  In the era of big data, standard analysis tools may be inadequate for making
inference and there is a growing need for more efficient and innovative ways to
collect, process, analyze and interpret the massive and complex data. We
provide an overview of challenges in big data problems and describe how
innovative analytical methods, machine learning tools and metaheuristics can
tackle general healthcare problems with a focus on the current pandemic. In
particular, we give applications of modern digital technology, statistical
methods, data platforms and data integration systems to improve diagnosis and
treatment of diseases in clinical research and novel epidemiologic tools to
tackle infection source problems, such as finding Patient Zero in the spread of
epidemics. We make the case that analyzing and interpreting big data is a very
challenging task that requires a multi-disciplinary effort to continuously
create more effective methodologies and powerful tools to transfer data
information into knowledge that enables informed decision making.
