Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts (preprint)

Objective: COVID-19 has spread worldwide and made a huge influence across the world. Modeling the infectious spread situation of COVID-19 is essential to understand the current condition and to formulate intervention measurements. Epidemiological equations based on the SEIR model simulate disease development. The traditional parameter estimation method to solve SEIR equations could not precisely fit real-world data due to different situations, such as social distancing policies and intervention strategies. Additionally, learning-based models achieve outstanding fitting performance, but cannot visualize mechanisms. Methods: Thus, we propose a deep dynamic epidemiological (DDE) method that combines epidemiological equations and deep-learning advantages to obtain high accuracy and visualization. The DDE contains deep networks to fit the effect function to simulate the ever-changing situations based on the neural ODE method in solving variants' equations, ensuring the fitting performance of multi-level areas. Results: We introduce four SEIR variants to fit different situations in different countries and regions. We compare our DDE method with traditional parameter estimation methods (Nelder-Mead, BFGS, Powell, Truncated Newton Conjugate-Gradient, Neural ODE) in fitting the real-world data in the cases of countries (the USA, Columbia, South Africa) and regions (Wuhan in China, Piedmont in Italy). Our DDE method achieves the best Mean Square Error and Pearson coefficient in all five areas. Further, compared with the state-of-art learning-based approaches, the DDE outperforms all techniques, including LSTM, RNN, GRU, Random Forest, Extremely Random Trees, and Decision Tree. Conclusion: DDE presents outstanding predictive ability and visualized display of the changes in infection rates in different regions and countries.

Child abuse during the COVID-19 pandemic-Prospect, risk and factors: A narrative review

This narrative review focuses on the risk of child abuse, the determinants of child maltreatment during the Covid-19 outbreak and the conceivable psycho-social impact of child abuse. Literature was retrieved from Scopus, PubMed, PsycINFO, Web of Science along with Google Scholar, and reports from various sources with no time and context restrictions. The narrative analysis of all pertinent records shows that the risk of abuse towards children has spiked during the Covid-19 outbreak, especially sexual abuse and neglect. Prolonged living inside of homes, school closures, limited contact, unemployment, domestic violence, poor access to health care, and related social stressors have impacted on the rates of child abuse during the Covid-19 outbreak. These maltreated children may experience poor interpersonal relationships, problematic coping behaviours, and depressive disorders across their life span. These findings point to context-specific outcomes and protective measures that could assist prospective researches and guide policies. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Ultra-sensitive and specific detection of pathogenic nucleic acids using composite-excited hyperfine plasma spectroscopy combs sensitized by Au nanoarrays functionalized with 2D Ta2C-MXene.

Accurate and rapid screening techniques on a population scale are crucial for preventing and managing epidemics like COVID-19. The standard gold test for nucleic acids in pathogenic infections is primarily the reverse transcription polymerase chain reaction (RT-PCR). However, this method is not suitable for widespread screening due to its reliance on large-scale equipment and time-consuming extraction and amplification processes. Here, we developed a collaborative system that combines high-load hybridization probes targeting N and OFR1a with Au NPs@Ta2C-M modified gold-coated tilted fiber Bragg grating (TFBG) sensors to enable direct nucleic acid detection. Multiple activation sites of SARS-CoV-2 were saturable modified on the surface of a homogeneous arrayed AuNPs@Ta2C-M/Au structure based on a segmental modification approach. The combination of hybrid probe synergy and composite polarisation response in the excitation structure results in highly specific hybridization analysis and excellent signal transduction of trace target sequences. The system demonstrates excellent trace specificity, with a limit of detection of 0.2 pg/mL, and achieves a rapid response time of 1.5 min for clinical samples without amplification. The results showed high agreement with the RT-PCR test (Kappa index = 1). And the gradient-based detection of 10-in-1 mixed samples exhibits high-intensity interference immunity and excellent trace identification. Therefore, the proposed synergistic detection platform has a good tendency to curb the global spread of epidemics such as COVID-19.

Ultra-sensitive specific detection of nucleic acids in pathogenic infections by Ta2C-MXene sensitization-based ultrafine plasmon spectroscopy combs.

Accurate and rapid population-scale screening techniques based on SARS-CoV-2 RNA are essential in preventing and controlling the COVID-19 epidemic. However, the sensitivity and specificity of the assay signal are challenged by the problems of target dilution and sample contamination inherent in high-volume pooled testing. Here, we reported a collaborative system of high-loaded hybrid probes targeting N and OFR1a coupling with the novel Ta2C-M/Au/TFBG biosensor, providing high-intensity vector signals for detecting SARS-CoV-2. The method relies on a segmental modification approach to saturable modify multiple activation sites of SARS-CoV-2 on the high-performance Ta2C-M surface. The coupling of multi-site synergy with composite excited TFBG results in excellent signal transduction, detection limits (0.2 pg/mL), and hybridization efficiency. Without relying on amplification, the collaborative system achieved specific differentiation of 30 clinical samples in an average diagnostic time of 1.8 min. In addition, for the first time, a kinetic determination of dilution mixed samples was achieved and showed a high-intensity carrier signal and fantastic stability. Therefore, it can be used as a collaborative, integrated tool to play a massive role in the screening, prevention, and control of COVID-19 and other epidemics.

Dynamic chest computed tomography change analysis and prediction of length of stay for delta variant COVID-19 patients

OBJECTIVE: As hospital admission rate is high during the COVID-19 pandemic, hospital length of stay (LOS) is a key indicator of medical resource allocation. This study aimed to elucidate specific dynamic longitudinal computed tomography (CT) imaging changes for patients with COVID-19 over in-hospital and predict individual LOS of COVID-19 patients with Delta variant of SARS-CoV-2 using the machine learning method. MATERIALS AND METHODS: This retrospective study recruited 448 COVID-19 patients with a total of 1761 CT scans from July 14, 2021 to August 20, 2021 with an averaged hospital LOS of 22.5 ± 7.0 days. Imaging features were extracted from each CT scan, including CT morphological characteristics and artificial intelligence (AI) extracted features. Clinical features were obtained from each patient's initial admission. The infection distribution in lung fields and progression pattern tendency was analyzed. Then, to construct a model to predict patient LOS, each CT scan was considered as an independent sample to predict the LOS from the current CT scan time point to hospital discharge combining with the patients' corresponding clinical features. The 1761 follow-up CT data were randomly split into training set and testing set with a ratio of 7:3 at patient-level. A total of 85 most related clinical and imaging features selected by Least Absolute Shrinkage and Selection Operator were used to construct LOS prediction model. RESULTS: Infection-related features were obtained, such as the percentage of the infected region of lung, ground-glass opacity (GGO), consolidation and crazy-paving pattern, and air bronchograms. Their longitudinal changes show that the progression changes significantly in the earlier stages (0–3 days to 4–6 days), and then, changes tend to be statistically subtle, except for the intensity range between (−470 and −70) HU which exhibits a significant increase followed by a continuous significant decrease. Furthermore, the bilateral lower lobes, especially the right lower lobe, present more severe. Compared with other models, combining the clinical, imaging reading, and AI features to build the LOS prediction model achieved the highest R2 of 0.854 and 0.463, Pearson correlation coefficient of 0.939 and 0.696, and lowest mean absolute error of 2.405 and 4.426, and mean squared error of 9.176 and 34.728 on the training and testing set. CONCLUSION: The most obvious progression changes were significantly in the earlier stages (0–3 days to 4–6 days) and the bilateral lower lobes, especially the right lower lobe. GGO, consolidation, and crazy-paving pattern and air bronchograms are the most main CT findings according to the longitudinal changes of infection-related features with LOS (day). The LOS prediction model of combining clinical, imaging reading, and AI features achieved optimum performance.

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

BACKGROUND: The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various countries. For policymaking and medical resource decisions, a good prediction model is necessary to monitor and evaluate the trends of the epidemic. We used a long short-term memory (LSTM) model and the improved hybrid model based on ensemble empirical mode decomposition (EEMD) to predict COVID-19 trends; Methods: The data were collected from the Harvard Dataverse. Epidemic data from 21 January 2020 to 25 April 2021 for California, the most severely affected state in the United States, were used to develop an LSTM model and an EEMD-LSTM hybrid model, which is an LSTM model combined with ensemble empirical mode decomposition. In this study, ninety percent of the data were adopted to fit the models as a training set, while the subsequent 10% were used to test the prediction effect of the models. The mean absolute percentage error, mean absolute error, and root mean square error were used to evaluate the prediction performances of the models; Results: The results indicated that the number of confirmed cases in California was increasing as of 25 April 2021, with no obvious evidence of a sharp decline. On 25 April 2021, the LSTM model predicted 3666418 confirmed cases, whereas the EEMD-LSTM predicted 3681150. The mean absolute percentage errors for the LSTM and EEMD-LSTM models were 0.0151 and 0.0051, respectively. The mean absolute and root mean square errors were 5.58 × 104 and 5.63 × 104 for the LSTM model and 1.9 × 104 and 2.43 × 104 for the EEMD-LSTM model, respectively; Conclusions: The results showed the advantage of an EEMD-LSTM model over a single LSTM model, and the established EEMD-LSTM model may be suitable for monitoring and evaluating the epidemic situation and providing quantitative analysis evidence for epidemic prevention and control.

Characterization and pathogenicity of the porcine epidemic diarrhea virus isolated in China.

Piglet diarrhea caused by the porcine epidemic diarrhea virus (PEDV) is a common problem on pig farms in China associated with high morbidity and mortality rates. In this study, three PEDV isolates were successfully detected after the fourth blind passage in Vero cells. The samples were obtained from infected piglet farms in Jilin (Changchun), and Shandong (Qingdao) Provinces of China and were designated as CH/CC-1/2018, CH/CC-2/2018, and CH/QD/2018. According to the analysis of the complete S protein gene sequence, the CH/CC-1/2018 and CH/CC-2/2018 were allocated to the G2b branch, while CH/QD/2018 was located in the G1a interval and was closer to the vaccine strain CV777. Successful detection and identification of the isolated strains were carried out using electron microscopy and indirect immunofluorescence. Meanwhile, animal challenge experiments and viral RNA copies determination were used to compare the pathogenicity. The results showed that CH/CC-1/2018 in Changchun was more pathogenic than CH/QD/2018 in Qingdao. In conclusion, the discovery of these new strains is conducive to the development of vaccines to prevent the pandemic of PEDV, especially that the CH/CC-1/2018, and CH/CC-2/2018 were not related to the classical vaccine strain CV777.

Patients with von Willebrand disease in China: Results of an online survey.

INTRODUCTION: Little is known about the clinical characteristics of von Willebrand disease (VWD) patients in China, the impact of Covid-19 on them and their genetic mutation. AIM: To describe the clinical characteristics of a group of VWD patients in China, the impact of Covid-19 on them and their genetic mutation. METHODS: An online survey using a self-designed questionnaire was conducted among patients within a WeChat group of VWD patients in China. Data were analysed using t-test, the Chi-square test, Fisher's exact test and rank sum test. RESULTS: Data from a total of 96 patients were collected. Several important findings are yielded. Above all, type 3 patients accounted for over half of the surveyed patients. Secondly, a surprising rate (>40%) of patients had experience of being misdiagnosed. Thirdly, treatment regimens were dominated by cryoprecipitate, blood-derived FVIII and plasma, and only a small percentage of patients received prophylaxis. Fourthly, we identified 17 new von Willebrand factor (VWF) mutant genes which merit further investigation. Additionally, Covid-19 was found to pose some challenges for the patients. CONCLUSION: In China, the high rates of type 3 patients and misdiagnosis suggest that most of the VWD patients may never be diagnosed in China. When it comes to diagnosis and treatment, there is a large gap between developing countries like China and developed countries.

Burnout, depression, anxiety and insomnia among medical staff during the COVID-19 epidemic in Shanghai.

Background: Coronavirus disease 2019 (COVID-19) has progressively impacted our daily lives, resulting in unexpected physical and mental stress on medical staff. This study is designed to investigate the levels of and risk factors for burnout, depression, anxiety, and insomnia among medical staff during the COVID-19 epidemic breakout in Shanghai, China. Methods: This cross-sectional survey was conducted from May 1 to May 31, 2022, among medical staff who were on the frontline during the epidemic breakout in Shanghai from different institutions. The MBI-HSS was used to assess burnout, PHQ-9, GAD-7 and ISI were used to evaluate mental status and insomnia. Results: A total of 543 valid questionnaires were collected. The depersonalization, depression, anxiety, and insomnia scores of medical staff were significantly higher during the pandemic in Shanghai compared with norms, while lack of personal achievement scores were decreased. Working time, work unit, work environment and age are important influencers of burnout, depression and anxiety of medical staff. Long working hours are the most likely causes of burnout and emotional disorders. Medical staff in primary hospitals were most likely to suffer from burnout and emotional disorders, while medical staff in tertiary hospitals had a reduced sense of personal achievement. Young medical staff are prone to negative emotions such as depression and anxiety, while older medical staff have a lower sense of personal accomplishment. Medical staff who were not in the shelter hospitals or designated hospitals were more likely to have problems of emotional exhaustion, depersonalization and anxiety than those who were in the shelter hospitals or designated hospitals. Contracting COVID-19 had no effect on medical staff. Emotional exhaustion and depersonalization were positively correlated with anxiety, depression, and sleep disorders while personal achievement was negatively correlated with these factors. Conclusion: Medical staff in Shanghai had high burnout, depression, anxiety and insomnia levels during the epidemic outbreak in Shanghai. During the COVID-19, medical staff may suffer different psychological problems which should be concerned. Care and supports about burnout, mental health and insomnia need to be taken to promote the mental health of medical staff according to different characteristics of medical staff.

mRNA-Based Therapeutics in Cancer Treatment.

Over the past two decades, significant technological innovations have led to messenger RNA (mRNA) becoming a promising option for developing prophylactic and therapeutic vaccines, protein replacement therapies, and genome engineering. The success of the two COVID-19 mRNA vaccines has sparked new enthusiasm for other medical applications, particularly in cancer treatment. In vitro-transcribed (IVT) mRNAs are structurally designed to resemble naturally occurring mature mRNA. Delivery of IVT mRNA via delivery platforms such as lipid nanoparticles allows host cells to produce many copies of encoded proteins, which can serve as antigens to stimulate immune responses or as additional beneficial proteins for supplements. mRNA-based cancer therapeutics include mRNA cancer vaccines, mRNA encoding cytokines, chimeric antigen receptors, tumor suppressors, and other combination therapies. To better understand the current development and research status of mRNA therapies for cancer treatment, this review focused on the molecular design, delivery systems, and clinical indications of mRNA therapies in cancer.

Burnout, depression, anxiety and insomnia among medical staff during the COVID-19 epidemic in Shanghai

Background Coronavirus disease 2019 (COVID-19) has progressively impacted our daily lives, resulting in unexpected physical and mental stress on medical staff. This study is designed to investigate the levels of and risk factors for burnout, depression, anxiety, and insomnia among medical staff during the COVID-19 epidemic breakout in Shanghai, China. Methods This cross-sectional survey was conducted from May 1 to May 31, 2022, among medical staff who were on the frontline during the epidemic breakout in Shanghai from different institutions. The MBI-HSS was used to assess burnout, PHQ-9, GAD-7 and ISI were used to evaluate mental status and insomnia. Results A total of 543 valid questionnaires were collected. The depersonalization, depression, anxiety, and insomnia scores of medical staff were significantly higher during the pandemic in Shanghai compared with norms, while lack of personal achievement scores were decreased. Working time, work unit, work environment and age are important influencers of burnout, depression and anxiety of medical staff. Long working hours are the most likely causes of burnout and emotional disorders. Medical staff in primary hospitals were most likely to suffer from burnout and emotional disorders, while medical staff in tertiary hospitals had a reduced sense of personal achievement. Young medical staff are prone to negative emotions such as depression and anxiety, while older medical staff have a lower sense of personal accomplishment. Medical staff who were not in the shelter hospitals or designated hospitals were more likely to have problems of emotional exhaustion, depersonalization and anxiety than those who were in the shelter hospitals or designated hospitals. Contracting COVID-19 had no effect on medical staff. Emotional exhaustion and depersonalization were positively correlated with anxiety, depression, and sleep disorders while personal achievement was negatively correlated with these factors. Conclusion Medical staff in Shanghai had high burnout, depression, anxiety and insomnia levels during the epidemic outbreak in Shanghai. During the COVID-19, medical staff may suffer different psychological problems which should be concerned. Care and supports about burnout, mental health and insomnia need to be taken to promote the mental health of medical staff according to different characteristics of medical staff.

The factors that affect members' use of a beauty industry matchmaking platform: Validation of the COM-B extended model.

The global impact of COVID-19 has seriously affected health and livelihood in every country or region, especially in terms of physical consumption behaviors. Hairdressing is an essential physical consumption behavior. To prevent infection, the consumption model for using the beauty industry matchmaking platform (BIMP) has been used during the pandemic. This study investigates the changes in the behavior of media app users in the beauty industry in the post-epidemic era of COVID-19. The COM-B model is the basis for a research framework to study the factors that affect changes in behavior in the areas of Capability, Motivation, and Opportunity of the theoretical framework. A new dimension of fashion sense has expanded the application and validation of the COM-B model to determine the causal relationship between the ability to pursue beauty, motivation, fashion sense, and opportunities by using the platform and the dimension of user behavior. The study finds that fashion sense in the BIMP has a positive and significant impact on beauty care ability, self-motivation to pursue beauty and future cooperation opportunities. The ability, motivation and opportunity to act are all positively significant, which is in agreement with the theoretical framework of the COM-B model. There is no mediating effect for motivation between fashion sense and behavior. The results of this study show that increasing the sense of fashion for members using the BIMP will increases active behavior for members using the platform. This study also proposes practical suggestions for the operation of the BIMP based on the results.

COVID-19-Related Self-Stigma, Post-Traumatic Stress Disorder, Insomnia, and Smartphone Addiction Among Frontline Government Workers with COVID-19 Pandemic Control Duties.

Purpose: The duties related to COVID-19 control and prevention may have caused psychological stress for the individuals in charge (eg, frontline government workers) and have reportedly led to mental health issues, such as insomnia and post-traumatic stress disorder (PTSD). However, the prevalence of these COVID-19-related disorders and their associated factors remain unclear. Therefore, the purpose of the present study was to investigate the prevalence rates of insomnia, PTSD, COVID-19-related self-stigma, and smartphone addiction, along with the identification of risk factors and protective factors for Taiwan frontline government workers with COVID-19 pandemic control duties. Methods: The survey was carried out with 151 participants between September and October 2021. All participants completed the Fear of COVID-19 Scale (assessing fear of COVID-19), Self-Stigma Scale (assessing self-stigma during the COVID-19 pandemic), Smartphone Application-Based Addiction Scale (assessing the risk of smartphone addiction), Insomnia Severity Index (assessing insomnia), Impacts of Event Scale-6 (assessing PTSD), and a self-designed set of questions assessing trait resilience. Results: The results showed that the prevalence rate was 31.1% for insomnia and 33.8% for PTSD. Furthermore, service duration (adjusted odds ratio [AOR] = 0.93; 95% confidence interval [CI] = 0.86, 0.999) and trait resilience (AOR = 0.19; 95% CI = 0.08, 0.46) were protective factors and fear of COVID-19 (AOR = 1.91; 95% CI = 1.02, 3.57) was a risk factor for insomnia. Fear of COVID-19 (AOR = 2.63; 95% CI = 1.35, 5.14), self-stigma (AOR = 3.62; 95% CI = 1.19, 11.02), and smartphone addiction (AOR = 1.09, 95% CI = 1.001, 1.19) were risk factors, and trait resilience was a protective factor (AOR = 0.58; 95% CI = 0.29, 1.17) for PTSD. Conclusion: The findings demonstrated a high prevalence of insomnia and PTSD. Risk-reducing strategies and protective factor promotion strategies are recommended to help reduce the symptoms of insomnia and PTSD among Taiwan frontline government workers.

The Associations Between Accelerometer-Measured Physical Activity Levels and Mental Health in Children and Adolescents with Intellectual Disabilities During the COVID-19 Pandemic.

To examine the associations between physical activity (PA) levels and mental health in children and adolescents with intellectual disabilities (IDs) during the COVID-19 pandemic, 117 participants aged between 6 and 17 years with IDs from 10 Hong Kong special schools were included. There were positive dose-response associations between PA (i.e., light PA, moderate PA, and vigorous PA) and mental health, and participants with higher levels of moderate-to-vigorous PA (MVPA) and self-concept (SC) had better social quality of life (QoL) than those with lower levels of MVPA and SC. Moreover, personal and environmental factors such as age, body mass index, school, sex, ID level, and parental education level influenced the PA levels and QoL in children and adolescents with IDs.

The impact of COVID-19 lockdown on maternal and neonatal outcomes of uninfected woman in late pregnancy: A multicenter study in China (preprint)

Background COVID-19 pandemic has had direct and indirect impacts on health-care system and maternal and neonatal health, but no multicenter evidence from China of this effects has been undertaken. The purpose of this study was to investigate the impacts of COVID-19 lockdown on maternal and fetal outcomes in China.Methods This retrospective cohort study included 3540 women in their late pregnancy without COVID-19 who received perinatal healthcare in three hospitals in Wuhan, Shanghai and Haikou during COVID-19 lockdown period in 2020 or the non-lockdown period in 2019. Propensity-score matching was used to compare preterm birth (< 37 weeks) and its classification, very preterm birth (< 34 weeks), caesarean section and its indications, the length of hospital stay, birth weight and other pregnancy outcomes between two groups.Results Preterm births before 37 weeks’ gestation (5.4% vs. 5.3%, P = 0.83) and very preterm birth (0.7% vs. 0.8%, P = 0.58) were not significantly changed overall. But medical-induced preterm birth before 37 weeks’ gestation in Wuhan was decreased (0.8% vs. 1.7%, P = 0.04). The cesarean section for maternal factors was decreased (21.4% vs. 24.3%, P = 0.003). The length of maternal (4.2d vs 4.5d, P < 0.001) and neonatal (3.4d vs 3.7d, P < 0.001) hospital stay was shortened. No overall significant effects were identified for other outcomes included in the quantitative analysis: maternal gestational diabetes; pregnancy-induced hypertension; preterm birth with premature rupture of membranes; low birthweight (< 2500 g); neonatal intensive care unit admission; or abnormal Apgar score.Conclusions This study demonstrated that there was protective impact of the COVID-19 lockdown on maternal and neonatal outcomes among women in their late pregnancy in China.

Beauty Consumption Matchmaking Mechanism for Confirming the Requirement Specification of App Development in the Post-COVID-19 Era

COVID-19 began to spread worldwide in early 2020. Various governments have taken measures such as isolation, travel bans, and evacuation, mandating people to wear masks and go out less, in an attempt to prevent the spread of the virus. Governments also restrict human contact service industries, including beauty and hair salons. When the pandemic was very serious, consumers had great doubts about going for hairdressing so the beauty industry was greatly affected. This study designed and developed an app platform that considers the COVID-19 and is used for the psychological role of consumer safety. The methodology of this research is a qualitative study. Based on the Capability, Opportunity, Motivation, Behavior (COM-B) model, and presenting the context of capabilities, opportunities, and motives of the theoretical framework, this study investigates the factors that identify the demand for the development of the platform for the beauty industry app matching mechanism. Four groups of people including consumers, beauty technicians, store managers, and application development engineers all conduct interviews based on their ability, opportunity, and motivation after experiencing the using application of OpenBeautiful. The results found that all groups of people already had the knowledge and ability to avoid infection in a pandemic, so it was possible to establish the need and feasibility of using the app platform. The use of the beauty industry app platform can bring new consumption patterns and career opportunities, and can trigger more business behavior activities. Therefore, this study starts from the COM-B model, and then explores the user needs of the platform according to the COM-B model framework, and proposes the mechanism and platform of app matching. Finally, based on the conclusion of the study, we propose practices and suggestions for the future operation of the app matching platform.

Impact of Coronavirus Disease 2019 Pandemic on Pediatric Out-of-Hospital Cardiac Arrest in the Emergency Department.

Background: Out-of-hospital cardiac arrest (OHCA) in children is a critical condition with a poor prognosis. After the coronavirus disease 2019 (COVID-19) pandemic developed, the epidemiology and clinical characteristics of the pediatric emergency department (PED) visits have changed. This study aimed to analyze the impact of the COVID-19 pandemic on pediatric OHCA in the PED. Methods: From January 2018 to September 2021, we retrospectively collected data of children (18 years or younger) with a definite diagnosis of OHCA admitted to the PED. Patient data studied included demographics, pre-/in-hospital information, treatment modalities; and outcomes of interest included sustained return of spontaneous circulation (SROSC) and survival to hospital-discharge (STHD). These were analyzed and compared between the periods before and after the COVID-19 pandemic. Results: A total of 97 patients with OHCA (68 boys and 29 girls) sent to the PED were enrolled in our study. Sixty cases (61.9%) occurred in the pre-pandemic period and 37 during the pandemic. The most common age group was infants (40.2%) (p = 0.018). Asystole was the most predominant cardiac rhythm (72.2%, P = 0.048). Eighty patients (82.5%) were transferred by the emergency medical services, 62 (63.9%) gained SROSC, and 25 (25.8%) were STHD. During the COVID-19 pandemic, children with non-trauma OHCA had significantly shorter survival duration and prolonged EMS scene intervals (both p < 0.05). Conclusion: During the COVID-19 pandemic, children with OHCA had a significantly lower rate of SROSC and STHD than that in the pre-pandemic period. The COVID-19 pandemic has changed the nature of PED visits and has affected factors related to ROSC and STHD in pediatric OHCA.

Mental health status among prison officers in the process of enforcing the law during COVID-19 epidemic: A cross-sectional survey from China

Background: A global public health emergency triggered by the Coronavirus Disease 2019 (COVID-19) epidemic may have are markable psychological impact on the population. There is still limited psychological research on police officers, especially prison officers in the process of enforcing the law. The present study aims to identify prevalence and influencing factors on mental health status among frontline prison officers in China during the prevention and control of the COVID-19 epidemic. Methods: A cross-sectional survey with a sample of 981 frontline prison officers was conducted using snowball sampling approach. The self-administered questionnaire consisted of 4 parts: (i) informed consent form;(ii) socio-demographic section;(iii) work and life situations during the prevention and control of the COVID-19 epidemic;(iv) the Chinese version of the 12-item General Health Questionnaire (GHQ-12). Univariate analysis and multivariable logistic regression were performed to identify factors influencing mental health status. Results: The prevalence of being prone to mental health problems (GHQ-12 score >= 4) was 33.43% among frontline prison officers. The results of GHQ-12 factors analysis indicated that the prison officers suffered from psychological issues was related to anxiety and depression, which main symptoms were unhappy and depressed, lost sleep over worry and constantly under strain. Multivariate logistic regression analysis revealed that male (OR = 1.573, 95% CI:1.385-1.853), lockdown shift inside the prison(OR = 2.203, 95% CI:2.139-2.297), more night shifts (OR = 2.163, 95% CI:2.031-2.317;OR = 2.749, 95% CI:2.194-2.901), more smoking (OR = 1.100, 95% CI:1.037-2.168), poor self-reported physical condition (OR = 1.947, 95% CI:1.478-2.250), chronic or serious illness history(OR = 1.870, 95% CI:1.314-2.660;OR = 2.214, 95% CI:1.460-2.812) were risk factors for mental health among frontline prison officers, while regular diet (OR = 0.779, 95% CI:0.539-0.928), more physical exercise (OR = 0.702, 95% CI:0.548-0.899;OR = 0.641, 95% CI:0.316-0.887), more communication with family members (OR = 0.437, 95% CI:0.295-0.616) were protective factors. Conclusion: Chinese frontline prison officers experienced different psychological stress coming from the prevention and control of this epidemic. Therefore, continued surveillance of psychological problems and targeted mental health care for frontline prison officers were urgent. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Tafenoquine and its derivatives as inhibitors for the severe acute respiratory syndrome coronavirus 2.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely affected human lives around the world as well as the global economy. Therefore, effective treatments against COVID-19 are urgently needed. Here, we screened a library containing Food and Drug Administration (FDA)-approved compounds to identify drugs that could target the SARS-CoV-2 main protease (Mpro), which is indispensable for viral protein maturation and regard as an important therapeutic target. We identified antimalarial drug tafenoquine (TFQ), which is approved for radical cure of Plasmodium vivax and malaria prophylaxis, as a top candidate to inhibit Mpro protease activity. The crystal structure of SARS-CoV-2 Mpro in complex with TFQ revealed that TFQ noncovalently bound to and reshaped the substrate-binding pocket of Mpro by altering the loop region (residues 139-144) near the catalytic Cys145, which could block the catalysis of its peptide substrates. We also found that TFQ inhibited human transmembrane protease serine 2 (TMPRSS2). Furthermore, one TFQ derivative, compound 7, showed a better therapeutic index than TFQ on TMPRSS2 and may therefore inhibit the infectibility of SARS-CoV-2, including that of several mutant variants. These results suggest new potential strategies to block infection of SARS-CoV-2 and rising variants.