Literature Review of Statistical Methods Comparisons through Simulations When Using External Control Arm for Regulatory or HTA Submissions

Objectives: Using a historical control or external control arm (ECA) to augment or replace a concurrent control arm in a randomized trial is a hot topic given the challenge of patient recruitment in rare diseases or during COVID-19 pandemic. The FDA released draft guidance in 2021 on effectiveness and safety submissions using real-world evidence. While the guidance focuses mainly on elements of study design and data source selection, there is a lack of consensus in the selection of appropriate statistical methods when constructing an ECA. This study discusses rigorous statistical methodology for ECA-supported trials in regulatory or HTA submissions. Method(s): Targeted literature reviews of statistical simulations comparing methods for ECA in statistical journals were performed. The articles compared commonly used ECA-construction and analysis methods were selected and summarized, including but not limited to propensity score (PS)-based matching, weighting, and stratification, and PS plus Bayesian integrated approaches. Result(s): Type I error, power, bias, and coverage probability are common criteria used to compare different methods. When imbalances only exist in known baseline covariates and the outcome distributions are the same between the trial concurrent control and ECA, the PS method alone or paired with commensurate prior yield almost unbiased estimates, good Type I errors, and coverage probability. PS plus Bayesian approaches have wider interval width and lower power compared with PS-only methods. When there is a change in the outcome distribution over time, the PS (matching or IPTW) and commensurate prior integrated methods yield the smallest biases among all methods. Conclusion(s): PS and Bayesian integrated methods outperformed the PS-only methods in terms of bias and Type I error when outcome distribution changed with current trial control. A "sweet spot" that balances all criteria through trial-specific simulations could provide the ideal setting of trial analyses plan based on specific trial design and scenarios.Copyright © 2023

The impact of COVID-19 on the tourism and hospitality Industry: Evidence from international stock markets

COVID-19 seriously affects the tourism and hospitality industry. In this study, we investigate the behavior of 40 tourism and hospitality stock market indices worldwide from two perspectives. First, empowered by the Granger causality test and network analysis, we test the spillover effects among these stock markets and find that the dynamics of interconnectedness network structures differ significantly in the pre-pandemic and in-pandemic periods. Second, we employ econometric models to explore how the influence of COVID-19 on these stock markets varies by considering the interconnectedness structure, the government response stringency index, and other country-level characteristics. We find that the interconnectedness structure significantly and robustly affects stock returns in the tourism and hospitality markets. Our investigation provides a better understanding of the impact of COVID-19 on tourism and hospitality industry. © 2022 Elsevier Inc.

Assessment of Economic Recovery in Hebei Province, China, under the COVID-19 Pandemic Using Nighttime Light Data

The COVID-19 pandemic has presented unprecedented disruptions to human society worldwide since late 2019, and lockdown policies in response to the pandemic have directly and drastically decreased human socioeconomic activities. To quantify and assess the extent of the pandemic's impact on the economy of Hebei Province, China, nighttime light (NTL) data, vegetation information, and provincial quarterly gross domestic product (GDP) data were jointly utilized to estimate the quarterly GDP for prefecture-level cities and county-level cities. Next, an autoregressive integrated moving average model (ARIMA) model was applied to predict the quarterly GDP for 2020 and 2021. Finally, economic recovery intensity (ERI) was used to assess the extent of economic recovery in Hebei Province during the pandemic. The results show that, at the provincial level, the economy of Hebei Province had not yet recovered;at the prefectural and county levels, three prefectures and forty counties were still struggling to restore their economies by the end of 2021, even though these economies, as a whole, were gradually recovering. In addition, the number of new infected cases correlated positively with the urban NTL during the pandemic period, but not during the post-pandemic period. The study results are informative for local government's strategies and policies for allocating financial resources for urban economic recovery in the short- and long-term. © 2022 by the authors.

The reliability and integrity of overall survival data based on follow-up records only and potential solutions to the challenges

Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world. © 2022 The Authors

Study on TOD urban design method at district level from the perspective of resilient city

During the novel coronavirus epidemic from 2020 to the present, various cities have experienced different degrees of prevention, control and residents living problems. Taking the subway station area of Sichuan Normal University as an example, based on the theory of resilient city, this paper puts forward a conceptual TOD urban design strategy for the city to cope with sudden public health problems, studies the concept, development context and theoretical connotation of resilient city, and analyzes three types of application logic of resilient city in urban design of TOD area. Based on the analysis of the site basic conditions and users in the subway station area of Sichuan Normal University, the design result of "TOD Healthy Life Mode" combined with the concept of "Health + " is obtained, and the life trajectories of four types of users, including students, office workers, retired elderly and purpose visitors, are simulated. © 2022 Science Press. All rights reserved.

Evaluation of Tocilizumab for Covid-19 Treatment in the Intensive Care Unit

INTRODUCTION: Tocilizumab is recognized as a safe and efficacious treatment option for critically ill patients with COVID-19. Controversy remains regarding appropriate criteria for use. This evaluation assessed tocilizumab use for COVID-19 treatment and clinical outcomes following implementation of an institutional guideline. METHOD(S): This was a 2-center (1 community;1 academic), retrospective review of adult patients admitted to the ICU that received tocilizumab for COVID-19. Baseline demographics, length of stay (LOS), mechanical ventilation (MV), morbidity, mortality, and drug cost were collected. C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH) were reviewed and compared to institutional criteria for use. RESULT(S): Forty (26 community;14 academic) critically ill patient cases were reviewed. No differences were observed in baseline demographics, with a pool median age and weight of 58 (49-65) years and 102 (88-117) kg, respectively. No difference (community, 4 [15.4%] vs academic, 0 [0%];p=0.28) was seen in vaccination status. No differences were seen in time to tocilizumab administration, dose, hospital and ICU LOS, or progression to MV. Pooled median inflammatory markers included a CRP 131 (92-200) mg/L, ferritin 1074 (418-1936) ng/mL, and LDH 589 (414-803) IU/L with no differences between groups. Median ferritin values were noted as numerically higher, but non-significant in the community group (1331 [614-2306] ng/L vs 555 [341- 1851] ng/mL;p=0.16). Pooled all-cause in-hospital mortality was observed in 14 (35%) patients, with numerically higher, but non-significant rates in the community group (12 [46.2%] vs 2 [14.3%];p=0.08). Median charge per patient was $15,625.55. CONCLUSION(S): Critically ill patients receiving tocilizumab for COVID-19 treatment have high rates of mortality despite early use upon ICU admission. Baseline inflammatory markers were markedly above institutional criteria for use, leading to adjustments in the institutional guideline. Routine evaluation of tocilizumab use criteria may be warranted during strained supplies and COVID-19 surges.

Literature Review of Statistical Methods Comparisons Through Simulations When Using External Control Arm for Regulatory or HTA Submissions

Objectives: Using a historical control or external control arm (ECA) to augment or replace a concurrent control arm in a randomized trial is a hot topic given the challenge of patient recruitment in rare diseases or during COVID-19 pandemic. FDA released several draft guidance in 2021 on effectiveness and safety submissions using real-world evidence. While the guidance focuses mainly on elements of study design and data source selection, there is a lack of consensus in the selection of appropriate statistical methods when constructing an ECA. This study aims to discuss rigorous statistical methodology for ECA-supported trial in regulatory or HTA submissions. Method(s): Targeted literature reviews of statistical simulations comparing methods for ECA in statistical journals were performed. The articles compare commonly used ECA-construction and analysis methods were selected and summarized, including but not limited to propensity-score (PS) based- matching, weighting, stratification, and PS plus Bayesian integrated approaches. Result(s): Type I error, power, bias, and coverage probability are common criteria used to compare different methods. When imbalances only exist in known baseline covariates and the outcome distribution are the same between the trial concurrent control and ECA, PS method alone or paired with commensurate prior yield almost unbiased estimates, good Type I errors, and coverage probability. PS plus Bayesian approaches have wider interval width and lower power compared with PS only methods. When there is a change in the outcome distribution over time, PS (matching or IPTW) and commensurate prior integrated method yield smallest biases among all methods. Conclusion(s): PS and Bayesian integrated methods outperformed the PS only methods in terms of bias and type I error when outcome distribution changed with current trial control. A "sweet spot" that balances all criteria through trial-specific simulations could provide the ideal setting of trial analyses plan based on specific trial design and scenarios. Copyright © 2022

A Two-Way Atomic Exchange Protocol for Peer-to-Peer Data Trading

Various types of data are generated every day, and the amount of generated data is growing exponentially. People are interested in extracting the value of data. Some valuable data among them can be viewed as digital products to be traded. For example, with the outbreak of COVID-19, patients’ personal health records, electronic medical records and travel history become important and valuable information for epidemic prevention. On the other hand, the license keys for high-priced software such as EDA (Electronic Design Automation) tools also have value and can be considered as tradable products. However, the trust between two parties in the trading process becomes an issue. Consumers do not pay until providers give the data while providers are not willing to do since they distrust that consumers will pay after receiving the data. In this paper, we propose a Blockchain-based protocol for data trading with zero-knowledge proofs. To protect the data and maintain their value, Zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) is included that the provider can convince the consumer of the correctness and security of the data without revealing the details before receiving the payment. Predefined agreements between both parties in smart contracts are executed automatically. When the data is valid, the provider receives the payment, and in the meantime, the consumer has the ability to obtain the purchase data. Otherwise, the payment is refunded to the consumer immediately if the provider cheats. This approach employs the method of two-way exchange, as known as Delivery versus Payment (DvP) in physical commodity trading and ensures the rights and benefits for both parties. The whole process is decentralized for the purpose of constructing fair data trading without any trusted third party and ensuring system availability. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Suicide Rate and Factors Analysis: Pre and Post COVID Pandemic Data Analysis

According to the 2021 Report from the World Health Organization (WHO), more than 700,000 people have taken their life. Suicide can be prevented but so far most of the efforts to do so have fallen short. However, the use of machine learning and artificial intelligence offers new opportunities to increase the accuracy level of prediction and aid the goal of suicide prevention. This paper reviews literature concerning the machine learning methods used to help identify various risk factors and help prevent suicide. This paper also presents our research and analysis findings which were used to identify various suicide risk factors and additional analysis of whether there are any correlations or variations in the risk factors from pre-and post-pandemic datasets regarding suicide rates. This is especially important during times of high stress, such as a worldwide pandemic and quarantine. The dataset(s) obtained from WHO suggest that high levels of risk factor identification are possible and This paper and the analysis serve as supporting research and guide to aid in the continued ambitious goal of suicide prevention worldwide © 2022 IEEE.

COVID-19 control measures and their effectiveness in the Department of Obstetrics and Gynecology, Taipei Veterans General Hospital

Objectives: The coronavirus disease (COVID-19) pandemic requires multilevel comprehensive epidemic prevention measures from the central government to hospitals and from hospitals to departments in order to control it. The aim of this study was to assess the effectiveness of infection control measures implemented by the Department of Obstetrics and Gynecology, Taipei Veterans General Hospital. Methods: Strategies were developed to deal with high-risk cases, newborn transportation, parental classes, and visits and companions. These strategies included early risk identification, infant exposure reduction, alternative health education tactics, and visitor management. Results: In 2020, 16 high-risk patients received care at our department. No confirmed COVID-19 cases and nosocomial infections were noted. Exclusive breastfeeding rate during the period of January to June 2020 was 44.8%, an increase of 1.3% and 1.5% over the same period in 2019 and 2018, respectively. The rooming-in rate was 7.7%, similar to that (7.5%) of the same period in 2019. Session-specific attendance rates in prenatal parenting classes were 4.4% for second semester and 4.7% for third semester expectant mothers;there was no significant change compared with the 2019 rates (4.5% and 4.6%). The attendance rate of expectant fathers was 1.8% for the second semester and 1.6% for the third semester, a decrease of 0.7% and 1.1%, respectively, compared with the 2019 rates. However, these differences were not statistically significant. Conclusions: The infection control measures implemented for eariy risk identification, infant exposure reduction, alternative prenatal parenting education, and visitor management were effective as no COVID-19 case occurred and the quality of patient care and treatment was maintained. © 2021 Chinese Public Health Association of Taiwan. All rights reserved.

TB Quantiferon Testing Predicts Mortality in Patients with COVID-19

Background. Finding reliable clinical predictors for severity of COVID-19 has been challenging. Interferon gamma (IFNG) plays an important role in viral replication. QuantiFERON-TB (QFT) test relies on IFNG release in response to antigens. A positive or negative test signifies adequate IFNG response, whereas an indeterminate result is obtained when such a response is lacking. In this study, we have attempted to see if an indeterminate QFT result can provide prognostic information on patients with COVID-19. Survival Probability in patients with Covid - 19 and an indeterminate TB Quantiferon test result Methods. This is a retrospective study of patients who were admitted at our institute with COVID-19 and had a QFT done within one month of the positive SARSCoV-2 nucleic acid amplification test result. Patient charts were analyzed for clinical course and outcomes, including in-hospital mortality (primary outcome), 90-day mortality, respiratory failure, requirement for intubation and other complications that would portend a more severe disease course. Results. A total of 120 patient charts were analyzed, out of which 43 (35.8%) had an indeterminate QFT. All the indeterminate results were due to an inadequate mitogen response. The indeterminate QFT group had a 41.86% (18/43) in-hospital mortality vs. 9.09% (7/77) in the negative or positive QFT group (p-value of < 0.001). The 90-day mortality was similar between the two groups. Patients with indeterminate QFT also had a higher incidence of respiratory failure (97.7% vs. 75.3%;p-value = 0.020), requirement for mechanical ventilation (55.8% vs. 23.4%;p-value < 0.001), requirement of ECMO (25.58% vs. 0%;p-vale < 0.001), requirement of pressor (48.83% vs. 14.28%;p-value < 0.001) and requirement for renal replacement therapy (32.5% vs. 1.3%;p-value < 0.001), when compared to patients with a negative or positive QFT. Patients in indeterminate group had a higher hospital length of stay than the other group (p-value = 0.035). Conclusion. Our study indicates that patients with COVID-19 who fail to mount an adequate IFNG mitogen response in QFT assay have worse clinical outcomes and a more complicated and protracted clinical course. Evaluating cell-mediated immune responses through commercially available IFNG release assays may yield a promising strategy to predict COVID-19 clinical outcomes.

COVID-HateBERT: A Pre-trained Language Model for COVID-19 related Hate Speech Detection

With the dramatic growth of hate speech on social media during the COVID-19 pandemic, there is an urgent need to detect various hate speech effectively. Existing methods only achieve high performance when the training and testing data come from the same data distribution. The models trained on the traditional hateful dataset cannot fit well on COVID-19 related dataset. Meanwhile, manually annotating the hate speech dataset for supervised learning is time-consuming. Here, we propose COVID-HateBERT, a pre-trained language model to detect hate speech on English Tweets to address this problem. We collect 200M English tweets based on COVID-19 related hateful keywords and hashtags. Then, we use a classifier to extract the 1.27M potential hateful tweets to re-train BERT-base. We evaluate our COVID-HateBERT on four benchmark datasets. The COVID-HateBERT achieves a 14.8%-23.8% higher macro average F1 score on traditional hate speech detection comparing to baseline methods and a 2.6%-6.73% higher macro average F1 score on COVID-19 related hate speech detection comparing to classifiers using BERT and BERTweet, which shows that COVID-HateBERT can generalize well on different datasets. © 2021 IEEE.

The Relationship between Home-Based Learning Satisfaction and Mental State of Primary and Secondary School Students during Epidemic Outbreak: An Analysis of Mediating Effect of Self-Management

This study explores the home-based learning satisfaction and mental health status of primary and secondary school students during epidemic outbreak, and analyzes the intermediary role of self-management in learning satisfaction and mental health. Questionnaires among 14,594 primary and middle school students from 11 schools in Shaoguan City were conducted to study their home-based learning and mental health status during epidemic outbreak. Spss and Amos software were used for specific analysis of data and for structural model verification. The results show that: (1) the scores of home-based learning satisfaction, self-management and mental health of primary and middle school students were in the upper-middle level;(2) there were significant pairwise correlations among home-based learning satisfaction, self-management and mental health status of primary and secondary school students;(3) self-management plays a partial mediating role for learning outcomes, teachers’ teaching and mental health, with a mediating rate of 98.8%. Therefore, improving students’ self-management awareness and management skills of primary and secondary school students plays an important role in improving students' learning satisfaction and mental health. © 2021 Kriedt Enterprises Ltd. All right reserved.

The role of media coverage on pandemic containment: Empirical analysis of the COVID-19 case

Since December 29, 2019, the world has been suffering from a serious pandemic disease, the COVID-19. Given its universal availability, social media platforms, such as Weibo, provides the public with frequently updated health information to support the virus containment work. The health information posted by the health authorities (government, hospital, and medical experts) is expected to urge individuals to take protective actions. To investigate whether there is a significant impact of media coverage on protective behaviors and further on pandemic transmission, we collect a panel dataset to conduct an empirical analysis. Our preliminary results show that the volume of all media coverage has a significant containment effect on pandemic transmission. In particular, verified publishers have greater containment effect than unverified publishers. In the future, we will use instrument variables or matching methods to examine the causal effects. © Proceedings of the 24th Pacific Asia Conference on Information Systems: Information Systems (IS) for the Future, PACIS 2020. All rights reserved.

[How to construct clinical laboratory of the hospital in post epidemic time].

A novel coronavirus pneumonia outbreak in the world. The epidemic of the new coronavirus pneumonia has been preliminarily controlled successfully in China. At this time, how to construct the clinical laboratory in the hospital? This artical puts some forward thoughts, such as improve the construction of biological safety protection ability, detection ability, test platform construction, scientific research ability construction, personnel training and clinical communication ability, etc. These above advices could provide reference for the development direction of the clinical laboratory in post epidemic era.

Coping with COVID-19: ventilator splitting with differential driving pressures using standard hospital equipment.

The global COVID-19 pandemic has led to a worldwide shortage of ventilators. This shortage has initiated discussions on how to support multiple patients with a single ventilator (ventilator splitting). Ventilator splitting is incompletely tested, experimental and the effects have not been fully characterised. This study investigated the effect of ventilator splitting on system variables (inspiratory pressure, flow and volume) and the possibility of different ventilation targets for each limb using only standard hospital equipment. Experiments were conducted on two test lungs with different compliances (0.02 l.cmH2 O-1 and 0.04 l.cmH2 O-1 ). The ventilator was used in both pressure and volume control modes and was set to ventilate the low compliance lungs at end-tidal volumes of 500 ± 20 ml. A flow restrictor apparatus consisting of a Hoffman clamp and tracheal tube was connected in series to the inspiratory limb of the high compliance test lungs and the resistance modified to achieve end-tidal volumes of 500 ± 20 ml. The restriction apparatus successfully modified the inspiratory pressure, minute ventilation and volume delivered to the high compliance test lungs in both pressure control (27.3-17.8 cmH2 O, 15.2-8.0 l.min-1 and 980-499 ml, respectively) and volume control (21.0-16.7 cmH2 O, 10.7-7.9 l.min-1 and 659-498 ml, respectively) ventilation modes. Ventilator splitting is not condoned by the authors. However, these experiments demonstrate the capacity to simultaneously ventilate two test lungs of different compliances, and using only standard hospital equipment, modify the delivered pressure, flow and volume in each test lung.