ABSTRACT
Nowadays, social media platforms generate an immense amount of information in the form of text, images, video, sound, among others. Their capabilities and reliability during adverse situations have made them society's go-to communication method as they continue to operate while more traditional methods fail [1]. With the unexpected arrival of the COVID-19 pandemic, billions of tweets had been generated, bringing both opportunities and challenges to emergency managers when seeking to leverage social media data as a source of information. Therefore, this research investigates how emergency managers could utilize social media data for monitoring public sentiment to enhance their strategic decision-making process. To achieve our end objective, we have adapted a visual analytics framework that has been developed for alerting and monitoring public sentiment during product recalls [2]. The proposed work understands that by developing an alert warning system based on collective sentiment analysis, decision makers will be able to identify scenarios where significant levels of negative or positive sentiment are being disseminated. The alert warning system framework includes concepts on data analytics, natural language processing, and machine learning techniques as mechanisms to generate inferences from social media applications. To illustrate our work, we extracted a sample of 24.7 millions of COVID-19 related tweets from the region of El Paso, TX, which in November 2020 was one of the most dangerous COVID-19 hotspots in the United States [3]. Our results indicate that the adapted framework is an initial step when seeking to assist emergency managers when seeking to utilize social media data;however, it has been found that additional challenges must be addressed before emergency domain decision makers can fully adopt it into their management strategies. © 2022 IEEE.
ABSTRACT
Background/Aims: Digestive symptoms are common in patients with COVID-19. Neverthe-less, the evidence available so far is based on retrospective and observational studies. This prospective multicenter cohort study aimed to describe the frequency, intensity, evolution, and impact of digestive symptoms and complications, during hospitalization and after dis-charge, of patients with COVID-19. Methods: Patients hospitalized due to COVID-19 (posi-tive PCR for SARS-CoV-2) from May to August 2020, were prospectively recruited in 31 centers. Follow-up included the period between admission and 15 days after discharge. Results: 829 patients (mean age 56.7±17.9 years;42% of females) were enrolled in this study. Of these, 7.2% were active smokers and the mean BMI was 29.1±5.7. Proton pump inhibitors were used by 21.5% (n=178). The most prevalent symptoms on admission were diarrhea (39.4%), nausea (27.4%), and abdominal pain (20.7%). Anorexia, a non-specific symptom, was present in 49.8% of hospitalized patients. At discharge and 15 days after discharge, most symptoms resolved, returning to the baseline prevalence of patients (<5%). Digestive complications during admission were infrequent, except for liver injury defined as hypertransaminasemia which was present in 267 patients (32.3%). The mean length of hospital stay was 8 days (5-12) and 13.6% needed ICU admission. Death happened in 5.2%of patients. On multivariate analysis, diarrhea on admission was associated with a shorter hospital stay (<10 days) ORa 0.508 (0.350-0.739) p=0.000. During hospitalization, diarrhea, constipation, and abdominal bloating were associated with shorter hospital stay ORa 0.531 (0.298-0.946) p=0.032, ORa 0.384 (0.167-0.885) p=0.025, ORa 0.163 (0.057-0.466) p= 0.00, respectively.Odynophagia and dysphagia during hospitalization were associated with a higher need for ICU admission, ORa 6.518 (2.255-18.835) p=0.001 and ORa 4.035 (1.453-11.204) p=0.007, respectively. Liver injury during hospitalization was associated with a higher hospital stay (>10 days) ORa 1.442 (1.019-2.041) p=0.039. In the linear regression analysis, the set of GI symptoms and complications, along with age, comorbidity, and respiratory symptoms, were able to predict 43% (R2 0.43) of the observed variability in the speed of ICU admission;in this case, digestive symptoms slowed it down (more days until ICU admission). Conclusions: Gastrointestinal manifestations of COVID-19 are common in hospitalized patients, while complications are infrequent. Gastrointestinal symptoms seemed to predict a shorter hospital stay and slower speed of ICU admission. These tend to resolve to their baseline prevalence 15 days after discharge, while elevated transaminases were associated with a longer hospital stay. Odynophagia and dysphagia during hospitaliza-tion were associated with an increased need for ICU admission.
ABSTRACT
Introduction. The COVID-19 pandemic has impacted the population generating widespread fear due to people's perception that both their health and safety are at risk. Widespread fear, a synonym for social anxiety, is associated with affective intrusive cognitions. Likewise, it is related to symptoms of post-traumatic stress, physiological intrusive and eluding coping responses, and could be associated with long-term vulnerability to develop PTSD. Objective. To assess the association between coping strategies, widespread fear to COVID-19, and symptoms of post-traumatic stress disorder in Mexican population exposed to the SARS-CoV2 pandemic. Method. A cross sectional, empirical, descriptive study through survey research was performed;370 participants were sampled by nationality quotas, and they completed digital self-informed instruments on an on-line psychosocial intervention. Sample size was estimated using a power analysis. Results. Findings showed reliable indicators between physiological coping and PTSD symptoms. There was a 42% variance related to PTSD delayed intrusive cognitive responses, a 40% variance was related to PTSD negative alterations in cognitions and mood, a 31% variance was explained by hyperarousal responses, and a 29% of the variance represented PTSD avoidance symptoms. Widespread fear of COVID-19 was explained by affective behavioral coping strategies linked also to PTSD symptoms. Discussion and conclusion. Research found consistency between findings and theories on emotion-centered strategies, which in turn were are related to affective coping around widespread fear to COVID-19 and avoidance intrusive symptoms, physiological coping with avoidance, considering future community post-traumatic stress traits and anxiety disorders in Mexican communities exposed to the pandemic, linking strategies with community trauma.