Researching of Improved Greed Algorithm used in COVID-19 Burst Detection

Nowadays, the outbreak of COVID-19 has severely affected people's normal lives. How to detect the source of infectious diseases as soon as possible by observing as few people as possible before the outbreak of the epidemic, to prevent more people from being infected, is a research problem of great practical significance. This problem is a burst detection, and we need to select one of the cases in many hospitals in our country for detecting. This article uses a new method improved from the conventional greedy algorithm to detect this problem and related problems, thus showing the characteristics of "sub-modularity". This algorithm is suitable for large-scale problems, and the simulation results are close to the optimal solution.