Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health - Dini, Guglielmo; Bragazzi, Nicola Luigi; Montecucco, Alfredo; Toletone, Alessandra; Debarbieri, Nicoletta; Durando, Paolo (La Medicina del Lavoro, 2019)
Background: New occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called “work 4.0”, and of the workplace. Objectives: To explore the roles and implications of Big Data in the new occupational medicine settings. Methods: Comprehensive literature search. Results: Big Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques (“molecular Big Data”) and computational infrastructures, including databases, sensors and smart devices (“computational Big Data” and “digital Big Data”). Conclusions: In the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.