This contribution proposes a calibrated model able to predict the risk of contagion in urban district in order to support decision of administration and identify the best strategies during and after the lockdown condition. The objective regards the achievement of a Decision Support System (DSS) to predict the risk of contagion in urban districts by considering epidemic, characteristic and social data of the territory. In addition, the DSS is able to provides different scenarios, based on different administrative policies, in order to analyse the related risks. In order to show the potential of the DSS, different administrative policies (after lockdown condition) are hypothesized: 1) limited reopening of some commercial and productive activities and prohibited moves between different urban districts; 2) partial reopening of some commercial and productive activities and people movement control, 3) the reopening of all commercial and productive activities and freedom of people movement.