Decreasing the COVID spread of infection among patients at physical isolation hospitals during the coronavirus
pandemic was the main aim of all governments in the world. It was required to increase isolation places in the
hospital’s rules to prevent the spread of infection. To deal with influxes of infected COVID-19 patients’ quick
solutions must be explored. The presented paper studies converting natural rooms in hospitals into isolation
sections and constructing new isolation cabinets using prefabricated components as alternative and quick solutions. Artificial Intelligence (AI) helps in the selection and making of a decision on which type of solution will
be used. A Multi-Layer Perceptron Neural Network (MLPNN) model is a type of artificial intelligence technique
used to design and implement on time, cost, available facilities, area, and spaces as input parameters. The
MLPNN result decided to select a prefabricated approach since it saves 43% of the time while the cost was the
same for the two approaches. Forty-five hospitals have implemented a prefabricated solution which gave
excellent results in a short period of time at reduced costs based on found facilities and spaces. Prefabricated
solutions provide a shorter time and lower cost by 43% and 78% in average values respectively as compared to
retrofitting existing natural ventilation rooms.