Early Warning and Prevention of High-Frequency Emergencies Based on Trusted Data Spaces

Abstract

As the frequency and scope of major diseases continue to rise, the need for an efficient early warning and prevention system in public health has become increasingly urgent. This paper addresses the challenges of preventing and predicting high-frequency and sudden-onset diseases, and proposes a blockchain-based solution to construct a trusted data space. The solution integrates blockchain technology with trusted data space construction, effectively addressing the challenges of data sharing and utilization across regions, departments, and business domains for disease warning and prevention. The experiment showed that the solution on-chain TPS(Transactions Per Second) for spatial data is 1318.7, and the single-node QPS(Queries Per Second) is 1999.2. It meets the requirements for handling high-frequency and sudden public health events, and offers certain advantages in data security, sharing efficiency, and privacy protection. Future research will continue to explore the deep integration and extended applications of cross - chain technology, zero - knowledge proof, and other privacy -preserving computing technologies.