COVID-19 dynamics in Madrid (Spain): A new convolutional model to find out the missing information during the first three waves.

This article presents a novel mathematical model to describe the spread of an infectious disease in the presence of social and health events: it uses 15 compartments, 7 convolution integrals and 4 types of infected individuals, asymptomatic, mild, moderate and severe. A unique feature of this work is that the convolutions and the compartments have been selected to maximize the number of independent input parameters, leading to a 56-parameter model where only one had to evolve over time. The results show that 1) the proposed mathematical model is flexible and robust enough to describe the complex dynamic of the pandemic during the first three waves of the COVID-19 spread in the region of Madrid (Spain) and 2) the proposed model allows us to calculate the number of asymptomatic individuals and the number of persons who presented antibodies during the first waves.

Developing modular training components to support home hospital digital solutions: Results of a Delphi panel.

Background: Home hospitalization (HH) has demonstrated to be a cost-effective alternative with respect ti traditional hospitalization. Digital technologies, such as remote monitoring, have the potential to contribute to its expansion. Tailored educational content is a need to ensure patient safety during the whole admission.