Public Policy, Big Data, Network Theory and COVID-19

Abstract

Technology applied to the use of big data has been an important tool to provide necessary information for public health responses to the COVID-19 pandemic, and Colombia has not been the exception. In this document, we analyze two data inputs (digital contact tracking and aggregate mobility analysis, both based on cell pone data), based on which public health measures have been taken in the Latin American country, such as, for example, determining differential control zones within a city, contact tracking, and identification of potential super spreaders. Based on a simple of the data used, we reflect upon the findings reported so far, especially from the perspective of complex networks of contacts and super spreaders, which have been shown to have a critical role in the behavior of the epidemic. The analyses shown here are part of a complex interaction of political and epidemiological contexts which have led to diverse implementations. We highlight that several examples of public policies in Colombia have been informed by this data.