Expert consensus on prevention and control of infection in COVID-19 designated hospitals

OBJECTIVE: To further standardize and guide the infection prevention and control(IPC) in designated hospitals so as to effectively ensure the stability, order and safety of medical treatment, ensure the safety of health care workers and patients, and reduce cross infections caused by the transmission of COVID-19. METHODS: The experts who repeatedly participated in the national COVID-19 medical treatment and IPC were invited to compile the consensus based on latest national norms, characteristics of the omicron and situation of epidemic prevention and control. RESULTS: The consensus consisted of two major parts: comprehensive coverage and control of infections in designated hospitals, with 47 recommendations involved. CONCLUSION: The expert consensus will provide guidance for the upcoming prevention and control of infection in designated hospitals.

mRNA Vaccine - A New Cancer Treatment Strategy.

The corresponding mRNA vaccines Comirnaty (BNT162b2) and Spikevax (mRNA-1273) have been authorized for emergency use since the COVID-19 outbreak. Most clinical researches have also discovered that the mRNA vaccine is a revolutionary strategy for preventing and treating numerous diseases, including cancers. Unlike viral vectors or DNA vaccines, mRNA vaccines cause the body to directly produce proteins following injection. Delivery vectors and mRNAs that encode tumor antigens or immunomodulatory molecules work together to trigger an anti-tumor response. Before mRNA vaccines may be employed in clinical trials, a number of challenges need to be resolved. These include establishing effective and safe delivery systems, generating successful mRNA vaccines against diverse types of cancers, and proposing improved combination therapy. Therefore, we need to improve vaccine-specific recognition and develop mRNA delivery mechanisms. This review summarizes the complete mRNA vaccines' elemental composition and discusses recent research progress and future direction for mRNA tumor vaccines.

Study on Flavonoids and Bioactivity Features of Pericarp of Citrus reticulata "Chachi" at Different Harvest Periods.

Dry mature pericarp of Citrus reticulata "Chachi" (PCR), Pericarpium Citri Reticulatae Chachiensis, is a traditional Chinese medicine that displays characteristics of different usage at different harvest times in clinical use. The corresponding changes in the bioactive components in PCR from different harvest times remain unclear. Therefore, in this study, broadly targeted metabolomics technology was used to compare the differences in bioactive components among pericarps of PCR, which are the raw material of PCR at different growth stages. In the results, 210 kinds of flavonoid metabolites were detected. The content of hesperidin in red PCR harvested in December was higher than that in Citri Reticulatae Pericarpium Viride (CRPV) and reddish PCR harvested from July to November. Furthermore, the content of nobiletin, tangeretin, and 3,3',4',5,6,7,8-heptamethoxyflavone in CRPV from July to September was higher than that in the PCR harvested at other times. In addition, the result of cluster analysis and PCA showed that CRPV harvested from July to September had an obvious grouping pattern with the reddish PCR and the red PCR harvested from October to December. Differential metabolites in six comparison groups (A1 vs. A6, A1 vs. A2, A2 vs. A3, A3 vs. A4, A4 vs. A5, A5 vs. A6) were 67, 48, 14, 51, 42, and 40, respectively. The common differential metabolite of four comparison groups was 3',4',7-trihydroxyflavone (A1 vs. A2, A2 vs. A3, A3 vs. A4, A4 vs. A5). All the flavonoid differential metabolites screened were enriched in 16 metabolic pathways. Moreover, the results of the evaluation of the total antioxidant capacity indicated that CRPV in August was a suitable raw material for the production of antioxidants. Through molecular docking, the content of potential anti-SARS-CoV-2 components in the PCR in October was higher than that in the PCR in other periods. These results further proved that PCR at different harvest times was endowed with different efficacy and usage due to the difference in the accumulation of bioactive components.

The effect of information overload and perceived risk on tourists' intention to travel in the post-COVID-19 pandemic.

Since the COVID-19 pandemic, the tourism economy has been seriously affected. China has implemented a direct traveling management mechanism and recovered from the pandemic faster than the rest of the world. However, the COVID-19 situation is complicated and uncontrollable because of the available unclear information including difficult medical terminologies. This study attempts to find the determinants of the travel intention of China's tourists in the post-COVID-19 epidemic. Along with information overload and perception risk, an expanded research model of the Theory of Planned Behavior (TPB) was employed to propose the theoretical framework of this study. A survey was conducted among 518 tourists who spend their holiday in Hainan, which is a popular tourist destination in China. The empirical results show that information overload positively and significantly impacted perceived risk. Furthermore, perceived risk negatively affects the intention to travel. Perceived risk also negatively affected the attitude toward traveling. However, response self-efficacy did not have a significant effect on the intention to travel. Finally, based on the analysis results, this study proposes relevant research contributions and practical recommendations with management implications for the travel industries.

Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.

Machine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors' intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806-0.811), accuracy: 0.815 (0.812-0.818), precision: 0.840 (0.835-0.845), and F1 score of XGBoost: 0.843 (0.840-0.845) and recall of SVM: 0.991 (0.988-0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies.

ECG Utilization Patterns of Patients With Arrhythmias During COVID-19 Epidemic and Post-SARS-CoV-2 Eras in Shanghai, China.

Background: The COVID-19 pandemic has led to concerns around its subsequent impact on global health. Objective: To investigate the health-seeking behavior, reflected by ECG utilization patterns, of patients with non-COVID-19 diseases during and after COVID-19 epidemic. Methods: Taking advantage of the remote ECG system covering 278 medical institutions throughout Shanghai, the numbers of medical visits with ECG examinations during the lockdown (between January 23 and April 7, 2020), post-lockdown (between April 8 and December 31, 2020) and post-SARS-CoV-2 (between January 23 and April 7, 2021) periods were analyzed and compared against those during the same periods of the preceding years (2018 and 2019). Results: Compared with the same period during pre-COVID years, the number of medical visits decreased during the lockdown (a 38% reduction), followed by a rebound post-lockdown (a 17% increase) and a fall to the baseline level in post-SARS-CoV-2 period. The number of new COVID-19 cases announced on a given day significantly correlated negatively with the numbers of medical visits during the following 7 days. Medical visit dynamics differed for various arrhythmias. Whereas medical visits for sinus bradycardia exhibited a typical decrease-rebound-fallback pattern, medical visits for atrial fibrillation did not fall during the lockdown but did exhibit a subsequent increase during the post-lockdown period. By comparison, the volume for ventricular tachycardia remained constant throughout this entire period. Conclusion: The ECG utilization patterns of patients with arrhythmias exhibited a decrease-rebound-fallback pattern following the COVID-19 lockdowns. Medical visits for diseases with more severe symptoms were less influenced by the lockdowns, showing a resilient demand for healthcare.

Epidemiology, management, and outcomes of atrial fibrillation among 30 million citizens in Shanghai, China from 2015 to 2020: A medical insurance database study.

Background: Atrial fibrillation(AF) has become a significant public health concern in China, with population aging and urbanization. Methods: Data screening was performed for 30,244,930 subjects with medical insurance in the Shanghai Municipal Health Commission database between 2015 and 2020. Patients diagnosed with AF were identified and further assessed for treatment information and clinical outcomes, as well as sex differences and impact of COVID-19 pandemic on AF managment. Findings: AF prevalence was 0.88% in Shanghai, which increased with age and reached 6.70% at subjects 80 years and over. AF was more prevalent in women compared with men (0.89% vs. 0.88%, p<0.0001), which could be attributed to higher AF burden in women over 80 years. Driven by increased prescription of non-vitamin K antagonist oral anticoagulants, anticoagulant use increased from 19.46% in 2015 to 56.57% in 2020. The number of left atrial appendage closure increased from 0.16% in 2015 to 1.23% in 2020. Rhythm control strategy was increasingly adopted, as the use of antiarrhythmic drugs doubled and ablation increased by 21% in 2020 compared to 2015. Compared with men, women were less prone to receive rhythm control treatments, including antiarrhythmics, ablation and cardioversion, but more likely to adopt rate control drugs. During the 5.5 years follow-up, the incidences of stroke, transient ischemic attack, systemic embolism, bleeding, myocardial infarction, and in-hospital death were 6.09%, 5.74%, 1.44%, 5.11%, 8.41%, and 12.84% in patients with index diagnosis of AF in 2015, respectively. Interpretation: The burdens of AF and AF-related outcomes in Shanghai are high. Management of AF is markedly improved in recent years, and was not or only slightly impeded by the COVID-19 pandemic. There are sex differences in the prevalence, management, and outcomes of AF. Funding: Shanghai Hospital Development Center, National Natural Science Foundation of China and Shanghai Municipal Science and Technology Commission.

Pregnant women's coping strategies, participation roles and social support in the online community during the COVID-19.

Pregnant women are experiencing enormous physical changes and suffering pregnancy-related losses, which may lead to depression symptoms during pregnancy. Given that the onslaught of COVID-19 had exacerbated pregnant women's anxiety because of disruptions in antenatal care and concerns regarding safe delivery, it is worth exploring how they obtain social support to cope with stress during COVID-19. Although many works have explored the impact of coping resources that people have on coping strategies, few studies have been done on the relationship between people's coping strategies and their acquisition of coping resources such as social support. To fill this gap, based on the stress and coping theory (SCT) and social penetration theory (SPT), this study investigates the impacts of pregnant women's different coping strategies on the acquisition of social support and the moderating role of the adverse impacts of COVID-19 and their online participation roles (support providers vs. support seekers) using the data of 814 pregnant women's online behavior from a parenting community in China. Our study indicates that both women's superficial level disclosure and personal level disclosure positively affect online social support received. Moreover, self-disclosure about the adverse impacts of COVID-19 negatively moderates the relationship between personal level disclosure and social support received. Participation role positively moderates the relationship between personal level disclosure and social support received, but negatively moderates the relationship between superficial level disclosure and social support received. This paper makes theoretical contributions to the literature of SCT, SPT and the literature about social support in online communities.

Utilization Intention of Community Pharmacy Service under the Dual Threats of Air Pollution and COVID-19 Epidemic: Moderating Effects of Knowledge and Attitude toward COVID-19.

The utilization of pharmacy services in response to the threat of COVID-19 infection remains unclear in areas suffering from air pollution, and little is known regarding the effects of knowledge and attitude (KA) toward COVID-19 on this preventive behavior. This study aimed to explore how the residents perceived and reacted to the new threats of the epidemic and how KA may affect the correlation. Based on the health belief model (HBM), this research took the pharmacy service utilization (PSU) as an example to explain the preventive behavior. The samples were 375 respondents recruited from five districts near the industrial parks. T-test, ANOVA, and regression analyses of SPSS 22.0 were used to analyze the data. Test results show that self-efficacy was the strongest predictor, followed by the net perceived benefit. KA moderated the association of perceived threat and PSU intention. The levels of air pollution of a district may not be a good predictor for the preventive behavior against COVID-19.

Three-dimensional reconstruction by electron tomography for the application to ultrastructural analysis of SARS-CoV-2 particles.

SARS-CoV-2 is the cause of COVID-19. The three-dimensional morphology of viral particles existing and multiplying in infected cells has not been established by electron tomography, which is different from cryo-electron tomography using frozen samples. In this study, we establish the morphological structure of SARS-CoV-2 particles by three-dimensional reconstruction of images obtained by electron tomography and transmission electron microscopy of biological samples embedded in epoxy resin. The characteristic roots of spike structures were found to be arranged at the surface of a virion covered with an envelope. A high-electron-density structure that appears to be a nucleocapsid was observed inside the envelope of the virion on three-dimensional images reconstructed by electron tomography. The SARS-CoV-2 particles that budded in the vacuoles in the cytoplasm were morphologically identical to those found outside the cells, suggesting that mature and infectious SARS-CoV-2 particles were already produced in the vacuoles. Here, we show the three-dimensional morphological structure of SARS-CoV-2 particles reconstructed by electron tomography. To control infection, inhibition of viral release from vacuoles would be a new target in the development of prophylactic agents against SARS-CoV-2.

Hydroxychloroquine administration exacerbates acute kidney injury complicated by lupus nephritis.

BACKGROUND: Hydroxychloroquine (HCQ) has been recommended as a basic treatment for lupus nephritis (LN) during this decade based on its ability to improve LN-related renal immune-mediated inflammatory lesions. As a classical lysosomal inhibitor, HCQ may inhibit lysosomal degradation and disrupt protective autophagy in proximal tubular epithelial cells (PTECs). Therefore, the final renal effects of HCQ on LN need to be clarified. METHOD: HCQ was administered on spontaneous female MRL/lpr LN mice with severe proteinuria daily for 4 weeks. Moreover, the MRL/lpr mice with proteinuric LN were subjected to cisplatin-induced or unilateral ischemia/reperfusion (I/R)-induced acute kidney injury (AKI) after 2 weeks of HCQ preadministration. RESULTS: As expected, HCQ treatment increased the survival ratio and downregulated the levels of serum creatinine in the mice with LN, ameliorated renal lesions, and inhibited renal interstitial inflammation. Unexpectedly, HCQ preadministration significantly increased susceptibility to and delayed the recovery of AKI complicated by LN, as demonstrated by an increase in PTEC apoptosis and expression of the tubular injury marker KIM-1 as well as the retardation of PTEC replenishment. HCQ preadministration suppressed the proliferation of PTECs by arresting cells in G1/S phase and upregulated the expression of cell cycle inhibitors. Furthermore, HCQ preadministration disrupted the PTEC autophagy-lysosomal pathway and accelerated PTEC senescence. CONCLUSION: HCQ treatment may increase susceptibility and delay the recovery of AKI complicated by LN despite its ability to improve LN-related renal immune-mediated inflammatory lesions. The probable mechanism involves accelerated apoptosis and inhibited proliferation of PTECs via autophagy-lysosomal pathway disruption and senescence promotion.

Study on flavonoid and bioactivity features of the pericarp of Citri Reticulatae 'Chachi' during storage

The mature pericarp of Citri Reticulatae 'Chachi' (PCRC) is one of the six traditional Chinese medicinal materials that should be used after long storage, and it was regarded that the longer the medicine was stored, the better. However, the aging mechanism of the medicine is not clear. To further investigate the effect of aging on the main active flavonoids of PCRC, ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-MS/MS) and metabolomics analysis were used to analyze the flavonoids of PCRC stored for different periods. In the results, 219 flavonoids were detected. 5,7,3',4',5'-pentamethoxy dihydroflavone and 2'-hydroxy-3,4,5,3'4',6'-hexamethoxychalcone were found from PCRC for the first time. According to the clustering analysis of metabolites, aging times of 0 year, 1 year, and 2 year were clustered into one group, and aging times of 3 year, 4 year, and 29 year were clustered into the other group. Quantitative analysis showed that the former group contained a greater amount of 4 flavonoids than the latter group, while the latter group contained a greater amount of 15 polymethoxyflavonoids. The newly harvested PCRC was compared with the other 5 groups of PCRC (stored for 1, 2, 3, 4, and 29 years). Eight flavonoids, tectochrysin, apigenin, 2'-hydroxyisoflavone, luteolin, 6-hydroxyluteolin, gallocatechin, quercetin -O- acetylhexoside and apigenin -7-O-[β-D-glucuronide (1→2) -O-β-D-glucuronide], were used as marker components to discriminate newly harvested PCRC and aging PCRC. In addition, the antioxidant potency composite index (APC) indicated that the PCRC stored for three or four years had stronger antioxidant activity than the PCRC stored for other periods. By means of molecular docking, it was reviewed that the amount of antiviral components against SARS-CoV-2 in freshly harvested PCRC was significantly higher than that in aging PCRC. The results in this study supplied scientific data for quality control, evaluation, and rational utilization of PCRC and basic information for further analysis of the metabolic regulation of the active components of the PCRC.

The Predictive Value of Myoglobin for COVID-19-Related Adverse Outcomes: A Systematic Review and Meta-Analysis.

Objective: Cardiac injury is detected in numerous patients with coronavirus disease 2019 (COVID-19) and has been demonstrated to be closely related to poor outcomes. However, an optimal cardiac biomarker for predicting COVID-19 prognosis has not been identified. Methods: The PubMed, Web of Science, and Embase databases were searched for published articles between December 1, 2019 and September 8, 2021. Eligible studies that examined the anomalies of different cardiac biomarkers in patients with COVID-19 were included. The prevalence and odds ratios (ORs) were extracted. Summary estimates and the corresponding 95% confidence intervals (95% CIs) were obtained through meta-analyses. Results: A total of 63 studies, with 64,319 patients with COVID-19, were enrolled in this meta-analysis. The prevalence of elevated cardiac troponin I (cTnI) and myoglobin (Mb) in the general population with COVID-19 was 22.9 (19-27%) and 13.5% (10.6-16.4%), respectively. However, the presence of elevated Mb was more common than elevated cTnI in patients with severe COVID-19 [37.7 (23.3-52.1%) vs.30.7% (24.7-37.1%)]. Moreover, compared with cTnI, the elevation of Mb also demonstrated tendency of higher correlation with case-severity rate (Mb, r = 13.9 vs. cTnI, r = 3.93) and case-fatality rate (Mb, r = 15.42 vs. cTnI, r = 3.04). Notably, elevated Mb level was also associated with higher odds of severe illness [Mb, OR = 13.75 (10.2-18.54) vs. cTnI, OR = 7.06 (3.94-12.65)] and mortality [Mb, OR = 13.49 (9.3-19.58) vs. cTnI, OR = 7.75 (4.4-13.66)] than cTnI. Conclusions: Patients with COVID-19 and elevated Mb levels are at significantly higher risk of severe disease and mortality. Elevation of Mb may serve as a marker for predicting COVID-19-related adverse outcomes. Prospero Registration Number: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020175133, CRD42020175133.

Prevalence and Impact Factors of COVID-19 Vaccination Hesitancy Among Breast Cancer Survivors: A Multicenter Cross-Sectional Study in China.

Cancer patients are at a high risk of being infected with COVID-19 and have a poor prognosis after infection. Breast cancer is one of the most common cancers. Since vaccination is an effective measure to prevent the spread of COVID-19, we studied the vaccination rate among breast cancer survivors and analyzed their characteristics to provide evidence for boosting the vaccination rate. The researchers conducted a multicenter, cross-sectional study on 747 breast cancer survivors from six hospitals in Wuhan city between June 5, 2021, and June 12, 2021. The self-administrated questionnaires based on relevant studies were distributed. The researchers then compared differences in characteristics among vaccinated patients, hesitant patients, and non-vaccinated patients. Moreover, they performed univariable and multivariable logistic regression analyses to identify potential factors associated with vaccination hesitancy. The researchers assessed a total of 744 breast cancer survivors -94 cases in the vaccinated group, 103 in the planning group, 295 in the hesitancy group, and 252 in the refusal group. The vaccination rate was 12.63% (95% CI 10.25-15.02%) and 37.23% (95% CI 27.48-47.82%) patients reported adverse reactions. The vaccination hesitancy/refusal rate was 73.52% (95% CI 70.19-76.66%), which was independently associated with current endocrine or targeted therapy (odds ratio [OR] = 1.52, 95% CI 1.03-2.24), no notification from communities or units (OR = 2.46, 95% CI 1.69-3.59) and self-perceived feel (general vs. good, OR = 1.46, 95% CI 1.01-2.13; bad vs. good, OR = 4.75, 95% CI 1.85-12.16). In the hesitancy/refusal group, the primary reason was "I did not know who to ask whether I can get vaccinated" (46.07%), the person who would most influence decisions of patients was the doctor in charge of treatment (35.83%). Effective interaction between doctors and patients, simple and consistent practical guidelines on vaccination, and timely and positive information from authoritative media could combat misinformation and greatly reduce vaccine hesitancy among breast cancer survivors.

Prediction of COVID-19 epidemic situation via fine-tuned IndRNN.

The COVID-19 pandemic is the most serious catastrophe since the Second World War. To predict the epidemic more accurately under the influence of policies, a framework based on Independently Recurrent Neural Network (IndRNN) with fine-tuning are proposed for predict the epidemic development trend of confirmed cases and deaths in the United Stated, India, Brazil, France, Russia, China, and the world to late May, 2021. The proposed framework consists of four main steps: data pre-processing, model pre-training and weight saving, the weight fine-tuning, trend predicting and validating. It is concluded that the proposed framework based on IndRNN and fine-tuning with high speed and low complexity, has great fitting and prediction performance. The applied fine-tuning strategy can effectively reduce the error by up to 20.94% and time cost. For most of the countries, the MAPEs of fine-tuned IndRNN model were less than 1.2%, the minimum MAPE and RMSE were 0.05%, and 1.17, respectively, by using Chinese deaths, during the testing phase. According to the prediction and validation results, the MAPEs of the proposed framework were less than 6.2% in most cases, and it generated lowest MAPE and RMSE values of 0.05% and 2.14, respectively, for deaths in China. Moreover, Policies that play an important role in the development of COVID-19 have been summarized. Timely and appropriate measures can greatly reduce the spread of COVID-19; untimely and inappropriate government policies, lax regulations, and insufficient public cooperation are the reasons for the aggravation of the epidemic situations. The code is available at https://github.com/zhhongsh/COVID19-Precdiction. And the prediction by IndRNN model with fine-tuning are now available online (http://47.117.160.245:8088/IndRNNPredict).

Low dose of emetine as potential anti-SARS-CoV-2 virus therapy: preclinical in vitro inhibition and in vivo pharmacokinetic evidences.

The global pandemic of COVID-19 has attracted extensive drug searching interets for the new coronavirus SARS-CoV-2. Although currently several of clinically used "old" drugs have been repurposed to this new disease for the urgent clinical investigation, there is still great demand for more effective therapies for the anti-infections. Here we report the discovery that an "old" drug Emetine could potently inhibit SARS-CoV-2 virus replication and displayed virus entry blocking effect in Vero cells at low dose. In addition, Emetine could significantly reduce the lipopolysaccharide (LPS) induced interleukin-6 (IL-6) protein level and moderately reduce the tumor necrosis factor (TNF-α) protein level in the M1 polarized THP-1 macrophages. In vivo animal pharmacokinetics (PK) study revealed that Emetine was enriched in the lung tissue and had a long retention time (over 12 h). With 1 mg/kg single oral dose, the effective concentration of Emetine in lung was up to 1.8 µM (mice) and 1.6 µM (rats) at 12 h, which is over 200-fold higher than the EC50 of the drug. The potent in vitro antiviral replication efficacy and the high enrichment in target tissue, combining with the well documented safety profiles in human indicate that low dose of Emetine might be a potentially effective anti-SARS-CoV-2 infection therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43556-020-00018-9.

Enhancing frontline workforce volunteerism through exploration of motivations and impact during the COVID-19 pandemic.

OBJECTIVES: During a pandemic, healthcare workers are requested to volunteer for potentially high-risk frontline duties outside of usual hospital and primary care clinic settings in order to better serve vulnerable communities. Examination of volunteer motivations and impact of such experiences can drive more effective pandemic response efforts with regards to volunteer recruitment and retention. This study aims to explore the motivational factors underlying healthcare worker volunteerism in COVID-19 pandemic response operations in the community, and to describe the impact of such operations on volunteers, in order to highlight important volunteer recruitment strategies and ensure volunteer sustainability. METHODS: A qualitative phenomenological approach is taken in this study through the use of semi-structured individual interviews of healthcare staff, to provide in-depth exploration of personal experiences. Staff were purposefully sampled to ensure diversity of personal and professional backgrounds. RESULTS: A total of 35 staff, consisting of 17 males and 18 females from medical, nursing, allied health, and administrative backgrounds, who participated in COVID-19 community-based operations in migrant worker dormitories and swab isolation facilities were interviewed. The main motivational factors were volunteer functions of values, understanding and enhancement. Participants were positively impacted on personal and professional levels, including self-growth, societal awareness, as well as skills development in leadership and team management. CONCLUSIONS: Healthcare organizations should consider volunteer functions in matching individual motivations to volunteer opportunities. Additionally, personal narratives and role-modelling by senior staff can serve as useful adjunct strategies to volunteer recruitment, while providing pre-pandemic preparedness, reassurance of safety, support, and recognition.

Identify and measure the degree of over-prevention behaviors in the post-COVID-19 era in China.

BACKGROUND: With the spread of vaccines, more and more countries have controlled the outbreak of the COVID-19. In this post-epidemic era, these countries began to revive their economy. However, pollution remains in the environment, and people's physical and psychological health has been under threat due to some over-prevention behaviors. Instruments for governmental agencies to manage these behaviors are not yet available. This study aims to develop a measurement model to identify and measure the degree of over-prevention behaviors during the COVID-19 epidemic in China. METHODS: A survey online was conducted to collect cognition from 1528 Chinese people, including descriptions of various over-prevention behaviors defined by health authorities. Factor analyses were used to develop the measurement model and test its validity. Logistic regression analyses were conducted to explore demographic characteristics, indicating people who are inclined to exhibit over-prevention behaviors. RESULTS: Four main factors were extracted to develop the model (eigenvalue = 7.337, 3.157, 1.447, and 1.059, respectively). The overall reliability (Cronbach's α = 0.900), the convergent (AVE > 0.5, CR > 0.8 for each factor) and discriminant validity is good. There is also a good internal consistency among these factors (Cronbach's α = 0.906, 0.852, 0.882, and 0.763, respectively). In Factor 1, gender has a negative effect (Beta = - 0.294, P <  0.05, OR = 0.745), whereas employment has a positive effect. Workers in institutions exhibit the greatest effect (Beta = 0.855, P <  0.001, OR = 2.352). In Factor 2, employment has a negative effect, with workers in institutions exhibit the greatest role (Beta = - 0.963, P <  0.001, OR = 0.382). By contrast, education level has a positive effect (Beta = 0.430, P <  0.001, OR = 1.537). In Factor 3, age plays a negative role (Beta = - 0.128, P < 0.05, OR = 0.880). CONCLUSIONS: People show a discrepancy in the cognition toward various over-prevention behaviors. The findings may have implications for decision-makers to reduce the contradiction between the epidemic and economic revival via managing these behaviors.

Use of donor-specific red blood cell transfusions for patients undergoing liver transplantation during the COVID-19 pandemic.

BACKGROUND: Increased risks have been found for patients undergoing liver transplantation due to the blood supply shortage following the ongoing coronavirus disease 2019 (COVID-19) pandemic. Hence, exploring a method to alleviate this dilemma is urgent. This phase I, nonrandomized, prospective trial aimed to evaluate the safety and feasibility of using donor-specific red blood cell transfusion (DRBCT) as an urgent measurement to alleviate the blood supply shortage in deceased donor liver transplantation (DDLT). METHODS: The outcomes of 26 patients who received DRBCT and 37 patients in the control group who only received 3rd party packed red blood cells (pRBCs) transfusion between May 2020 and January 2021 were compared. RESULTS: Patients receiving DRBCT did not develop transfusion-related complications, and the incidence of postoperative infection was similar to that in the control group (23.1% vs. 18.9%, P=0.688). Because the patients received the red blood cells from organ donors, the median volume of intraoperative allogeneic red blood cell transfusion from blood bank was 4.0 U (IQR 1.1-8.0 U) in the DRBCT group, which is significantly lower than that (7.5 U, IQR 4.0-10.0 U) in the control group (P=0.018). The peak aspartate aminotransferase (AST) level was significantly lower in the DRBCT group than in the control group (P=0.008) and so were the AST levels in the first two days after the operation (P=0.006 and P=0.033). CONCLUSIONS: DRBCT is a safe and effective procedure to lower the need for blood supply and is associated with a reduction in AST levels after transplantation. DRBCT is beneficial to patients receiving life-saving transplantation without sufficient blood supply during the COVID-19 pandemic.