Covid-19: A Digital Transformation Approach to a Public Primary Healthcare Environment

Digital transformation in e-health is a well-known challenge problem reported from several studies and from several dimensions. In addition, it has been verified a gap in the utilization of new technologies as differential tool in the war against the Covid-19 pandemic. In this paper, we present an ongoing research effort which is characterized for supporting a digital transformation gap found in a public primary healthcare system. Therefore, it can be seen as an interesting case study approach to tackle some challenges found in Covid-19. Utilizing smart bands by groups of different type of voluntaries, where vital signals were collected in a digital data fashion and then evaluated in public health unit. A recommendation system (RS) algorithm was also developed to understand userś behaviors, based upon their vital signals. In addition, we utilized a simulator software to highlight people movement and predictable scenarios of Covid-19 contamination. This last effort provides a visualization on how the proposal could also help in a real ordinary monitoring scenario. Initial results from this research work indicates a differentiated approach to tackle challenges in digital transformation in a public health scenario, especially in a pandemic. In addition, our experiments illustrate that the adoption of some computational technologies require mainly changes on the present behavior, from governments and people, to be successful approaches to individual protection inside public environments.