Containing Future Epidemics With Trustworthy Federated Systems for Ubiquitous Warning and Response

Abstract

In this paper, we propose a global digital platform to avoid and combat epidemics by providing relevant real-time information to support selective lockdowns. It leverages the pervasiveness of wireless connectivity while being trustworthy and secure. The proposed system is conceptualized to be decentralized yet federated, based on ubiquitous public systems and active citizen participation. Its foundations lie on the principle of informational self-determination. We argue that only in this way it can become a trustworthy and legitimate public good infrastructure for citizens by balancing the asymmetry of the different hierarchical levels within the federated organization while providing highly effective detection and guiding mitigation measures toward graceful lockdown of the society. To exemplify the proposed system, we choose a remote patient monitoring as use case. This use case is evaluated considering different numbers of endorsed peers on a solution that is based on the integration of distributed ledger technologies and NB-IoT (narrowband IoT). An experimental setup is used to evaluate the performance of this integration, in which the end-to-end latency is slightly increased when a new endorsed element is added. However, the system reliability, privacy, and interoperability are guaranteed. In this sense, we expect active participation of empowered citizens to supplement the more usual top-down management of epidemics.

An Analysis of Image Features Extracted by CNNs to Design Classification Models for COVID-19 and Non-COVID-19

“…However, during an outbreak of a disease that causes breathing problems, radiologists may be overwhelmed with medical image analysis [ 2 , 8 , 13 ]. In this context, applying different machine learning models [ 14 – 17 ] during a pandemic is very useful, as it performs the automatic analysis of medical images.…”