A preprint paper coauthored by researchers at Microsoft, the Indian Institute of Technology, and TCS Research (the R&D division of Tata Consultancy Services) describes an AI framework designed to help cities and regions make policy decisions about lockdowns, closures, and physical distancing in response to COVID-19. They claim that because it learns policies automatically as a function of disease parameters like infectiousness, gestation period, duration of symptoms, probability of death, population density, and movement propensity, it's superior to the modeling tools that have thus far been used. If the peer-review process bears out the researchers' claims, the framework could be of use to organizations and governments in the nearly 200 countries with cases of the coronavirus. Asian nations including Singapore and Taiwan have demonstrated that containment strategies like contact tracing, or the process of identifying people who may have come into contact with an infected person, can effectively mitigate COVID-19's spread. The coauthors first generated a graph network -- a model containing objects in which some pairs are related, such that the objects correspond to vertices and each pair of vertices is called an edge -- with 100 nodes and 1,000 individuals.