The initial spread of the virus in Italy was noted on 22 February, even though some atypical pneumonia cases had been detected earlier. As of 31 August 2020, there were over 25 million confirmed cases globally. COVID-19 was declared a pandemic by the World Health Organization (WHO). It emerged in China and quickly spread globally. These results are unique to Dress-COV and distinguish our system from classical surveillance applications.ĭecember 2019 saw the appearance of a novel coronavirus, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The main results reflect: (a) the individual’s compliance with the tool (b) the security and versatility of the architecture (c) support and promotion of self-management of behavior to accommodate surveillance system delays (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The system uses bot technology of the Telegram application. It aims to establish a lasting link between the user and the tool thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual’s self-empowerment. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens.
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