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State and local governments have imposed health policies to contain the spread of COVID-19 since it had a serious impact on human daily life. However, the public stance on these measures may be time-varying. It is likely to escalate the infection in the area where the public is negative or resistant. To take advantage of the correlation between public stance on health policies and the COVID-19 statistics, we propose a novel framework, Multitask Learning Neural Networks for Pandemic Prediction with Public Stance Enhancement (MP3), which is composed of three modules: (1) Stance awareness module to make stance detection on health policies from users' tweets in social media and convert them into a stance time series. (2) Temporal feature extraction module that applies Convolution Neural Network and Recurrent Neural Network to extract and fuse local patterns and long-term correlations from COVID-19 statistics. Moreover, a Stance Latency-aware Attention is proposed to capture dynamic social effects and fuse them with temporal features. (3) Multi-task prediction module to adopt Graph Convolution Network to model the spread of pandemic and employ multi-task learning to simultaneously predict COVID-19 statistics and the trend of public stance on health policies. The proposed framework outperforms state-of-the-art baselines on both confirmed cases and deaths prediction tasks. © 2022 IEEE.
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Objective: To retrospectively analyze the clinical data of 52 patients with coronavirus disease-2019 COVID-19 and explore the clinical efficacy of modified Sanxiaoyin on mild/moderate COVID-19 patients. Method(s): The propensity score matching method was used to collect the clinical data of mild or moderate COVID-19 patients enrolled in the designated hospital of the Second Hospital of Jingzhou from December 2019 to May 2020. A total of 26 eligible patients who were treated with modified Sanxiaoyin were included in the observation group,and the 26 patients treated with conventional method were the regarded as the control. The disappearance of clinical symptoms,disappearance time of main symptoms,efficacy on traditional Chinese medicineTCMsymptoms,hospitalization duration,laboratory test indicators,and CT imaging changes in the two groups were compared. Result(s): The general data in the two groups were insignificantly different and thus they were comparable. After 7 days of treatment,the disappearance rate of fever,cough, fatigue,dry throat,anorexia,poor mental state,and poor sleep quality in the observation group was higher than that in the control groupP<0.05,and the difference in the disappearance rate of expectoration and chest distress was insignificant. For the cases with the disappearance of symptoms,the main symptomsfever, cough,fatigue,dry throat,anorexia,chest distressdisappeared earlier in the observation group than in the control groupP<0.01. After 7 days of treatment,the scores of the TCM symptom scale of both groups decreasedP<0.01,and the decrease of the observation group was larger that of the control groupP<0.01. All patients in the two groups were cured and discharged. The average hospitalization duration in the observation group12.79+/-2.68dwas shorter than that in the control group15.27+/-3.11dP<0.01. The effective rate in the observation group92.31%,24/26was higher than that in the control group76.92%,20/26. After 7 days of treatment,the lymphocyteLYMcount increasedP<0.05,and white blood cellWBCcount and neutrophilNEUTcount decreased insignificantly in the two groups. Moreover,levels of C-reactive protein CRP,erythrocyte sedimentation rateESR,and procalcitoninPCTreduced in the two groups after treatmentP<0.01and the reduction in the observation group was larger than that in the control group P<0.01. Through 7 days of treatment,the total effective rate on pulmonary shadow in the observation group 90.00%,18/20was higher than that in the control group77.27%,17/22P>0.05and the improvement of lung shadow in the observation group was better than that in the control groupP<0.01. Conclusion(s):Modified Sanxiaoyin can significantly alleviate fever,cough,fatigue,anorexia,chest distress,poor sleep quality,and other symptoms of patients with mild or moderate COVID-19,improve biochemical indicators,and promote the recovery of lung function. This paper provides clinical evidence for the application of modified Sanxiaoyin in the treatment of mild or moderate COVID-19.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.
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The analysis of the daily spatial patterns of near-surface Nitrogen dioxide (NO2) concentrations can assist decision makers mitigate this common air pollutant in urban areas. However, comparative analysis of NO2 estimates in different urban agglomerations of China is limited. In this study, a new linear mixed effect model (LME) with multi-source spatiotemporal data is proposed to estimate daily NO2 concentrations at high accuracy based on the land-use regression (LUR) model and Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) products. In addition, three models for NO2 concentration estimation were evaluated and compared in four Chinese urban agglomerations from 2018 to 2020, including the COVID-19 closed management period. Each model included a unique combination of methods and satellite NO2 products: ModelⅠ: LUR model with OMI products;Model Ⅱ: LUR model with TropOMI products;Model Ⅱ: LME model with TropOMI products. The results show that the LME model outperformed the LUR model in all four urban agglomerations as the average RMSE decreased by 16.09% due to the consideration of atmospheric dispersion random effects, and using TropOMI instead of OMI products can improve the accuracy. Based on our NO2 estimations, pollution hotspots were identified, and pollution anomalies during the COVID-19 period were explored for two periods;the lockdown and revenge pollution periods. The largest NO2 pollution difference between the hotspot and non-hotspot areas occurred in the second period, especially in the heavy industrial urban agglomerations. © 2022 Elsevier Ltd
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COVID-19 has had a profound impact on the lives of all human beings. Emerging technologies have made significant contributions to the fight against the pandemic. An extensive review of the application of tech-nology will help facilitate future research and technology development to provide better solutions for future pan-demics. In contrast to the extensive surveys of academic communities that have already been conducted, this study explores the IT community of practice. Using GitHub as the study target, we analysed the main functionalities of the projects submitted during the pandemic. This study examines trends in projects with different functionalities and the relationship between functionalities and technolo-gies. The study results show an imbalance in the number of projects with varying functionalities in the GitHub community, i.e., applications account for more than half of the projects. In contrast, other data analysis and AI projects account for a smaller share. This differs significantly from the survey of the academic community, where the findings focus more on cutting-edge technologies while projects in the community of practice use more mature technologies. The spontaneous behavior of developers may lack organization and make it challenging to target needs.
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Objective To investigate the correlation between Global Health Security Index (GHSI) and the epidemic situation of COVID-19 and to explore the value of GHSI. Methods A crosssectional study of 159 countries from an open database was conducted. Analyze the correlation of GHSI with the COVID-19 pandemic with Spearman and plot the correlation matrix. Fitted multiple linear regression models controlled for variables such as socioeconomic and health conditions in countries, and further studied the association of GHSI with COVID-19 pandemic outcome indicators. Results The mean total GHSI score of the 159 countries in 2021 was (41. 19+/-13. 41), with a minimum of 16. 10 (Yemen) and a maximum of 75.90 (The United States). As of 31 December 2021, the crude case fatality rate of COVID-19 in 159 countries was 0. 02 (0. 01, 0. 03), with a minimum <0. 01 (Bhutan) and a maximum of 0. 20 (Yemen). The total number of confirmed cases per million population was 50 844.42 (5 807. 88, 101 572.70), with a minimum of 22.26 (Republic of Vanuatu) and a maximum of 251 608. 38 (Slovakia). The total number of deaths per million population was 590. 71 (105. 66,1533. 20), with a minimum of 3. 10 (Burundi) and a maximum of 6 075. 95 (Peru). Multiple linear regression analysis results showed that the Detect score of GHS1 was negatively correlated with the total confirmed cases per million population (fi =-0. 34, P =0. 038) and the total deaths per million population (fi = -0.42, P = 0. 025);the Norms score of GHS1 was negatively correlated with the total confirmed cases per million population (fi = -0. 49, P = 0. 041), and the Health score of GHS1 was positively correlated with the total deaths per million population (fi =0.65, P = 0.003). Risk score of GHS1 was inversely correlated with case fatality rate(fi = -0. 91, P = 0. 044). Conclusion The GHS 1ndex has limited value in assessing a country's capacity to respond to the COV1D-19 pandemic. Nevertheless, it has potential value in others. Copyright © 2022, Publication Centre of Anhui Medical University. All rights reserved.
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Objectives: The novel coronavirus (COVID-19) is still recurring so far. Considering that a great number of patients do examination in the same room and thus are exposed to high risks of cross infection, we should promote the epidemic prevention in the radiology department to prevent cross infection and another outbreak. Therefore, this article aims to share the experience and protocols of the radiology department of our hospital so as to help more hospitals and their radiology medical staff in epidemic prevention. Methods: We firstly collected three major epidemic prevention policies formulated by the radiology department since the outbreak, and then drew the schematic diagrams of patients' treatment routes under each measure, including the infection control team, the reconfiguration of the radiology department and the Examination procedures for patients with COVID-19. After three stages, we finally provide a specific machine for patients with COVID-19 to examine. Results: From January 18, 2020, our hospital has received 113 patients with COVID-19, among which 112 patients were discharged and 1 were dead. The total number of outpatients with fever-CT examinations was 2870, that of inpatients were 477. The number of DR exposures was 87, that of US examinations were 207, and that of MRI examinations was 148. No medical workers in the radiology department were diagnosed with COVID-19. Conclusions: Imaging examination has been an indispensable diagnostic method for COVID-19 since the outbreak. As the global epidemic situation is still unstable at present, radiology departments need to constantly improve the corresponding epidemic prevention and control measures, and formulate effective inspection plans for the patients with COVID-19, which can help patients and staff protect themselves against a high risk of COVID-19.
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OBJECTIVE: To explore the factors associated with depression in residents in the post-epidemic era of COVID-19. METHODS: A multi-stage stratified random sampling method was used to conduct a questionnaire survey among community residents through self-designed questionnaires and self-rating depression scale (SDS). Multivariate logistic regression analysis was performed on the influencing factors of depressive symptoms. RESULTS: A total of 1993 residues completed the survey of depression status. The incidence of depressive symptoms was 27.04%. The multivariate logistic regression analysis showed that female (odds ratio (OR): 6.239, 95% confidence interval (CI): 2.743-10.698), body mass index (BMI) > 24 (OR: 2.684, 95% CI: 1.059-3.759) and drinking (OR: 1.730, 95% CI: 1.480-3.153) were the risk factors for developing depressive symptoms. Married (OR: 0.417, 95% CI: 0.240-0.652), monthly income (3001-5000 yuan, OR: 0.624, 95% CI: 0.280-0.756; >5000 yuan, OR: 0.348, 95% CI: 0.117-0.625), ordinary residents (OR: 0.722, 95% CI: 0.248-0.924) and urban residents (OR: 0.655, 95% CI: 0.394-0.829) were the protective factors of depressive symptoms. CONCLUSIONS: Under the post-epidemic era of COVID-19, depressive symptoms are still common among community residents in China. Gender, BMI, drinking, marriage, monthly income and nature of personnel and residential area are associated with the incidence of depressive symptoms.
Subject(s)
COVID-19 , Depression , COVID-19/epidemiology , China/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Female , Humans , Prevalence , Risk Factors , Surveys and QuestionnairesABSTRACT
［］ Objective： To retrospectively analyze the clinical data of 52 patients with coronavirus disease-2019 （COVID-19） and explore the clinical efficacy of modified Sanxiaoyin on mild/moderate COVID-19 patients. Method： The propensity score matching method was used to collect the clinical data of mild or moderate COVID-19 patients enrolled in the designated hospital of the Second Hospital of Jingzhou from December 2019 to May 2020. A total of 26 eligible patients who were treated with modified Sanxiaoyin were included in the observation group，and the 26 patients treated with conventional method were the regarded as the control. The disappearance of clinical symptoms，disappearance time of main symptoms，efficacy on traditional Chinese medicine（TCM）symptoms，hospitalization duration，laboratory test indicators，and CT imaging changes in the two groups were compared. Result： The general data in the two groups were insignificantly different and thus they were comparable. After 7 days of treatment，the disappearance rate of fever，cough， fatigue，dry throat，anorexia，poor mental state，and poor sleep quality in the observation group was higher than that in the control group（P<0.05），and the difference in the disappearance rate of expectoration and chest distress was insignificant. For the cases with the disappearance of symptoms，the main symptoms（fever， cough，fatigue，dry throat，anorexia，chest distress）disappeared earlier in the observation group than in the control group（P<0.01）. After 7 days of treatment，the scores of the TCM symptom scale of both groups decreased（P<0.01），and the decrease of the observation group was larger that of the control group（P<0.01）. All patients in the two groups were cured and discharged. The average hospitalization duration in the observation group［（12.79±2.68）d］was shorter than that in the control group［（15.27±3.11）d］（P<0.01）. The effective rate in the observation group（92.31%，24/26）was higher than that in the control group（76.92%，20/26）. After 7 days of treatment，the lymphocyte（LYM）count increased（P<0.05），and white blood cell（WBC）count and neutrophil（NEUT）count decreased insignificantly in the two groups. Moreover，levels of C-reactive protein （CRP），erythrocyte sedimentation rate（ESR），and procalcitonin（PCT）reduced in the two groups after treatment（P<0.01）and the reduction in the observation group was larger than that in the control group （P<0.01）. Through 7 days of treatment，the total effective rate on pulmonary shadow in the observation group （90.00%，18/20）was higher than that in the control group（77.27%，17/22）（P>0.05）and the improvement of lung shadow in the observation group was better than that in the control group（P<0.01）. Conclusion：Modified Sanxiaoyin can significantly alleviate fever，cough，fatigue，anorexia，chest distress，poor sleep quality，and other symptoms of patients with mild or moderate COVID-19，improve biochemical indicators，and promote the recovery of lung function. This paper provides clinical evidence for the application of modified Sanxiaoyin in the treatment of mild or moderate COVID-19. © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.
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To make informative public policy decisions in battling the ongoing COVID-19 pandemic, it is important to know the disease prevalence in a population. There are two intertwined difficulties in estimating this prevalence based on testing results from a group of subjects. First, the test is prone to measurement error with unknown sensitivity and specificity. Second, the prevalence tends to be low at the initial stage of the pandemic and we may not be able to determine if a positive test result is a false positive due to the imperfect test specificity. The statistical inference based on a large sample approximation or conventional bootstrap may not be valid in such cases. In this paper, we have proposed a set of confidence intervals, whose validity doesn't depend on the sample size in the unweighted setting. For the weighted setting, the proposed inference is equivalent to hybrid bootstrap methods, whose performance is also more robust than those based on asymptotic approximations. The methods are used to reanalyze data from a study investigating the antibody prevalence in Santa Clara County, California in addition to several other seroprevalence studies. Simulation studies have been conducted to examine the finite-sample performance of the proposed method.
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Objective: To explore the mechanism of Kangguan decoction in the treatment of coronavirus disease 2019 (COVID-19) and then perform preliminary verification. Methods: The effective compounds and target genes of Kangguan decoction were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. COVID-19 related target genes were searched in the GeneCards database. The active target genes of Kangguan decoction acting on COVID-19 were identified to perform GO function enrichment and KEGG pathway enrichment analysis. The compound-target network and protein-protein interaction were constructed;Molecular docking simulations of macromolecular protein target receptors and their corresponding compounds were performed. The clinical data of COVID-19 patients were retrieved from their electronic medical records of Nantong Third People's Hospital. Results: We screened out 137 effective compounds and 274 effective target genes of Kangguan decoction from TCMSP. The active target genes of Kangguan decoction were compared with the COVID-19 related target genes, and 63 active target genes for Kangguan decoction acting on COVID-19 were identified. GO function enrichment and KEGG pathway enrichment analysis were performed. The compound-target network and PPI network were constructed and the key compounds and key targets were selected to construct a key compound-target network. Finally, the binding of the target and its corresponding components was verified by molecular docking and two clinical cases with obvious clinical efficacy after Kangguan decoction application were demonstrated. Conclusion: The pharmacological mechanism of Kangguan decoction acting on COVID-19 has been explored, and the active compounds and targets of Kangguan decoction acting on COVID-19 and clinical efficacy for Kangguan decoction treating COVID-19 patients have been preliminarily verified.
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Objective: The objectives of this study were to measure the global impact of the pandemic on the volumes for intravenous thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with two control 4-month periods. Background: The COVID-19 pandemic led to widespread repercussions on the delivery of health care worldwide. Design/Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by ICD-10 codes and/or classifications in stroke center databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95%CI,-11.7 to-11.3, p<0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95%CI,-13.8 to-12.7, p<0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95%CI,-13.7 to-10.3, p=0.001). There were greater declines in primary compared to comprehensive stroke centers (CSC) for stroke hospitalizations (-17.3% vs-10.3%, p<0.0001) and IVT (-15.5% vs-12.6%, p=0.0001). Recovery of stroke hospitalization volume (9.5%, 95%CI 9.2-9.8, p<0.0001) was noted over the two later (May, June) versus the two earlier (March, April) months of the pandemic, with greater recovery in hospitals with lower COVID-19 hospitalization volume, high volume stroke center, and CSC. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months, with greater recovery in hospitals with lower COVID-19 hospitalizations, high volume stroke centers, and CSCs.
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Objective: To retrospectively analyze the clinical characteristics and drug resistance among COVID-19 patients with bacterial and fungal infections. Methods: Clinical data of COVID-19 patients whose blood, urine, sputum and alveolar lavage fluid samples were positive for bacteria and fungi were collected in Tongji Hospital from February 10 to March 31, 2020. WHONET5.6 software was used to analyze drug susceptibility test results. Results: A total of 95 COVID-19 patients positive for pathogenic bacteria were enrolled and among them, 23 were non-critical patients and 72 were critical patients. The main symptoms in these patients included fever, cough with sputum, fatigue and dyspnea. Male and female critical patients accounted for 63.89% and 36.11%, respectively. Most of the patients with bacterial and fungal infections were critical type, accounting for 23.61%. The mortality rates of non-critical and critical patients were 13.04% and 61.11%, respectively. A total of 179 strains of pathogenic bacteria were isolated. The positive rate of Escherichia coli in non-critical patients was 37.50%, which was higher than that in critical patients. However, the positive rates of Acinetobacter baumannii and Klebsiella pneumoniae in critical patients were both 29.87%, higher than those in non-critical patients. There was no significant difference in the positive rate of gram-positive bacteria or fungi between non-critical and critical patients. It was noteworthy that the positive rate of Candida parapsilosis in blood samples of critical patients was relatively high, reaching 36.40%. Drug susceptibility test results showed that no carbapenem-resistant Escherichia coli stains were detected and 60.87% of Klebsiella pneumoniae strains were resistant to carbapenems. Acinetobacter baumannii strains were 100% resistant to three antimicrobial drugs. Methicillin-resistant Staphylococcus aureus strains accounted for 71.43%, but no vancomycin-resistant gram-positive cocci were found. Conclusions: Critical COVID-19 patients were mostly male and prone to multiple bacterial and fungal infections. The mortality of critical patients was higher than that of non-critical patients. Critical COVID-19 was often complicated by hospital acquired infections caused by bacteria including Acinetobacter baumannii and Klebsiella pneumoniae with high drug resistance. © 2021 Chinese Medical Association
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Background and Objective: The Coronavirus Disease 2019 pandemic situation is remaining severe worldwide. A single outbreak data source is not adequate for comprehensive analyses of the response to the pandemic. Such analyses need to seek proper integration of epidemic data for subsequent statistical analyses. Methods: 1) Considering reputations of publishers, activities, public users' accessibility, and retrievable historical data among several platforms, the World Health Organization (WHO), the US Centers for Disease Control (CDC), and Baidu's Real-time Epidemics (BRE) websites were selected as our data sources. 2) Data for 32 weeks until August 15th, 2020, were followed, including the US cumulative confirmed cases (CCCs), cumulative death cases (CDCs), cumulative discharged or cured cases (CD\vert CCs), daily new infective confirmed cases (DNCCs), and daily new death cases (DNDCs). 3) Estimators for the weekly current active infected confirm cases (CACs) and the weekly COVID19 fatal rate in the US hospitals (WFRUSH) were derived. Graphic display modules demonstrated the risks associated with demographic data. Results: 1) CCCs reached 5,285,546 cases in the US on August 15th, 2020, which initially climbed from the 9th-11th week;the CDCs were 167,546. The fatality rate initially climbed from the 12th-13th week, but fast turned over to decrease from the 18th week, then gradually flattened out near 3.17% till the mid of August 2020. 2) The WFRUSH first rose sharply at the 10th-11th week and started to decline in the 12th week, although there was a repeated smaller fluctuation in the 13th-14th week, during the generally downward process. 3) The US demographic characteristics and CDCs showed that the proportion of fatal cases in the senior Americans (age group over 65) accounted was 78.8%, about 4 (3.83) times the proportions of the other age groups. Supposed the death cases of seniors, directly caused by the COVID-19 rather than caused by the fundamental diseases, the \gamma value of the seniors, a ratio between the senior CDCs proportion over the senior population proportion was 4.81. Such a \gamma value for seniors, indicated a much higher fatality risk than other age groups. Conclusion: Integrative capture data from the publicly web-published COVID-19 statistics helps extend analyzable data and estimate or derive new-useful indicators CACs, WFRUSH, and \gamma value for the demographic group. As of the including the working population age of over 45, would have a much higher fatality rate than younger ages. It seemed necessary to study further if these death were caused directly by the COVID-19. Additionally, the African Americans, and male Americans, had relatively higher fatality rates. These high risks require more attention to strengthening health prevention;including the working-age population, even although the WFRUSH as a more appropriate and vital indication becomes stable to a low level after July 2020, meaning the clinical interventions and treatments were improved, or the virus fatality power was declined. © 2020 IEEE.
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COVID-19 has brought about significant economic and social disruption, and misinformation thrives during this uncertain period. In this paper, we apply state-of-the-art rumour detection systems that leverage both text content and user metadata to classify COVID-19 related rumours, and analyse how users, topics and emotions of rumours differ from non-rumours. We found that a number of interesting insights, e.g. rumour-spreading users have a disproportionately smaller number of followers compared to their followees, rumour topics largely involve politics (with an abundance of party blaming), and rumours tend to be emotionally charged (anger) but reactions towards rumours exhibit disapproving sentiments. © 2020 CEUR-WS. All rights reserved.