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Preprint in English | medRxiv | ID: ppmedrxiv-20080341


BackgroundHealthcare is responding to the COVID-19 pandemic through the fast adoption of digital solutions and advanced technology tools. The aim of this study is to describe which digital solutions have been reported in the scientific literature and to investigate their potential impact in the fight against the COVID-19 pandemic. MethodsWe conducted a literature review searching PubMed and MedrXiv with terms considered adequate to find relevant literature on the use of digital technologies in response to COVID-19. We developed an impact score to evaluate the potential impact on COVID-19 pandemic of all the digital solutions addressed in the selected papers. ResultsThe search identified 269 articles, of which 145 full-text articles were assessed and 124 included in the review after screening and impact evaluation. Of selected articles, most of them addressed the use of digital technologies for diagnosis, surveillance and prevention. We report that digital solutions and innovative technologies have mainly been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles we identified numerous suggestions on the use of artificial-intelligence-powered tools for the diagnosis and screening of COVID-19. Digital technologies are useful also for prevention and surveillance measures, for example through contact-tracing apps or monitoring of internet searches and social media usage. DiscussionIt is worth taking advantage of the push given by the crisis, and mandatory to keep track of the digital solutions proposed today to implement tomorrows best practices and models of care, and to be ready for any new moments of emergency.

Preprint in English | medRxiv | ID: ppmedrxiv-20066183


BackgroundIn the early phases of a new pandemic, identifying the most relevant evidence and quantifying which studies are shared the most can help researchers and policy makers. The aim of this study is to describe and quantify the impact of early scientific production in response to COVID-19 pandemic. MethodsThe study consisted of: 1) review of the scientific literature produced in the first 30 days since the first COVID-19 paper was published; 2) analysis of papers metrics with the construction of a "Computed-Impact-Score" (CIS) that represents a unifying score over heterogeneous bibliometric indicators. In this study we use metrics and alternative metrics collected into five separate categories. On top of those categories we compute the CIS. Highest CIS papers are further analyzed. Results239 papers have been included in the study. The mean of citations, mentions and social media interactions resulted in 1.63, 10 and 1250, respectively. The paper with highest CIS resulted "Clinical features of patients[...]" by Chaolin Huang et al., which rated first also in citations and mentions. This is the first paper describing patients affected by the new disease and reporting data that are clearly of great interest to both the scientific community and the general population. ConclusionsThe early response of scientific literature during an epidemic does not follow a pre-established pattern. Being able to monitor how communications spread from the scientific world toward the general population using both traditional and alternative metric measures is essential, especially in the early stages of a pandemic.