odels categorize the infected population according to their individual infection or symptom status. While traditional SIR models used a limited set of data elements, the advances in deep learning allowed researchers to use all available data to model, analyze and forecast the virus spread or containment. Accurately modeling the spread of an infection is key to help governments take containment measures. The Global Epidemic and Mobility Gleam 4 model: The Gleam model combines real-world data on human mobility with elaborate stochastic models of disease transmission. It provides analytic and forecasting power to address the challenges faced in developing intervention strategies that minimize the impact of potentially devastating epidemics. It also allows teams to study the efficacy and outcomes of diverse intervention strategies, analyze threats through model scenarios, and forecast newly evolving infectious diseases. Transportation Analysis and Simulation TRANSIMS system: TRANSIMS 5 uses unconventional computational techniques to predict the spread of. It can simulate the travel behavior of each individual for an entire 24-hour period based on the survey data received, which includes statistics on the volume of traffic and congestion, time-dependent delays for the entire road and transit network, and queues at intersections. Tracker map to predict hotspots: Captivity, a healthcare AI company, developed a tracker map 6 that could accurately predict new outbreaks in the United States. The tracker map uses big data models and AI technologies to show the relative risk of infection for people with underlying health conditions in affected areas. This was a helpful tool 7 for public health officials to direct their limited resources to those most in need. AI-backed, superior care for patients Smart field hospitals: Following the outbreak, a Smart field hospital 13 was built in the Hong Shan Sports Center in Wuhan, China. It was staffed with robots responsible for administering medications, taking vitals, and disinfecting the facility. In addition to helping the hospital staff, specialized robots were used to provide entertainment and information to the 200,000 people at the hospital. Thermal sensing drones: South Korea used drones to completely disinfect high epidemic areas. In Inching County, China, the drones delivered medical supplies to centers in need, and thermal sensing drones 14 identified people running fever, potentially infected with the virus. Chatbots as assistants: Several public and private care providers leveraged chatbots 15 to help patients and medical workers. Chatbots were able to respond to a flood of enquiries about symptoms in various languages with a human-touch, enabling people to receive timely, accurate information. The United States Center for Disease Control and Prevention and Microsoft developed a coronavirus self-checker service to help users self-assess their condition and suggest a course of action. Combating misinformation on social media platforms: Social networks were full of misinformation about the pandemic, which led to the general public challenging restrictions, often gathering in large numbers to protest the measures. To counter this, social networks and search engines used personalized information and AI algorithms to identify problematic material on their platforms and have it removed. Drug development with.