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The COVID-19 pandemic has been at the center of the lives of many of us for at least a couple of years, during which periods of isolation and lockdowns were common. How all that affected our mental well-being, especially the ones' who were already in distress? To investigate the matter we analyse the online discussions on Sanctioned Suicide, a forum where users discuss suicide-related topics freely. We collected discussions starting from March 2018 (before pandemic) up to July 2022, for a total of 53K threads with 700K comments and 16K users. We investigate the impact of COVID-19 on the discussions in the forum. The data show that covid, while being present in the discussions, especially during the first lockdown, has not been the main reason why new users registered to the forum. However, covid appears to be indirectly connected to other causes of distress for the users, i.e. anxiety for the economy. © 2023 ACM.
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Purpose: Globally, age and some comorbidities have been associ-ated with the risk of more severe outcomes of COVID-19. The purpose of this research is to calculate the hospitalization rate of SARS-CoV-2 positive patients in an Italian Local health Authority (LHA) and to examine whether medical comorbidities encoded through pharmaceutical administrative data are predictors of hospital admission in patients with a positive SARS-CoV-2 naso-pharyngeal swab. Methods: This retrospective observational study was conducted in a LHA of Pescara. Comorbidities were coded through the consumption of drugs, using the WHO's Anatomical Therapeutic Chemical (ATC) classification System. The admission was ascertained by checking the hospital discharge records where generated. Results: During the study period, 1571 patients were tested positive for SARS-CoV-2 oro-and-nasopharyngeal swab. Multivariable logistic analisys showed as predictors of admission an age ≥65 in the total sample (aOR 10.91; 95%CI 6.86-17.36) as well as in the male (aOR 12.64;95%CI 6.42-24.87) and female. (aOR 9.27; 95%CI 4.87-17.66) in SARS-CoV-2 positive patients. Comorbidities assiociated with admission were (GERD) in overall (AdjOR 1.58; 95% CI 1.06-2.34) and male (AdjOR 2.30; 95%CI 1.12-4.72) samples and anticoagulants drugs use in male (AdjOR 3.90; 95% 1.11-13.65) sample, the presence of congestive heart failure (CHF) in female (AdjOR 0.47;95%CI 0.27-0.83) sample results as protective factor. Conclusion: In conclusion, increasing age, male gender and PPI use are positively associated while female gender and CHF-related drug use are negatively associated with hospitalization in SARS-CoV-2 positive patients.
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COVID-19 , SARS-CoV-2 , Humans , Male , Female , COVID-19/epidemiology , COVID-19/therapy , Hospitalization , Comorbidity , HospitalsABSTRACT
Background Current data suggest that SARS-CoV-2 reinfections are rare. Uncertainties remain, however, on the duration of the natural immunity, its protection against Omicron variant, and on the impact of vaccination to reduce reinfection rates. Methods In this retrospective cohort analysis of the entire population of an Italian Region, we followed 1,293,941 subjects from the beginning of the pandemic to the current scenario of Omicron predominance (up to mid-February 2022). We assessed the proportion of reinfections overall, and by demographic and clinical characteristics, time after primary infection, and predominant circulating variant. Cox proportional hazard analysis was used to compute the relative hazards of reinfection. Results After an average of 277 days, we recorded 729 reinfections among 119,266 previously infected subjects (overall rate: 6.1‰), eight COVID-19-related hospitalizations (7/100,000), and two deaths. Importantly, the incidence of reinfection did not vary substantially over time: after 18-22 months from the primary infection, the reinfection rate was still 6.7‰, suggesting that protection conferred by natural immunity may last beyond 12 months. The risk of reinfection was significantly higher among females, unvaccinated subjects, and during the Omicron wave. Conclusions This study confirms and expands previous findings reporting a low risk of SARS-CoV-2 reinfection, and a very low risk of severe or lethal COVID-19 for those who recovered from primary infection, suggesting that the protection conferred by the natural immunity lasts beyond 12 months. Although the marked increase of the reinfection rates during the Omicron wave is concerning, the risk of a secondary severe disease or death remained close to zero. Vaccines were able to significantly reduce the likelihood of reinfection in both pre-Omicron and Omicron waves, although the risk-benefit profile of multiple vaccine doses for this population should be carefully evaluated. Key messages • After primary infection, the risk of SARS-CoV-2 reinfection and of severe/lethal COVID-19 was low, suggesting that natural immunity lasts beyond 12 months. • Despite increasing reinfection rates with Omicron, the risk of a secondary severe/lethal disease was close to zero, and vaccines reduced the likelihood of reinfection before and during Omicron waves.
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We describe the fifth edition of the CheckThat! lab, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to factuality in multiple languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 asks to identify relevant claims in tweets in terms of check-worthiness, verifiability, harmfullness, and attention-worthiness. Task 2 asks to detect previously fact-checked claims that could be relevant to fact-check a new claim. It targets both tweets and political debates/speeches. Task 3 asks to predict the veracity of the main claim in a news article. CheckThat! was the most popular lab at CLEF-2022 in terms of team registrations: 137 teams. More than one-third (37%) of them actually participated: 18, 7, and 26 teams submitted 210, 37, and 126 official runs for tasks 1, 2, and 3, respectively.
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We present the results and the main findings of the NLP4IF-2021 shared tasks. Task 1 focused on fighting the COVID-19 infodemic in social media, and it was offered in Arabic, Bulgarian, and English. Given a tweet, it asked to predict whether that tweet contains a verifiable claim, and if so, whether it is likely to be false, is of general interest, is likely to be harmful, and is worthy of manual fact-checking;also, whether it is harmful to society, and whether it requires the attention of policy makers. Task 2 focused on censorship detection, and was offered in Chinese. A total of ten teams submitted systems for task 1, and one team participated in task 2;nine teams also submitted a system description paper. Here, we present the tasks, analyze the results, and discuss the system submissions and the methods they used. Most submissions achieved sizable improvements over several baselines, and the best systems used pre-trained Transformers and ensembles. The data, the scorers and the leader-boards for the tasks are available at http://gitlab.com/NLP4IF/nlp4if-2021. © 2021 Association for Computational Linguistics.
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We describe the fourth edition of the CheckThat! Lab, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting three tasks related to factuality, and it covers seven languages such as Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Here, we present the task 2, which asks to detect previously fact-checked claims (in two languages). A total of six teams participated in this task, submitted a total of 37 runs, and most submissions managed to achieve sizable improvements over the baselines using transformer based models such as BERT, RoBERTa. In this paper, we describe the process of data collection and the task setup, including the evaluation measures, and we give a brief overview of the participating systems. Last but not least, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research in detecting previously fact-checked claims. © 2022 Copyright for this paper by its authors.
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We present an overview of CheckThat! lab 2022 Task 1, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). Task 1 asked to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics in six languages: Arabic, Bulgarian, Dutch, English, Spanish, and Turkish. A total of 19 teams participated and most submissions managed to achieve sizable improvements over the baselines using Transformer-based models such as BERT and GPT-3. Across the four subtasks, approaches that targetted multiple languages (be it individually or in conjunction, in general obtained the best performance. We describe the dataset and the task setup, including the evaluation settings, and we give a brief overview of the participating systems. As usual in the CheckThat! lab, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research on finding relevant tweets that can help different stakeholders such as fact-checkers, journalists, and policymakers. © 2022 Copyright for this paper by its authors.
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Background: A significant proportion of survivor COVID-19 patients presented sequelae that impact on the quality of life and social-health systems. We described long term sequelae in hospitalized for severe disease patients. Materials and Methods: 143 patients was evaluated at 6 and 12 months after discharge in a prospective study by medical examination, laboratory tests, spirometry, Hamilton test for anxiety and depression, ECG. The results was compared between survivors of the first two pandemic waves. Results: mean age was 66±8 years;90 (63%) was male, median BMI was 26,7±2 Kg/m2. After 6 months 32,1% of patients reported dyspnoea, 35% fatigue, 14% transiet hair loss, 18,8% arthralgia, 10,4% concentration and memory deficit, about 53% anxiety and/or depression. At 12 months symptom prevalence decreased. Prevalent spirometric feature was restrictive. DLCO was altered in about 70% of patients at 6 months. At 12 months the percentage was the same in first wave patients and decreased to 45% in second wave patients. Healthy state was worse in survived of first wave. Conclusions: approximately 1/3 of patients recovered from COVID-19 have sequelae of disease that improved over time. Data analysis are invalidated by patients heterogeneity (background, severity disease and clinical feature, received therapy);its possible that better knowledges in disease management in second pandemic wave had a favorable impact on long-term outcomes.
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The fifth edition of the CheckThat! Lab is held as part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting various factuality tasks in seven languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 focuses on disinformation related to the ongoing COVID-19 infodemic and politics, and asks to predict whether a tweet is worth fact-checking, contains a verifiable factual claim, is harmful to the society, or is of interest to policy makers and why. Task 2 asks to retrieve claims that have been previously fact-checked and that could be useful to verify the claim in a tweet. Task 3 is to predict the veracity of a news article. Tasks 1 and 3 are classification problems, while Task 2 is a ranking one.
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Social media have democratized content creation and have made it easy for anybody to spread information online. However, stripping traditional media from their gate-keeping role has left the public unprotected against biased, deceptive and disinformative content, which could now travel online at breaking-news speed and influence major public events. For example, during the COVID-19 pandemic, a new blending of medical and political disinformation has given rise to the first global infodemic. We offer an overview of the emerging and inter-connected research areas of fact-checking, disinformation, "fake news'', propaganda, and media bias detection. We explore the general fact-checking pipeline and important elements thereof such as check-worthiness estimation, spotting previously fact-checked claims, stance detection, source reliability estimation, detection of persuasion techniques, and detecting malicious users in social media. We also cover large-scale pre-trained language models, and the challenges and opportunities they offer for generating and for defending against neural fake news. Finally, we discuss the ongoing COVID-19 infodemic. © 2022 ACM.
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Background: Telemedicine is becoming a necessary tool for chronic disease management. Thanks to the wide diffusion of devices connecting to the World Wide Web, a large part of the population are now able to access to telemedicine services.Telemedicine is becoming a necessary tool for chronic disease management. Thanks to the wide diffusion of devices connecting to the World Wide Web, a large part of the population are now able to access to telemedicine services. The aim of this survey was to explore the willingness and hesitancy of patients with inflammatory bowel disease (IBD) to the use of telemedicine during COVD-19 outbreak. Methods: A paper-and-pencil questionnaire was proposed to all consecutive patients observed at our tertiary IBD center in San Giovanni Rotondo (Italy) from February to May 2021. The survey investigated 20 items that can be grouped into 5 areas: socio-demographic data, clinical data, informatics competence, devices and network utilized for the internet connection, attitude to the telemedicine, and the impact of COVID-19 pandemic. Results: A total of 156 patients completed the questionnaire (100 males). One hundred forthy-three patients (91.7%) were under 65 years and only 15 (9.6%) were graduates. Forthy-seven patients (30%) were single, 101 married (65%). Eighteen patients (11.5%) felt they had no IT skills. Eight patients (5.1%) had a previous experience of telemedicine. One hundred twenty-three patients (78.8%) consider the support of telemedicine useful for the management of their pathology and 134 (85.9%) would like the Center where they are followed up to have the possibility of offering a telemedicine service. One hundred three patients (66.0%) would like to have a teleconsultation with figures other than the Gastroenterologist. Ninety-seven patients (62.2%) agree that the ongoing coronavirus pandemic has a major impact on the need to implement telemedicine. Regarding the confidence with telemedicine, 106 patients (67.9%) were partially or totally agreeing telemedicine can properly resolve health problems, and 98 (62.8%) agree that technologies guarantee the privacy of the health data. One hundred twenty-five patients (80%) agree that telemedicine should be developed independently of the pandemic, however only 48 patients (31%) believe that telemedicine guarantee the same level of assistance of visit in presence. Conclusion: Italian IBD patients showed a positive attitude towards telemedicine and consider that useful for the management of their disease. The majority of patients would like the center where they are followed up offering a telemedicine service, regardless of the ongoing pandemic. However only one third of patients believe that telemedicine can offer the same level of assistance of in-presence visit.
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The rise of Internet and social media changed not only how we consume information, but it also democratized the process of content creation and dissemination, thus making it easily available to anybody. Despite the hugely positive impact, this situation has the downside that the public was left unprotected against biased, deceptive, and disinformative content, which could now travel online at breaking-news speed and allegedly influence major events such as political elections, or disturb the efforts of governments and health officials to fight the ongoing COVID-19 pandemic. The research community responded to the issue, proposing a number of inter-connected research directions such as fact-checking, disinformation, misinformation, fake news, propaganda, and media bias detection. Below, we cover the mainstream research, and we also pay attention to less popular, but emerging research directions, such as propaganda detection, check-worthiness estimation, detecting previously fact-checked claims, and multimodality, which are of interest to human fact-checkers and journalists. We further cover relevant topics such as stance detection, source reliability estimation, detection of persuasion techniques in text and memes, and detecting malicious users in social media. Moreover, we discuss large-scale pre-trained language models, and the challenges and opportunities they offer for generating and for defending against neural fake news. Finally, we explore some recent efforts aiming at flattening the curve of the COVID-19 infodemic. © 2021 ACM.
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Issue After the announcement of Public Health Emergency of International Concern about COVID19 by WHO, health authorities need to implement strategies to face the emergency. These responses included early diagnosis, patient isolation, quarantine and symptomatic monitoring of contacts. In this context, integrated care and telemedicine are the best instruments for COVID management. Description of the problem The COVID19 epidemic needs a real time integration of epidemiological, clinical and laboratoristic data, in order to better manage patients and to improve public health surveillance. Based on a tool previosly used by GPs for flu vaccination and diabetes integrated care, the Local Health Authority of Pescara, Abruzzo Region, Italy, developed a web-based platform (QuickwebConnect), accessible to public health practitioners (PHP), GPs, infectious diseases physicians and laboratories, in order to integrate information about COVID19 patients. This platform contain individual-level information on patients with laboratory-confirmed COVID19, symptoms, reported onset dates, and basic demographics. Information are in real time accessible to all actors involved in the process. In addition, GPs can use this tool to directly book diagnostic tests for symptomatic or suspected patients. Results With the use of this platform, the management of pandemic emergency was improved, allowing direct management of epidemic data both at person and population level. The real time evaluation of clinical and epidemiological data improved patients care, clinical survellance of COVID19 contacts and development of tailored preventive measure in areas with high incidence. Lessons COVID19 patients care need to be quick, needing the integrate support of different actors. In addition, public health actions have to be supported by strong data. The use of a cost-effective web platform allow physician and PHP to better manage patiens and develope focused interventions. Key messages Integrated care and telemedicine are best instruments for COVID management. The real time evaluation of data aimed to develop tailored preventive measure.
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Background Overall mortality is a relevant indicator of the population burden during COVID-19 pandemic, reflecting the overload and preparedness of the healthcare system. This study aimed to analyse the distribution of deaths in SARS-CoV-2 positive patients between pandemic phases and to evaluate the characteristics of COVID-19 patients deceased during the year. Methods Data on confirmed COVID-19 cases were collected from the recording system of the Department of Prevention of the Local Health Authority of Abruzzo Region, Italy. The course of the epidemic was stratified in 4 phases: the first wave (March-May 2020), the low incidence phase (June-September 2020), the second wave (October 2020-December 2021), and the variants spread phase in our region (January-March 2021). Results From March 2020 to March 2021 we registered 17,082 cases of SARS-CoV-2 infection, of these patients 571 (3.35%) had a fatal outcome. The mortality was the highest during the first ‘peak' phase, interesting the 14.20% of the notified cases, and the lowest during the last phase (2.50%). Mortality due to COVID-19 mainly affected men (54.99%) and geriatric patients (median age: 84;IQR: 75-90). Women dying for SARS-CoV-2 infection had a more advanced median age (87;IQR: 79-92) than men (81;IQR: 73-87). The lowest median age was registered in patients deceased during the low incidence phase (75.5;IQR: 71-82). The median time span, in days, from a SARS-CoV-2 positive test to death was significant lower in the phase 1 (days:10;IQR:4-20) then in phase 4 (days:14;IQR:8-22) (p < 0.001). Conclusions Our results showed that mortality markedly decreased during the COVID-19 epidemic, and this could be likely related to an improved organisation and delivery of care, in addition to a better knowledge of disease treatment. Elderly patients were more likely to progress toward fatal outcome. The healthcare systems should pay special attention to them in order to effectively manage possible future pandemics. Key messages The COVID-19 mortality reduction highlights an improvement of health care;the elderly remains at major risk of death. Providing pandemic prevention and care models focused also on vulnerable groups is a major public health challenge.