  We present an open source model that allows quantitative prediction of the
effects of testing on the rate of spread of COVID-19 described by R, the
reproduction number, and on the degree of quarantine, isolation and lockdown
required to limit it. The paper uses the model to quantify the outcomes of
different test types and regimes, and to identify strategies and tests that can
reduce the rate of spread and R value by a factor of between 1.67 and 33.3,
reducing it to between 60% and 3% of the initial value.
