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Info-metrics for modeling and inference with complex and uncertain pandemic information

Info-metrics for modeling and inference with complex and uncertain pandemic information

As the world faces the possibility of recurring waves of the current novel coronavirus pandemic, it is critical to identify patterns and dynamics that could be leveraged to decrease future transmission, infection, and death rates. At this stage in the pandemic, data on disease patterns and dynamics are emerging from almost all countries in the world. Variations across countries with respect to coronavirus infection rates, public health policies, social structure, norms, health conditions, environmental policy, climate, and other factors provide us with the data to investigate the impact of different underlying factors and governmental policies on COVID-19 transmission, infection, and death rates.