics.

Successful application in 12 communities during COVID-19 peak.

Demonstrated computational efficiency of the proposed method.

Abstract

Traditional Chinese medicine (TCM) has played an important role in the prevention and control of the novel coronavirus pneumonia (COVID-19), and community prevention has become the most essential part in reducing the spread risk and protecting populations. However, most communities use a uniform TCM prevention program for all residents, which violates the "treatment based on syndrome differentiation" principle of TCM and limits the effectiveness of prevention. In this paper, we propose an intelligent optimization method to develop diversified TCM prevention programs for community residents. First, we use a fuzzy clustering method to divide the population based on both modern medicine and TCM health characteristics; we then use an interactive optimization method, in which TCM experts develop different TCM prevention programs for different clusters, and a heuristic algorithm is used to optimize the programs under the resource constraints. We demonstrate the computational efficiency of the proposed method and report its successful application to TCM-based prevention of COVID-19 in 12 communities in Zhejiang province, China, during the peak of the pandemic.