Various key performance indicators (KPIs) are communicated daily to the public by health authorities since the COVID-19 pandemic has started. “Upstream” KPIs mainly include the incidence of detected Sars-CoV-2-positive cases in the population, and “downstream” KPIs include daily hospitalizations, intensive care unit admissions and fatalities. Whereas “downstream” KPIs are essential to evaluate and adapt hospital organization, “upstream” KPIs are the most appropriate to decide on the strength of restrictions such as lockdown set up and evaluate their effectiveness. Here, we suggested tools derived from pharmacokinetic calculations to improve understanding the epidemic progression. From the time course of the number of new cases of SARS-coV-2 infection in the population, it is possible to calculate the infection rate constant using a simple linear regression and determine its corresponding half-life. This epidemic regression half-life is helpful to measure the potential benefits of restriction measures and to estimate the adequate duration of lockdown if implemented by policymakers in relation to the decided public health objectives. In France, during the first lockdown, we reported an epidemic half-life of 10 days. Our tools allow clearly acknowledging that the zero-COVID target is difficult to reach after a period of lockdown as seven half-lives are required to clear 99.2% of the epidemic and more than 10 half-lives to almost reach the objective of eliminating 100% of the contaminations.