Thyroid function and associated mood changes after COVID-19 vaccines in patients with Hashimoto thyroiditis.

Context: Severe acute respiratory syndrome-coronavirus 2 (COVID-19) vaccines may incur changes in thyroid functions followed by mood changes, and patients with Hashimoto thyroiditis (HT) were suggested to bear a higher risk. Objectives: We primarily aim to find whether COVID-19 vaccination could induce potential subsequent thyroid function and mood changes. The secondary aim was to find inflammatory biomarkers associated with risk. Methods: The retrospective, multi-center study recruited patients with HT receiving COVID-19-inactivated vaccines. C-reactive proteins (CRPs), thyroid-stimulating hormones (TSHs), and mood changes were studied before and after vaccination during a follow-up of a 6-month period. Independent association was investigated between incidence of mood state, thyroid functions, and inflammatory markers. Propensity score-matched comparisons between the vaccine and control groups were carried out to investigate the difference. Results: Final analysis included 2,765 patients with HT in the vaccine group and 1,288 patients in the control group. In the matched analysis, TSH increase and mood change incidence were both significantly higher in the vaccine group (11.9% versus 6.1% for TSH increase and 12.7% versus 8.4% for mood change incidence). An increase in CRP was associated with mood change (p< 0.01 by the Kaplan-Meier method) and severity (r = 0.75) after vaccination. Baseline CRP, TSH, and antibodies of thyroid peroxidase (anti-TPO) were found to predict incidence of mood changes. Conclusion: COVID-19 vaccination seemed to induce increased levels and incidence of TSH surge followed by mood changes in patients with HT. Higher levels of pre-vaccine serum TSH, CRP, and anti-TPO values were associated with higher incidence in the early post-vaccine phase.

Augmented reality for stroke rehabilitation during COVID-19.

BACKGROUND: The lack of the rehabilitation professionals is a global issue and it is becoming more serious during COVID-19. An Augmented Reality Rehabilitation System (AR Rehab) was developed for virtual training delivery. The virtual training was integrated into the participants' usual care to reduce the human trainers' effort so that the manpower scarcity can be eased. This also resulted in the reduction of the contact rate in pandemics. OBJECTIVE: To investigate the feasibility of the AR Rehab-based virtual training when integrated into the usual care in a real-world pandemic setting, by answering questions of whether the integrated trials can help fulfill the training goal and whether the trials can be delivered when resources are limited because of COVID-19. METHODS: Chronic stroke participants were randomly assigned to either a centre-based group (AR-Centre) or a home-based group (AR-Home) for a trial consisting of 20 sessions delivered in a human-machine integrated intervention. The trial of the AR-Centre was human training intensive with 3/4 of each session delivered by human trainers (PTs/OTs/Assistants) and 1/4 delivered by the virtual trainer (AR Rehab). The trial of the AR-Home was virtual training intensive with 1/4 and 3/4 of each session delivered by human and virtual trainers, respectively. Functional assessments including Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Lower Extremity (FMA-LE), Functional Ambulation Category (FAC), Berg Balance Scale (BBS), Barthel Index (BI) of Activities of Daily Living (ADL), and Physical Component Summary (SF-12v2 PCS) and Mental Component Summary (SF-12v2 MCS) of the 12-Item Short Form Health Survey (SF-12v2), were conducted before and after the intervention. User experience (UX) using questionnaires were collected after the intervention. Time and human resources required to deliver the human and virtual training, respectively, and the proportion of participants with clinical significant improvement were also used as supplementary measures. RESULTS: There were 129 patients from 10 rehabilitation centres enrolled in the integrated program with 39 of them were selected for investigation. Significant functional improvement in FMA-UE (AR-Centre: p = 0.0022, AR-Home: p = 0.0043), FMA-LE (AR-Centre: p = 0.0007, AR-Home: p = 0.0052), SF-12v2 PCS (AR-Centre: p = 0.027, AR-Home: p = 0.036) were observed in both groups. Significant improvement in balance ability (BBS: p = 0.0438), and mental components (SF-12v2 MCS: p = 0.017) were found in AR-Centre group, while activities of daily living (BI: p = 0.0007) was found in AR-Home group. Contact rate was reduced by 30.75-72.30% within AR-All, 0.00-60.00% within AR-Centre, and 75.00-90.00% within AR-Home. CONCLUSION: The human-machine integrated mode was effective and efficient to reduce the human rehabilitation professionals' effort while fulfilling the training goals. It eased the scarcity of manpower and reduced the contact rate during the pandemics.

Pathogen Distribution, Drug Resistance Risk Factors, and Construction of Risk Prediction Model for Drug-Resistant Bacterial Infection in Hospitalized Patients at the Respiratory Department During the COVID-19 Pandemic.

Objective: To investigate the distribution and drug resistance of pathogens among hospitalized patients in the respiratory unit during the COVID-19 pandemic, analyze the risk factors of drug resistance, construct a risk prediction model. Methods: This study isolated 791 strains from 489 patients admitted to the Affiliated Hospital of Chengdu University, who were retrospectively enrolled between December 2019 and June 2021. The patients were divided into training and validation sets based on a random number table method (8:2). The baseline information, clinical characteristics, and culture results were collected using an electronic database and WHONET 5.6 software and compared between the two groups. A risk prediction model for drug-resistant bacteria was constructed using multi-factor logistic regression. Results: K. pneumoniae (24.78%), P. aeruginosa (17.19%), A. baumannii (10.37%), and E. coli (10.37%) were the most abundant bacterial isolates. 174 isolates of drug-resistant bacteria were collected, ie, Carbapenem-resistant organism-strains, ESBL-producing strains, methicillin-resistant S. aureus, multi-drug resistance constituting 38.51%, 50.57%, 6.32%, 4.60%, respectively. The nosocomial infection prediction model of drug-resistant bacteria was developed based on the combined use of antimicrobials, pharmacological immunosuppression, PCT>0.5 ng/mL, CKD stage 4-5, indwelling catheter, and age > 60 years. The AUC under the ROC curve of the training and validation sets were 0.768 (95% CI: 0.624-0.817) and 0.753 (95% CI: 0.657-0.785), respectively. Our model revealed an acceptable prediction demonstrated by a non-significant Hosmer-Lemeshow test (training set, p=0.54; validation set, p=0.88). Conclusion: K. pneumoniae, P. aeruginosa, A. baumannii, and E. coli were the most abundant bacterial isolates. Antimicrobial resistance among the common isolates was high for most routinely used antimicrobials and carbapenems. COVID-19 did not increase the drug resistance pressure of the main strains. The risk prediction model of drug-resistant bacterial infection is expected to improve the prevention and control of antibacterial-resistant bacterial infection in hospital settings.

miR-615 facilitates porcine epidemic diarrhea virus replication by targeting IRAK1 to inhibit type III interferon expression.

Porcine epidemic diarrhea virus (PEDV) in the Coronavirus family is a highly contagious enteric pathogen in the swine industry, which has evolved mechanisms to evade host innate immune responses. The PEDV-mediated inhibition of interferons (IFNs) has been linked to the nuclear factor-kappa B (NF-κB) pathway. MicroRNAs (miRNAs) are involved in virus-host interactions and IFN-I regulation. However, the mechanism by which the PEDV regulates IFN during PEDV infection has not yet been investigated in its natural target cells. We here report a novel mechanism of viral immune escape involving miR-615, which was screened from a high-throughput sequencing library of porcine intestinal epithelial cells (IECs) infected with PEDV. PEDV infection altered the profiles of miRNAs and the activities of several pathways involved in innate immunity. Overexpression of miR-615 increased PEDV replication, inhibited IFN expression, downregulated the NF-κB pathway, and blocked p65 nuclear translocation. In contrast, knockdown of miR-615 enhanced IFN expression, suppressed PEDV replication, and activated the NF-κB pathway. We further determined that IRAK1 is the target gene of miR-615 in IECs. Our findings show that miR-615 suppresses activation of the NF-κB pathway by suppressing the IRAK1 protein and reducing the generation of IFN-IIIs, which in turn facilitates PEDV infection in IECs. Moreover, miR-615 inhibited PEDV replication and NF-κB pathway activation in both IECs and MARC-145 cells. These findings support an important role for miR-615 in the innate immune regulation of PEDV infections and provide a novel perspective for developing new treatments.

Impactful publications of critical care medicine research in China: A bibliometric analysis

Background Although publications have been increasing rapidly, the research quality has yet to improve in the field of critical care medicine (CCM) in China. This study aimed at investigating the current status of and the influential factors for impactful publications in CCM research by Chinese authors. Methods Publications by authors with the affiliation of critical care medicine department or intensive care unit (CCM/ICU) in Chinese as well as American hospitals from 2001 to 2020 were retrieved from the Web of Science Core Collection (WoSCC) database for this bibliometric analysis. Moreover, statistical analyses to test factors affecting impactful publications by Chinese authors were performed. Results Of 13,487 articles retrieved by this search strategy, 6,622 were published by Chinese authors as first or corresponding authors. The annual publications by Chinese authors have been rapidly increasing from 2001 to 2020, and so did the citations to these articles. However, the proportion in the world of publications by Chinese authors was much less than that by American authors each year [M (IQR): 1.85 (9.592) vs. 27.77 (7.3), p < 0.001]. In addition, impactful articles were significantly less published by Chinese than by American authors, including articles either in journals with a high impact factor (p < 0.001) or in the top 10 journals in the field of CCM (5.4 vs 13.4%, p < 0.001), and articles with high citation frequency as well (p < 0.001). Moreover, the percentage of impactful publications by Chinese authors was likely associated with academic background and regions of the author's affiliations, funds support, public health events of COVID-19, and collaboration between authors. Conclusion Our results demonstrated that CCM research in China grew rapidly in the recent 20 years. However, the impactful publications remained limited, largely owing to the shortage of comprehensive research training, inactive collaboration, and underfunded CCM research.

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.)

Epidemiological features and dynamic changes in blood biochemical indices for COVID-19 patients in Hebi.

BACKGROUND: Millions of people have died of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and retrospective studies of the disease in local regions are necessary. AIM: To characterize the epidemiological features and dynamic changes in blood biochemical indices for SARS-CoV-2-infected patients in Hebi, a representative city with a large floating population in North China. METHODS: From January 25 to February 10, 2020, the clinical data of patients who tested positive for SARS-CoV-2 by quantitative real-time polymerase chain reaction in Hebi city (China) were evaluated at admission, and laboratory data for hematologic parameters, inflammatory indices, coagulation function indices, liver function indices, blood lipid indices, renal function indices, myocardial enzyme activities and five blood biochemical markers of immunity were evaluated at admission, upon hospitalization and before discharge. RESULTS: Sixteen confirmed COVID-19 patients developed pneumonia but were cured after adequate treatment. Fever and fatigue were the common symptoms. The most common laboratory abnormalities of patients at admission were leukopenia, eosinopenia, decreased percentage of eosinophils, elevated high sensitivity C-reactive protein and fibrinogen levels, hypoalbuminemia, mildly increased aspartate transferase activity and levels of bilirubin, and increased levels of ß2-microglobulin. Importantly, aggravated liver dysfunction was detected in most patients, which may be partially attributed to virus infection as well as medicinal treatment. CONCLUSION: This study provides several potential diagnostic markers and dynamic biochemical indices of disease progression to better prevent, diagnose and treat COVID-19 infection.

Reduced neutralization of SARS-CoV-2 B.1.617 variant by convalescent and vaccinated sera.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Spike protein that mediates coronavirus entry into host cells is a major target for COVID-19 vaccines and antibody therapeutics. However, multiple variants of SARS-CoV-2 have emerged, which may potentially compromise vaccine effectiveness. Using a pseudovirus-based assay, we evaluated SARS-CoV-2 cell entry mediated by the viral Spike B.1.617 and B.1.1.7 variants. We also compared the neutralization ability of monoclonal antibodies from convalescent sera and neutralizing antibodies (NAbs) elicited by CoronaVac (inactivated vaccine) and ZF2001 (RBD-subunit vaccine) against B.1.617 and B.1.1.7 variants. Our results showed that, compared to D614G and B.1.1.7 variants, B.1.617 shows enhanced viral entry and membrane fusion, as well as more resistant to antibody neutralization. These findings have important implications for understanding viral infectivity and for immunization policy against SARS-CoV-2 variants.

Prognostic value of neutrophil-to-lymphocyte ratio, lactate dehydrogenase, D-dimer, and computed tomography score in patients with coronavirus disease 2019.

BACKGROUND: This study aimed to explore the significance of neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), D-dimer, and CT score in evaluating the severity and prognosis of coronavirus disease 2019 (COVID-19). METHODS: Patients with laboratory-confirmed COVID-19 were retrospectively enrolled. The baseline data, laboratory findings, chest computed tomography (CT) results evaluated by CT score on admission, and clinical outcomes were collected and compared. Logistic regression was used to assess the independent relationship between the baseline level of the four indicators (NLR, LDH, D-dimer, and CT score) and the severity of COVID-19. RESULTS: Among the 432 patients, 125 (28.94%) and 307 (71.06%) were placed in the severe and non-severe groups, respectively. As per the multivariate logistic regression, high levels of NLR and LDH were independent predictors of severe COVID-19 (OR=2.163; 95% CI=1.162-4.026; p=0.015 for NLR>3.82; OR=2.298; 95% CI=1.327-3.979; p=0.003 for LDH>246 U/L). Combined NLR>3.82 and LDH>246 U/L increased the sensitivity of diagnosis in patients with severe disease (NLR>3.82 [50.40%] vs. combined diagnosis [72.80%]; p=0.0007; LDH>246 [59.2%] vs. combined diagnosis [72.80%]; p<0.0001). CONCLUSIONS: High levels of serum NLR and LDH have potential value in the early identification of patients with severe COVID-19. Moreover, the combination of LDH and NLR can improve the sensitivity of diagnosis.

Emotional Creativity Improves Posttraumatic Growth and Mental Health During the COVID-19 Pandemic.

Emotional creativity refers to a set of cognitive abilities and personality traits related to the originality of emotional experience and expression. Previous studies have found that emotional creativity can positively predict posttraumatic growth and mental health. The outbreak of coronavirus disease 2019 (COVID-19) has posed great challenges to people's daily lives and their mental health status. Therefore, this study aims to address the following two questions: whether emotional creativity can improve posttraumatic growth and mental health during the COVID-19 pandemic and how it works. To do this, a multiple mediation model has been proposed, which supposes that emotional creativity is associated with posttraumatic growth and mental health through perceived social support and regulatory emotional self-efficacy. The study involved 423 participants from multiple regions with different COVID-19 involvement levels. Participants were asked to complete a questionnaire with six parts, which included Emotional Creativity Inventory (ECI), Regulatory Emotional Self-Efficacy Scale (RES), Stress-Related Growth Scale-Short Form (SRGS-SF), Multidimensional Scale of Perceived Social Support scale (MSPSS), Brief Symptom Inventory-18 scale (BSI-18), and COVID-19-related life events questionnaire. Path analysis used to examine the mediation model indicated that under the control of COVID-19-related life events and age, perceived social support mediated a positive association between emotional creativity and posttraumatic growth as well as a negative association between emotional creativity and all mental health problems, including somatization, depression, and anxiety. Regulatory emotional self-efficacy mediates the association between emotional creativity and posttraumatic growth, emotional creativity and anxiety, and emotional creativity and depression. The results suggest that emotional creativity plays an important role in coping with stressful events related to COVID-19. Furthermore, these results might provide a better understanding of the possible paths through which emotional creativity is related to psychological outcomes, such as mental health and posttraumatic growth.

Serum IP-10 and IL-7 levels are associated with disease severity of coronavirus disease 2019.

We quantified the serum levels of 34 cytokines/chemokines in 30 patients with SARS-CoV-2 infection. Elevated levels of IP-10 and IL-7 were detected in the acute and convalescent stages of the infection and were highly associated with disease severity.

Pleural effusion as an indicator for the poor prognosis of COVID-19 patients.

BACKGROUND: Coronavirus Disease 19 (COVID-19) is a global health concern that has become a pandemic over the past few months. This study aims at understanding the clinical manifestations of COVID-19 patients with pleural effusion. METHODS: COVID-19 patients were retrospectively enrolled from the Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Pharyngeal swabs from patients were tested using real-time polymerase chain reaction. Patients with COVID-19 were divided into two groups based on their computed tomography (CT) scans for the presence of pleural effusion at admission. We compared the clinical features, laboratory findings, scans and clinical outcomes between the two groups. RESULTS: Pleural effusion was observed in 9.19% of the patients. Patients with pleural effusion were more likely to be severe or critical cases. Moreover, patients with pleural effusion were associated with increased mortality. Of the 799 discharged patients, patients with pleural effusion had longer hospital stays and duration of viral shedding since the onset of symptoms as compared with that for patients without pleural effusion. After discharge, 217 patients visited for a follow-up CT re-examination at the Union Hospital. The CT scans showed that patients with pleural effusion required a longer time to resolve the lung inflammation after the onset of COVID-19 as compared with the time required by patients without pleural effusion. CONCLUSION: This population of patients requires special attention and pleural effusion may be an indicator of poor prognosis in COVID-19 patients.

Co-infection of SARS-COV-2 and Influenza A Virus: A Case Series and Fast Review.

Coronavirus disease 2019 (COVID-19) occurs in the influenza season and has become a global pandemic. The present study aimed to examine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) co-infection with influenza A virus (IAV) in an attempt to provide clues for the antiviral interventions of co-infected patients. We described two patients who were co-infected with SARS-CoV-2 and IAV treated at Wuhan Union Hospital, China. In addition, we performed a review in PubMed, Web of Science and CNKI (from January 1 up to November 1, 2020) with combinations of the following key words: "COVID-19, SARS-COV-2, influenza A and co-infection". A total of 28 co-infected patients were enrolled in the analysis. Of the 28 patients, the median age was 54.5 years (IQR, 34.25-67.5) and 14 cases (50.0%) were classified as severe types. The most common symptoms were fever (85.71%), cough (82.14%) and dyspnea (60.71%). Sixteen patients had lymphocytopenia on admission and 23 patients exhibited abnormal radiological changes. The median time from symptom onset to hospital admission was 4 days (IQR, 3-6), and the median time of hospital stay was 14 days (IQR, 8.5-16.75). In conclusion, patients with SARS-COV-2 and IAV co-infection were similar to those infected with SARS-COV-2 alone in symptoms and radiological images. SARS-COV-2 co-infection with IAV could lead to more severe clinical condition but did not experience longer hospital stay compared with patients infected with SARS-COV-2 alone.

Lasting antibody and T cell responses to SARS-CoV-2 in COVID-19 patients three months after infection.

The dynamics, duration, and nature of immunity produced during SARS-CoV-2 infection are still unclear. Here, we longitudinally measured virus-neutralising antibody, specific antibodies against the spike (S) protein, receptor-binding domain (RBD), and the nucleoprotein (N) of SARS-CoV-2, as well as T cell responses, in 25 SARS-CoV-2-infected patients up to 121 days post-symptom onset (PSO). All patients seroconvert for IgG against N, S, or RBD, as well as IgM against RBD, and produce neutralising antibodies (NAb) by 14 days PSO, with the peak levels attained by 15-30 days PSO. Anti-SARS-CoV-2 IgG and NAb remain detectable and relatively stable 3-4 months PSO, whereas IgM antibody rapidly decay. Approximately 65% of patients have detectable SARS-CoV-2-specific CD4+ or CD8+ T cell responses 3-4 months PSO. Our results thus provide critical evidence that IgG, NAb, and T cell responses persist in the majority of patients for at least 3-4 months after infection.

Risk factors for mortality of coronavirus disease-2019 (COVID-19) patients in two centers of Hubei province, China: A retrospective analysis.

PURPOSE: Since the outbreak in late December 2019 in Wuhan, China, coronavirus disease-2019 (COVID-19) has become a global pandemic. We analyzed and compared the clinical, laboratory, and radiological characteristics between survivors and non-survivors and identify risk factors for mortality. METHODS: Clinical and laboratory variables, radiological features, treatment approach, and complications were retrospectively collected in two centers of Hubei province, China. Cox regression analysis was conducted to identify the risk factors for mortality. RESULTS: A total of 432 patients were enrolled, and the median patient age was 54 years. The overall mortality rate was 5.09% (22/432). As compared with the survivor group (n = 410), those in the non-survivor group (n = 22) were older, and they had a higher frequency of comorbidities and were more prone to suffer from dyspnea. Several abnormal laboratory variables indicated that acute cardiac injury, hepatic damage, and acute renal insufficiency were detected in the non-survivor group. Non-surviving patients also had a high computed tomography (CT) score and higher rate of consolidation. The most common complication causing death was acute respiratory distress syndrome (ARDS) (18/22, 81.8%). Multivariate Cox regression analysis revealed that hemoglobin (Hb) <90 g/L (hazard ratio, 10.776; 95% confidence interval, 3.075-37.766; p<0.0001), creatine kinase (CK-MB) >8 U/L (9.155; 2.424-34.584; p = 0.001), lactate dehydrogenase (LDH) >245 U/L (5.963; 2.029-17.529; p = 0.001), procalcitonin (PCT) >0.5 ng/ml (7.080; 1.671-29.992; p = 0.008), and CT score >10 (39.503; 12.430-125.539; p<0.0001) were independent risk factors for the mortality of COVID-19. CONCLUSIONS: Low Hb, high LDH, PCT, and CT score on admission were the predictors for mortality and could assist clinicians in early identification of poor prognosis among COVID-19 patients.

RLIM: A Recursive and Latent Infection Model for COVID-19 Prediction and Turning Point in United States (preprint)

Initially found at Hubei, Wuhan and identified as a novel virus of coronavirus family by WHO, COVID-19 has spread worldwide with an exponentially speed, causing millions of death and public fear. Currently, COVID19 has brought a secondary wave within U.S., India, Brazil and other parts of the world. However, its transmission, incubation, and recovery processes are still unclear from the medical, mathematical and pharmaceutical aspects. Classical Suspect-Infection-Recovery model has limitations to describe the dynamic behavior of COVID-19. Hence, it becomes necessary to introduce a recursive, latent model to predict the number of future COVID-19 infected cases in U.S. In this article, a dynamic model called RLIM based on classical SEIR model is proposed to predict the number of COVID-19 infections with a dynamic secondary infection rate ω in assumption. An intermediate state called SI is introduced between recovery and infection statues to record the number of secondary infected cases from a latent period of recovery. Compared with other models, RLIM fits historical recovery cases and utilizes them to predict future infections. Because RLIM utilizes multiple information sources, and provides error back propagation schematics, it is reasonable to assert that its predictions are more accurate and persuasive. Projections of four U.S. COVID19 states show that with the secondary infectious rate ω varies from 0.01 to 0.3 within a latent period of 14 days chosen, RLIM can predict the newly infected number from January 15 to February 15, 2021 with AFER lower to 14%. It also successfully estimates the turning point of New Yorks infections in January 2021, based on current data records.

Interferon-α2b Treatment for COVID-19.

The global pandemic of COVID-19 cases caused by infection with SARS-CoV-2 is ongoing, with no approved antiviral intervention. We describe here the effects of treatment with interferon (IFN)-α2b in a cohort of confirmed COVID-19 cases in Wuhan, China. In this uncontrolled, exploratory study, 77 adults hospitalized with confirmed COVID-19 were treated with either nebulized IFN-α2b (5 mU b.i.d.), arbidol (200 mg t.i.d.) or a combination of IFN-α2b plus arbidol. Serial SARS-CoV-2 testing along with hematological measurements, including cell counts, blood biochemistry and serum cytokine levels, and temperature and blood oxygen saturation levels, were recorded for each patient during their hospital stay. Treatment with IFN-α2b with or without arbidol significantly reduced the duration of detectable virus in the upper respiratory tract and in parallel reduced duration of elevated blood levels for the inflammatory markers IL-6 and CRP. These findings suggest that IFN-α2b should be further investigated as a therapy in COVID-19 cases.

Immunogenicity and Safety of a SARS-CoV-2 Inactivated Vaccine in Healthy Adults Aged 18-59 years: Report of the Randomized, Double-blind, and Placebo-controlled Phase 2 Clinical Trial (preprint)

BACKGROUND The top priority for the control of COVID-19 pandemic currently is the development of a vaccine. A phase 2 trial conducted to further evaluate the immunogenicity and safety of a SARS-CoV-2 inactivated vaccine (CoronaVac). METHODS We conducted a randomized, double-blind, placebo-controlled trial to evaluate the optimal dose, immunogenicity and safety of the CoronaVac. A total of 600 healthy adults aged 18-59 years were randomly assigned to receive 2 injections of the trial vaccine at a dose of 3 g/0.5 mL or 6 g /0.5mL, or placebo on Day 0,14 schedule or Day 0,28 schedule. For safety evaluation, solicited and unsolicited adverse events were collected after each vaccination within 7 days and 28 days, respectively. Blood samples were taken for antibody assay. RESULTS CoronaVac was well tolerated, and no dose-related safety concerns were observed. Most of the adverse reactions fell in the solicited category and were mild in severity. Pain at injection site was the most frequently reported symptoms. No Grade 3 adverse reaction or vaccine related SAEs were reported. CoronaVac showed good immunogenicity with the lower 3 g dose eliciting 92.4% seroconversion under Day 0,14 schedule and 97.4% under Day 0,28 schedule. 28 days after two-dose vaccination, the Nab levels of individual schedules range from 23.8 to 65.4 among different dosage and vaccination schedules. CONCLUSIONS Favorable safety and immunogenicity of CoronaVac was demonstrated on both schedules and both dosages, which support the conduction of phase 3 trial with optimum schedule/dosage per different scenarios.