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The COVID-19 pandemic represents an unprecedented global crisis. Its global economic, social and health impact is already staggering and will continue to grow. Increased urbanization, global travel, climate change and a generally older and immuno-compromised populations continue to make the problem of pandemic planning and control challenging. Computation, and more broadly, computational thinking, plays a multi-faceted role in supporting global real-time epidemic science, especially because controlled experiments are impossible in epidemiology. High-performance computing, data science, and new sources of massive amounts of data from device-mediated interactions have created unprecedented opportunities to prevent, detect, and respond to pandemics. In this talk, using COVID-19 as an exemplar, I will describe how scalable computing, AI, and data science can play an important role in advancing real-time epidemic science.