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People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such connections, which we call connected behavior, gives researchers a unique opportunity to predict how one would behave for a future event given their past behaviors. In this work, we propose a framework to conduct connected behavior analysis. Neural stance detection models are trained on Twitter data collected on three seemingly independent topics, i.e., wearing a mask, racial equality, and Trump, to detect people's stance, which we consider as their online behavior in each topic-related event. Our results reveal a strong connection between the stances toward the three topical events and demonstrate the power of past behaviors in predicting one's future behavior. © 2023 ACM.
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Objective To analyze the clinical features of patients with coronavirus disease 2019COVID-19in Wuhan, and we provide reference for further prevention and control of the disease. Methods We collected the clinical data of patients with COVID-19 in Dongxihu Shelter Hospital of Wuhan from February 7 to March 6, 2020. The main symptoms, blood test results, lung CT results, and nucleic acid negative conversion were analyzed. Results A total of 654 patients were included, 17526.76%were mild, and 47973.24%were general. There were 344 males (52.60%), and 310 females (47.40%). The patients were with a mean age of49.36+/-10.30years, and 97 patients (14.83%) with a history of hypertension, 51 patients (7.80%) had a history of diabetes. The main clinical symptoms were fever with 547(83.64%) patients, 186 cases (28.44%) had chills, 15 cases (2.29%) had shiver, 342(52.29%) had fatigue symptoms, 413(63.15%) had cough, 137(20.95%) had chest tightness, and 109(16.67%) had diarrhea during the course of the disease. Blood routine tests of 395 patients, the white blood cell count (WBC) was (4.12+/-1.46)x109/L. The total white blood cell count was normal in 378 cases(95.70%), increased in 7(1.77%), and decreased in 10(2.53%). The lymphocyte percentage was (23.10+/-10.02)%, lymphocyte1.06+/-0.37x109/L. The percentage and count of lymphocyte were low. All the 654 cases were examined by CT, 175 cases (26.76%) showed normal lung CT, 422 cases (64.52%) showed patchy or segmental ground-glass opacity, and 57 cases (8.72%) showed multilobar consolidation, ground-glass shadow coexisted with consolidation or streak shadow. The interval between positive nucleic acid test before admission and negative test after admission was as short as 5 days and as long as 24 days, the average was (12.35+/-3.73) days. Conclusion Fever, coughing, and fatigue are the main symptoms in patients with COVID-19. The typical lung CT findings can be used as the basis for clinical diagnosis and disease evaluation. Patients with mild and common type had better prognosis.Copyright © 2021 Editorial Office of Chinese Journal of Schistosomiasis Control. All rights reserved.
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Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81:1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers' markets, medical workers and other key areas and groups, and ensure early detection and timely response.Copyright © 2022 China Tropical Medicine. All rights reserved.
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Wearing masks is an easy way to operate and popular measure for preventing epidemics. Although masks can slow down the spread of viruses, their efficacy in gathering environments involving heterogeneous person-to-person contacts remains unknown. Therefore, we aim to investigate the epidemic prevention effect of masks in different real-life gathering environments. This study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering environments. The transmission of COVID-19 is simulated using the Monte Carlo simulation method. The heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general society. Furthermore, the heterogeneity of gathering environments causes the epidemic prevention effect of masks to differ. Wearing masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools, high schools, and hospitals. However, the use of masks alone in primary schools and hospitals cannot control outbreaks. In high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse, masks can meet the need for prevention. Given the heterogeneity of individual behavior, if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing, the epidemic prevention effect of masks can be improved. Finally, asymptomatic infection has varying effects on the prevention effect of masks in different environments. The effect can be weakened or eliminated by increasing the usage rate of masks in high schools and workplaces. However, the effect on primary schools and hospitals cannot be weakened. This study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention. © 2022, Higher Education Press.
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Introduction: Guselkumab (GUS), an IL-23p19 antagonist, had greater efficacy than placebo (PBO) in achieving clinical response and clinical remission atWeek (Wk) 12 in the randomized, controlled Phase 2b QUASAR Induction Study 1 (NCT04033445) in patients with moderately to severely active ulcerative colitis (UC).1 Patients who were not in clinical response at Wk 12 received GUS treatment through Wk 24. Here, we report GUS cumulative efficacy and safety results for Induction Study 1. Method(s): Eligible patients had moderately to severely active UC (modified Mayo score of 5 to 9 with a Mayo endoscopy subscore >=2) at baseline. Patients were randomized 1:1:1 to IV GUS 200mg, 400mg, or PBO at Wks 0, 4, and 8. Patients who were not in clinical response to IV induction at Wk 12 received GUS treatment (PBO IV->GUS 200mg IV;GUS 200mg IV->GUS 200mg SC;GUS 400mg IV->GUS 200mg SC) at Wks 12, 16, and 20 and were evaluated at Wk 24 (Figure). Matching IV or SC PBO was administered to maintain the blind. Result(s): Three hundred thirteen patients were randomized and treated at baseline. Demographic and disease characteristics at baseline were similar among the treatment groups, and approximately 50% had a prior inadequate response or intolerance to advanced UC therapy. AtWk 12, clinical response was achieved by 61.4% (62/101) and 60.7% (65/107) of patients randomized to GUS 200mg and GUS 400mg IV vs 27.6 % (29/105) of patients randomized to PBO IV (both p< 0.001). Of the patients in the GUS groups who were not in clinical response at Wk 12, 54.3% (19/35) in the GUS 200mg IV->200mg SC group and 50.0% (19/38) in the GUS 400mg IV->200mg SC group achieved clinical response at Wk 24. Clinical response atWk 12 or 24 was achieved by 80.2% of patients who were randomized to GUS 200mg IV and 78.5% of patients who were randomized to GUS 400mg IV. For patients who received PBO IV->GUS 200mg IV, clinical response at Wk 24 (65.2%) was similar toWk 12 clinical response following GUS 200mg IV induction (61.4%). The most frequent adverse events among all GUS-treated pts (n=274) were anemia (7.7%), headache (5.1%), worsening UC (4.4%), COVID-19 (3.6%), arthralgia (2.9%) and abdominal pain (2.6%) which are consistent with Wk 12 results. Conclusion(s): Overall, approximately 80% of patients randomized to receive GUS achieved clinical response at Wk 12 or 24. Continued treatment with SC GUS allowed 50-54.3% of IV GUS Wk 12 clinical nonresponders to achieve clinical response at Wk 24. No new safety concerns for GUS were identified. (Figure Presented).