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 $\epsilon$-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.

翻译：我们认为,基于独立的SIR模型的动态感染传播模式,该模型假定感染通过受感染和非孤立的个人长期传播。在我们的系统中,主要目标不是最大限度地减少确定每一种感染所需的测试数量,而是利用现有的测试能力,每次测试能力都特特元,以有效控制感染的传播。我们引入并研究一种新的性能衡量标准,我们把它当作美元/日元疾病控制时间。这一衡量标准可用于衡量特定算法控制疾病传播的速度。我们描述动态个人测试算法的性能,并引入新的动态的SAFFFRON集体测试算法。我们提出理论结果,并采用拟议的算法来比较其性能。