Extensive and ongoing COVID-19 testing of populations for viremia and antibodies is expected to play a major role in shaping and managing the process of reopening the states. Mehta’s “Algorithms and Software Tools for Testing and Control of COVID-19,” is an interdisciplinary project bringing together epidemiologists, systems theorists, and data scientists to develop models, algorithms, and software tools to support the state-level PCR (polymerase chain reaction) and serological testing efforts.
His team is developing algorithms to assimilate real-time testing data into networked epidemiological models, and mean-field type control strategies to inform and evaluate the effect of social distancing and other control measures on the progression of the disease. They hope to develop epidemiological models that are better and more realistic in order to better inform testing guidelines, such as what groups to sample, with which tests and with what frequency, and to better evaluate the effects of deploying control measures.
The algorithms will be implemented as efficient, scalable, and open-source software and made available to policy makers and the public on an interactive website, assimilating daily observational data to generate real-time disease maps (with quantified uncertainty) and tools to allow simulation under different control policies. This requires substantial backend computation, with simulation and learning running on the C3.ai/Azure platform.
Mehta, an associate professor in MechSE, co-founded and served as Chief Science Officer of the startup Rithmio; he also worked at United Technologies Research Center. His research is in the areas of mathematical and computational aspects of dynamics and control theory.