ABSTRACT
Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among the millions of posts being added every day can be difficult, and in current approaches developing an automatic data analysis project requires time and technical skills. This work presents a new approach for the analysis of social media posts, based on configurable automatic classification combined with Citizen Science methodologies. The process is facilitated by a set of flexible, automatic and open-source data processing tools called the Citizen Science Solution Kit. The kit provides a comprehensive set of tools that can be used and personalized in different situations, particularly during natural emergencies, starting from images and text contained in the posts. The tools can be employed by citizen scientists for filtering, classifying, and geolocating the content with a human-in-the-loop approach to support the data analyst, including feedback and suggestions on how to configure the automated tools, and techniques to gather inputs from citizens. Using flooding scenario as a guiding example, this paper illustrates the structure and functioning of the different tools proposed to support citizens scientists in their projects, and a methodological approach to their use. The process is then validated by discussing three case studies based on the Albania earthquake of 2019, the Covid-19 pandemic, and the Thailand floods of 2021. The results suggest that a flexible approach to tools composition and configuration can support a timely setup of an analysis project by citizen scientists, especially in case of emergencies in unexpected locations. © 2013 IEEE.
ABSTRACT
BACKGROUND AND AIM: Bronchiolitis is the most common lower respiratory illness in young children, mostly caused by Respiratory Syncitial Virus (RSV);PICU admission for respiratory support is required in some cases. The recent Covid-19 pandemic has altered dynamics of viral transmission in the community. We aim to describe if there has been a modification in the number and characteristics of patients admitted to Italian PICUs between the pre-pandemic and post-pandemic period. METHOD(S): Multicenter retrospective observational study based on the national electronic web-based national registry of the Italian Network of PICU Study Group (TIPNet). PICU admissions due to bronchiolitis were compared from 2017 to 2022, considering the seasonal peak periods (October, 1st to April, 30th). RESULT(S): 918 patients have been admitted due to bronchiolitis to Italian PICUs in the above mentioned years. Cumulative yearly admissions are reported in Figure 1. The winter season of 2020-2021 reported a significantly lower number of admissions. RSV was consistently the reported cause in most cases throughout the years except in season 2020-2021, when it was never reported. In the 2020-2021 season, enterovirus was reported in 23% of cases. Covid-19 as cause of bronchiolitis was reported in one case in 2020- 21 and 2 cases in 2021-22. CONCLUSION(S): Covid-19 pandemic, due to possibly multiple factors, has changed the panorama of PICU admissions due to bronchiolitis in Italy. Although research is still ongoing, it seems that Covid itself is not a cause of severe bronchiolitis requiring respiratory support. (Figure Presented).