The new COVID-19 pandemic has challenged policymakers on key issues. Most countries have adopted "lockdown" policies to reduce the spatial spread of COVID-19, but they have damaged the economic and moral fabric of society. Mathematical modeling in non-pharmaceutical intervention policy management has proven to be a major weapon in this fight due to the lack of an effective COVID-19 vaccine. A new hybrid model for COVID-19 dynamics using both an age-structured mathematical model based on the SIRD model and spatio-temporal model in silico is presented, analyzing the data of COVID-19 in Israel. Using the hybrid model, a method for estimating the reproduction number of an epidemic in real-time from the data of daily notification of cases is introduced. The results of the proposed model are confirmed by the Israeli Lockdown experience with a mean square error of 0.205 over 2 weeks. The use of mathematical models promises to reduce the uncertainty in the choice of "Lockdown" policies. The unique use of contact details from 2 classes (children and adults), the interaction of populations depending on the time of day, and several physical locations, allow a new look at the differential dynamics of the spread and control of infection.