Mitigating COVID-19 outbreak via high testing capacity and strong transmission-intervention in the United States

Shi Chen; Qin Li; Song Gao; Yuhao Kang; Xun Shi

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.03.20052720 doi: medRxiv preprint Accordingly, the core of the study is twofold. First, to localize the modeling, we developed a mathematical compartmental model system that simultaneously characterizes the spatiotemporal dynamics of infections in 51 areas (50 states and the District of Columbia). Each state or district has its own model, and all models simultaneously take into account inflows and outflows of interstate travelers. Second, to improve the practical relevance, we chose to use three parameters that can directly correspond to possible practical means to discover, combat, and control the spread of the disease, and quantify their impact on the final output of the model. The three parameters include: 1) the transmission rate b, which corresponds to the local socialdistancing enforcement, e.g., the stay-home order; 2) the detection and reporting rate r, which corresponds to the testing capacity; and 3) the travel ratio α t , which corresponds to the ratio of interstate travel volume compared to that of 2019 during the same period.