Abstract
Big data epidemiology facilitates pandemic response by providing data-driven insights by utilizing big data tools that differ from traditional methods. Aspects regarding ‘garbage in, garbage out’, such as insufficient data, inaccessibility of data, missing data, uncertainty in handling data and bias in analysis or common findings are addressable by combining techniques across disciplines.
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