Using Big Data and Network Theory to Inform Decision-making on COVID-19 in Bogotá

After the initial year of the pandemic (2020), a need for Non-Pharmaceutical Interventions (NPIs) that did not imply lockdowns became evident, particularly in locations where human mobility was greatly restricted like in South America. In this research, we propose a multidisciplinary framework to combine findings from diverse academic fields (epidemiology, public health, urban studies, molecular biology) to inform decision making in public health. Furthermore, we designed and implemented NPIs that minimized the effect on human mobility while mitigating viral transmission in Bogota, a city of ~10 million people in a middle-income country. Our results suggest that near real time information can and should be used to design, assess and optimize the effectiveness of public health interventions to reduce disease burden while minimizing socioeconomic disturbances.