An investigation of testing capacity for evaluating and modeling the spread of coronavirus disease.

Despite the consistent recommendation to scale-up the testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), comprehensive analysis on determining the desirable testing capacity () is limited. This study aims to investigate the daily and the percentage of positive cases over the tested population () to evaluate the novel coronavirus disease 2019 (COVID-19) trajectory phase and generate benchmarks on desirable . Data were retrieved from government facilities, including 101 countries and 55 areas in the USA. We have divided the pandemic situations of investigated areas into four phases, i.e., low-level, suppressing, widespread, or uncertain transmission phase. Findings indicate each country should increase TC to roughly two tests per thousand people each day. Additionally, based on , a susceptible-unconfirmed-confirmed-recovered (SUCR) model, which can capture the dynamic growth of confirmed cases and estimate the group size of unconfirmed cases in a country or area, is proposed. We examined our proposed SUCR model for 55 areas in the USA. Results show that the SUCR model can accurately capture the dynamic growth of confirmed cases in each area. By increasing by five times and applying strict control measures, the total number of COVID-19 patients would reduce to 33%.