2022/05/18 by Arasli, Batuhan, Ulukus, Sennur
#Data Structures and Algorithms (cs.DS) #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Populations and Evolution (q-bio.PE) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2205.09520
We consider the dynamic infection spread model that is based on the discrete SIR model which assumes infections to be spread over time via infected and non-isolated individuals. In our system, the main objective is not to minimize the number of required tests to identify every infection, but instead, to utilize the available, given testing capacity T at each time instance to efficiently control the infection spread. We introduce and study a novel performance metric, which we coin as ε-disease control time. This metric can be used to measure how fast a given algorithm can control the spread of a disease. We characterize the performance of dynamic individual testing algorithm and introduce a novel dynamic SAFFRON based group testing algorithm. We present theoretical results and implement the proposed algorithms to compare their performances.