Event Detection from Social Media for Epidemic Prediction (preprint)

Social media is an easy-to-access platform providing timely updates about societal trends and events. Discussions regarding epidemic-related events such as infections, symptoms, and social interactions can be crucial for informing policymaking during epidemic outbreaks. In our work, we pioneer exploiting Event Detection (ED) for better preparedness and early warnings of any upcoming epidemic by developing a framework to extract and analyze epidemic-related events from social media posts. To this end, we curate an epidemic event ontology comprising seven disease-agnostic event types and construct a Twitter dataset SPEED with human-annotated events focused on the COVID-19 pandemic. Experimentation reveals how ED models trained on COVID-based SPEED can effectively detect epidemic events for three unseen epidemics of Monkeypox, Zika, and Dengue; while models trained on existing ED datasets fail miserably. Furthermore, we show that reporting sharp increases in the extracted events by our framework can provide warnings 4-9 weeks earlier than the WHO epidemic declaration for Monkeypox. This utility of our framework lays the foundations for better preparedness against emerging epidemics.

Decisional procrastination and problematic mobile phone use: the mediation of anxiety and the moderation of 2019-nCoV traumatic experience (preprint)

Background Decisional procrastination (DP) has an important effect on problematic mobile phone use (PMPU); however, the potential mechanisism and boundary conditions between DP and PMPU remianed to be further explored. This essay studied the mediation of anxiety between DP and PMPU and whether 2019-nCoV traumatic experience moderated the mediation process.Methods A questionnaire was used in this study. A valid sample of 798 college students reported levels of decisional procrastination, problematic mobile phone use, anxiety, and 2019-nCoV traumatic experience.Results The results indicated that decisional procrastination is positively associated with problematic mobile phone use among college students. Anxiety served as a partial mediator in the association between decisional procrastination and problematic mobile phone use. 2019-nCoV traumatic experience would positively moderated the mediating effects of anxiety between DP and PMPU. A higher degree of 2019-nCoV traumatic experience would strengthen the mediation effects of DP to PMPU through anxiety.Conclusions This study deepens our understanding of how DP affects college students' PMPU. It was found in the study that 2019-nCoV traumatic experience positively moderated the mediation effects of anxiety between DP and PMPU. These findings provide universities with a theoretical foundation for preventing PMPU among college students.

Exploring the Transmission Dynamics of the COVID-19 Outbreaks after Dec. 2022 in Shaanxi Province, China: Analysis of Baseline Data from A Large Scale Cohort (preprint)

Backgrounds: The goal of this study is to explore the transmission dynamics for recent large-scale COVID-19 outbreaks in Shaanxi Province on the Chinese mainland. Furthermore, the potential effects of the Spring Festival travel rush on the ongoing COVID-19 pandemic were depicted. Methods This study uses baseline data from a large cohort to investigate the characteristics of the recent COVID-19 epidemic in Shaanxi province. A cluster sampling method was used to recruit the study participants during the COVID-19 pandemic in Shaanxi province since Dec. 1st, 2022. A total of 44 sampling cluster (11 village in rural areas and 33 residences in urban areas) were chosen for enrollment of study participants. A self-developed questionnaire was applied to data collection of socio-demographic and COVID-19 pandemic related information. Results A total of 14,744 study participants were enrolled in the baseline survey and 12,111 completed survey data were extracted for analysis. The cumulative infection attack rate (IAR) of COVID-19 among the study participants was 84.7%. The cumulative IAR in urban and rural areas were 85.6% and 83.7%, respectively. A peak of COVID-19 self-reported diagnosis could be observed from Dec. 15th, 2022 to Jan. 1st, 2023 in the provincial level. Beside this major peak of the recent epidemic (around Dec.20th, 2022), a small but steep rise could also be identified between Jan 13th to 14th, 2023. Individuals who escaped the first wave of COVID-19 outbreaks may face danger of infection from returnees during the 2023 Spring Festival. Conclusion According to the COVID-19 cumulative IAR data, the herd community was primarily achieved in Shaanxi province's urban and rural areas. The epidemic in Shaanxi province has been exacerbated by mass population movement during the Spring Festival travel rush in both urban and rural areas. Further surveillance should be performed to monitor the spread of SARS-CoV-2 infections.

Deep‐Learning‐Assisted Noncontact Gesture‐Recognition System for Touchless Human‐Machine Interfaces

Human‐machine interfaces (HMIs) play important role in the communication between humans and robots. Touchless HMIs with high hand dexterity and hygiene hold great promise in medical applications, especially during the pandemic of coronavirus disease 2019 (COVID‐19) to reduce the spread of virus. However, current touchless HMIs are mainly restricted by limited types of gesture recognition, the requirement of wearing accessories, complex sensing platforms, light conditions, and low recognition accuracy, obstructing their practical applications. Here, an intelligent noncontact gesture‐recognition system is presented through the integration of a triboelectric touchless sensor (TTS) and deep learning technology. Combined with a deep‐learning‐based multilayer perceptron neural network, the TTS can recognize 16 different types of gestures with a high average accuracy of 96.5%. The intelligent noncontact gesture‐recognition system is further applied to control a robot for collecting throat swabs in a noncontact mode. Compared with present touchless HMIs, the proposed system can recognize diverse complex gestures by utilizing charges naturally carried on human fingers without the need of wearing accessories, complicated device structures, adequate light conditions, and achieves high recognition accuracy. This system could provide exciting opportunities to develop a new generation of touchless medical equipment, as well as touchless public facilities, smart robots, virtual reality, metaverse, etc. [ FROM AUTHOR] Copyright of Advanced Functional Materials is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Sustainable Financing and Financial Risk Management of Financial Institutions—Case Study on Chinese Banks

This study examines the relationship between sustainable financing and financial risk management of Chinese financial institutions, using data from Chinese banks. Financial risk management is a comprehensive measure of operating performance, asset quality and capital adequacy ratio. The structural vector auto-regression model determines the relationship between two variables. The positive shock of sustainable financing business negatively impacts the financial risk management of banks. In contrast, positive shock of banks’ financial risk management positively affects sustainable financing. Further subdivision of the sample revealed that sustainable financing does not always negatively impact the financial risk management of large state-owned banks. However, the positive shock of financial risk management reduces urban banks’ green credit proportions. The results are consistent whenever compared between the empirical outcome of the entire sample and the sample consisting of national joint stock bank accounts. This comparison helps eliminate the possibility of a biased outcome as a major portion of the sample is from a national joint-stock bank account. Apart from data limitations, the results of the sub-sample test are influenced due to the difference in deposit and loan interest rates, as well as different ownership structures of banks.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4+ T cells, CD8+ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4+ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

The impact of COVID-19 epidemic on emergency department visits of older patients in Taiwan (preprint)

Background The number of emergency department (ED) visits has significantly declined since the COVID-19 pandemic. In Taiwan, an aging society, it is unknown whether older adults are accessing emergency care during the COVID-19 epidemic. Therefore, this study aimed to investigate the impact of COVID-19 on the ED visits and triage, admission, and intensive care unit (ICU) hospitalization of the geriatric population in a COVID-19-dedicated medical center throughout various periods of the epidemic.Methods A retrospective chart review of ED medical records from April 9 to August 31, 2021 were conducted, and demographic information was obtained from the hospital’s computer database. The period was divided into pre-, early-, peak-, late-, and post-epidemic stages. For statistical analysis, one-way analysis of variance followed by multiple comparison tests (Scheffe’s test) were used.Results A statistically significant decrease in the total number of patients attending the ED was noted during the peak-, late-, and post-epidemic stages. In the post- and pre-epidemic stage, the number of older patients visiting ED was consistent, indicating their earlier visit to ED than the general population. Regarding ICU admission, the total number of patients in late-epidemic stage was smaller than that in pre-epidemic stage; however, the number of older patients was steady, regardless of hospital or ICU admission.Conclusions During the peak of COVID-19 outbreak, the number of ED visits was significantly affected. However, it is noteworthy that as the epidemic was gradually controlled, the older patients resumed their ED visits earlier that the general population as indicated by the surge in their number. Additionally, in the patient group of triage 1 or 2, which represents a true emergency, the number did not show a drastic change.

Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Management (preprint)

The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e. Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial), lead to shifts in planning and budgeting, but most importantly, reduces confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. This manuscript presents three data-driven methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resources allocation and sharing. Conventional decision-making methods fall short in recommending validated policies for managers. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. Experiments are performed; the results are recorded, evaluated, and presented.

Predictors of Depression and Anxiety Symptoms in Brazil during COVID-19 (preprint)

The COVID-19 pandemic in Brazil is extremely severe, and Brazil has the third-highest number of cases in the world. The goal of the study is to identify the prevalence rates and several predictors of depression and anxiety in Brazil during the initial outbreak of COVID-19. We surveyed 482 adults in 23 Brazilian states online on 9-22 May 2020, and found 70.3% of the adults (N=339) had depressive symptoms and 67.2% (N=320) had anxiety symptoms. The results of multi-class logistic regression models revealed that females, younger adults and those with fewer children had a higher likelihood of depression and anxiety symptoms; adults who worked as employees were more likely to have anxiety symptoms than those who were self-employed or unemployed; adults who spent more time browsing COVID-19 information online were more likely to have depression and anxiety symptoms. Our results provide preliminary evidence and early warning for psychiatrists and healthcare organizations to better identify and focus on the more vulnerable sub-populations in Brazil during the ongoing COVID-19 pandemic. Keywords: COVID-19; Brazil; anxiety; depression; predictors; risk factors

Air quality characteristics in Wuhan (China) during the 2020 COVID-19 pandemic.

Understanding the relationship between air quality, pollution emission control measures, and meteorological conditions is important for developing effective air quality improvement policies. In this study, we used pollution monitoring and meteorological data from January to May 2020 to analyze the air quality characteristics during the COVID-19 lockdown in Wuhan, which lasted from January 23 to April 8, 2020. Compared with the same period in 2019, the air quality in 2020 was significantly better. The total excellent and good air quality rates increased by 17.58%-90.08% in 2020; concentrations of NO2, particulate matter with a diameter <10 µm (PM10) and <2.5 µm (PM2.5), and total volatile organic compounds (TVOCs) also decreased by 38.23%, 30.25%, 32.92%, and 39.80%, respectively. Moreover, the number of days with NO2, PM10, and PM2.5 as the primary pollutants decreased by approximately 10%, 9%, and 15%, respectively. We compared the wind direction, wind speed, temperature, and relative humidity in January-April 2020, 2019, 2018, and 2017 and found no obvious correlation between meteorological factors and improved air quality during the 2020 lockdown. The implementation of strict lockdown measures, such as home quarantining, traffic restrictions, and non-essential enterprise shutdowns, was the dominant cause for the substantial air quality improvement during the 2020 COVID-19 lockdown in Wuhan.

The Impact of COVID-19 Pandemic on Colorectal Cancer Patients: A Single-Center Retrospective Study (preprint)

Background: Since December 2019, China has experienced the public health emergency of coronavirus disease, which has expanded globally and is impacting the care of cancer patients. This study evaluated the impact of the pandemic on colorectal cancer (CRC) patients at our center and aimed to share lessons learned with clinics currently experiencing this impact. Methods: We retrospectively collected data on CRC patients admitted between January 1, 2020 and May 3, 2020; the control group comprised patients admitted between January 1, 2019 and May 3, 2019. Results: During the pandemic, outpatient volumes decreased significantly, especially among nonlocal and elderly patients, whereas the number of patients who received chemotherapy and surgery were maintained. During the pandemic, 710 CRC patients underwent curative enterectomy. The proportion of laparoscopic surgery was 49.4%, which was significantly higher than the 39.5% patients who received a laparoscopic surgery during the same period in 2019. The proportion of major complication during the pandemic was not significantly different from that of the control group. The mean hospital stay was significantly longer than that of the control group. Conclusions: CRC patients who are confirmed to be infection-free can receive routine treatment. Using online medical counseling and appropriate identification, treatment and follow-up was effectively maintained. Adjuvant and palliative chemotherapy should not be discontinued. Endoscopic polypectomy, elective, palliative, and multidisciplinary surgeries can be postponed, whereas curative surgery should be performed. For elderly CRC patients, endoscopic surgery and neoadjuvant radiotherapy are recommended.Trial registration: retrospectively registered

The impact of COVID-19 pandemic on colorectal cancer patients: A single-center retrospective study (preprint)

Background: Since December 2019, China has experienced the public health emergency of coronavirus disease, which has expanded globally and is impacting the care of cancer patients. This study evaluated the impact of the pandemic on colorectal cancer (CRC) patients at our center and aimed to share lessons learned with clinics currently experiencing this impact. Methods: We retrospectively collected data on CRC patients admitted between January 1, 2020 and May 3, 2020; the control group comprised patients admitted between January 1, 2019 and May 3, 2019. Results: During the pandemic, outpatient volumes decreased significantly, especially among nonlocal and elderly patients, whereas the number of patients who received chemotherapy and surgery were maintained. During the pandemic, 710 CRC patients underwent curative enterectomy. The proportion of laparoscopic surgery was 49.4%, which was significantly higher than the 39.5% patients who received a laparoscopic surgery during the same period in 2019. The proportion of major complication during the pandemic was not significantly different from that of the control group. The mean hospital stay was significantly longer than that of the control group. Conclusions: CRC patients who are confirmed to be infection-free can receive routine treatment. Using online medical counseling and appropriate identification, treatment and follow-up was effectively maintained. Adjuvant and palliative chemotherapy should not be discontinued. Endoscopic polypectomy, elective, palliative, and multidisciplinary surgeries can be postponed, whereas curative surgery should be performed. For elderly CRC patients, endoscopic surgery and neoadjuvant radiotherapy are recommended.

Structural basis for the inhibition of the papain-like protease of SARS-CoV-2 by small molecules (preprint)

SARS-CoV-2 is the pathogen responsible for the COVID-19 pandemic. The SARS-CoV-2 papain-like cysteine protease has been implicated in virus maturation, dysregulation of host inflammation and antiviral immune responses. We showed that PLpro preferably cleaves the K48-ubiquitin linkage while also being capable of cleaving ISG15 modification. The multiple functions of PLpro render it a promising drug target. Therefore, we screened an FDA-approved drug library and also examined available inhibitors against PLpro. Inhibitor GRL0617 showed a promising IC50 of 2.1 M. The co-crystal structure of SARS-CoV-2 PLpro-C111S in complex with GRL0617 suggests that GRL0617 is a non-covalent inhibitor. NMR data indicate that GRL0617 blocks the binding of ISG15 to PLpro. The antiviral activity of GRL0617 reveal that PLpro is a promising drug target for therapeutically treating COVID-19. One Sentence SummaryCo-crystal structure of PLpro in complex with GRL0617 reveals the druggability of PLpro for SARS-CoV-2 treatment.

Social Distancing 2.0 with Privacy-Preserving Contact Tracing to Avoid a Second Wave of COVID-19 (preprint)

How to avoid a second wave of COVID-19 after reopening the economy is a pressing question. The extremely high basic reproductive number $R_0$ (5.7 to 6.4, shown in new studies) of SARS-CoV-2 further complicates the challenge. Here we assess effects of Social distancing 2.0, i.e. proximity alert (to maintain inter-personal distance) plus privacy-preserving contact tracing. To solve the dual task, we developed an open source mobile app. The app uses a Bluetooth-based, decentralized contact tracing platform over which the anonymous user ID cannot be linked by the government or a third party. Modelling results show that a 50\% adoption rate of Social distancing 2.0, with privacy-preserving contact tracing, would suffice to decrease the $R_0$ to less than 1 and prevent the resurgence of COVID-19 epidemic.

Selection of homemade mask materials for preventing transmission of COVID-19: a laboratory study (preprint)

The Coronavirus Disease 2019 (COVID-19) has swept the whole world with high mortality. Since droplet transmission is the main route of transmission, wearing a mask serves as a crucial preventive measure. However, the virus has spread quite quickly, causing severe mask shortage. Finding alternative materials for homemade masks while ensuring the significant performance indicators will help alleviate the shortage of masks. Referring to the national standard for the "Surgical Mask" of China, 17 materials to be selected for homemade masks were tested in four key indicators: pressure difference, particle filtration efficiency, bacterial filtration efficiency and resistance to surface wetting. Eleven single-layer materials met the standard of pressure difference ([≤]49 Pa), of which 3 met the standard of resistance to surface wetting ([≥]3), 1 met the standard of particle filtration efficiency ([≥]30%), but none met the standard of bacterial filtration efficiency ([≥]95%). Based on the testing results of single-layer materials, fifteen combinations of paired materials were tested. The results showed that three double-layer materials including double-layer medical non-woven fabric, medical non-woven fabric plus non-woven shopping bag, and medical non-woven fabric plus granular tea towel could meet all the standards of pressure difference, particle filtration efficiency, and resistance to surface wetting, and were close to the standard of the bacterial filtration efficiency. In conclusion, if resources are severely lacking and medical masks cannot be obtained, homemade masks using available materials, based on the results of this study, can minimize the chance of infection to the maximum extent.

Scarce Health-care Resources and Higher Case-fatality Rates Early in an Epidemic: Analysis of Hospitalized Patients with COVID-19 in Tianmen. (preprint)

Background Tianmen had the highest case-fatality rate (CFR) among all the cities in China early in the transmission of SARS-CoV-2, but little is known about the details of the epidemic in Tianmen. Our study aims to reveal the causes of the high CFR from the aspects of clinical features, medical resources, and epidemic situation.Methods In this study, we report the admission and outcomes of 341 patients with confirmed COVID-19 who were admitted and hospitalized in the hospital (The First People's Hospital of Tianmen) from January 14 to February 25, 2020. Epidemic information and medical resources across different regions were collected and compared. Results All deaths from COVID-19 in Tianmen occurred in the hospital, and the proportion of patients with critical (8.5%) symptoms in the hospital is higher than the average in China. In addition, the number of affected patients in Tianmen is quite low, but the hospital and the whole city had the highest CFR in the early stage of the epidemic. Completely different from the stable CFR in Hubei Province, the CFR of COVID-19 in the hospital and city dropped dramatically, from the largest value in China to a more average level, within a few days. Analysis of government public documents showed that the per capita medical resources in Tianmen are worse than those of Wuhan and Hubei. Conclusions Our findings suggest that the inadequate capacity to respond to public health emergencies caused by relatively scarce health-care resources is a crucial factor contributing to the higher CFR of infectious diseases in regions with lower economic levels. Such countries and territories should implement strategies earlier to minimize the danger of COVID-19.

Geographical Distance to the Epicenter of Covid-19 Predicts the Burnout of Working Population: Ripple effect or Typhoon Eye effect? (preprint)

Covid-19 originated in Wuhan and rippled across China. We investigate how the geographical distance of working adults to the epicenter of Wuhan predicts their burnout. Preliminary results of a survey of 308 working adults in 53 cities showed the distance to the epicenter of Wuhan had an inverted U-shaped relationship with the burnout. Such results help to identify regions where people would need more psychiatric assistance, carrying direct implications to healthcare practitioners and policymakers.