Intelligent Optimization of Diversified Community Prevention of COVID-19 using Traditional Chinese Medicine
This work addresses the need for personalized TCM-based COVID-19 prevention in communities, though it is incremental as it applies existing optimization techniques to a specific domain.
The authors tackled the problem of uniform Traditional Chinese Medicine (TCM) prevention programs for COVID-19 in communities by proposing an intelligent optimization method to develop diversified programs based on population clustering, resulting in successful application in 12 communities in Zhejiang province during the pandemic peak.
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.