[Cross-sectional study on the use of masks among occupational groups with high-risk positions for overseas import and pollution transmission].

Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.

Symptom Based Models of COVID-19 Infection Using AI

Coronavirus Disease 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) has spread around the world in a global pandemic [1-4]. Early and daily detection of suspected COVID-19 patients is the most important approach not only for tracing close contacts to prevent further spread [5], but also providing crucial information for healthcare providers and officials to make resource allocation and policy decisions [6]. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Messenger RNA Nanovaccine in Cancer Immunotherapy

During the past 2 years, messenger RNA (mRNA) nanovaccine has shown its remarkable antiviral efficacy, rapid manufacture, and good safety profile for preventing coronavirus infection. Meanwhile, intracellular delivery of mRNA-based cancer vaccine starts to show great potential to elicit antitumor immunity. mRNA encoding tumor antigens, delivery vehicles, and immune adjuvants are the key components of mRNA cancer vaccine. To achieve robust antitumor efficacy, mRNA encoding tumor antigens need to be efficiently delivered and translated in dendritic cells with concurrent innate immune stimulation to promote antigen presentation. Compared with other types of tumor vaccines, mRNA nanovaccine is featured by efficient antigen expression, high potential for rapid development, low-cost manufacture, and safe administration. In this chapter, we mainly focus on the mRNA synthesis, mRNA modification, delivery vectors with immune-stimulating features, and tumor antigen selection and discuss the future direction of mRNA nanovaccine in cancer immunotherapy. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Potential targets and traditional Chinese medicine treatment strategy of cough after SARS-CoV-2 infection.

The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) Omicron variants BA.5.2 and BF.7 have become the main epidemic strains in China since the quarantine policy was lifted in 7th December 2022. Cough is one of the main symptoms induced by SARS-CoV-2 infection. SARS-CoV-2 infection-associated cough injuries the lung and upper respiratory tract, while the infected people cough out virus and liquid which forms virus-containing aerosols, a medium for quickly spreading. Furthermore, cough is one of primary sequelae of discharged patients in corona virus disease 2019 (COVID-19). By now, there are no efficacious drugs for treatment of upper respiratory tract infection associated cough induced by omicron. Traditional Chinese medicine (TCM) has a long history on treating cough. By reviewing the mechanisms of the occurrence of cough after SARS-CoV-2 infection, potential therapeutic targets and cough suppressant herbs with significant efficacy in clinical and basic research, we provide a reference for the treatment of cough after SARS-Cov-2 infection and a basis for the majority of infected patients to select appropriate herbs for cough relief under guidance of physicians.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

Pericytes may facilitate SARS-CoV-2 entry into the nervous system

Objective: Although the neurological and olfactory symptoms of coronavirus disease 2019 have been identified, the neurotropic properties of the causative virus, severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2), remain unknown. We sought to identify the susceptible cell types and potential routes of SARS-CoV-2 entry into the central nervous system, olfactory system, and respiratory system. Method(s): We collected single-cell RNA data from normal brain and nasal epithelium specimens, along with bronchial, tracheal, and lung specimens in public datasets. The susceptible cell types that express SARS-CoV-2 entry genes were identified using single-cell RNA sequencing and the expression of the key genes at protein levels was verified by immunohistochemistry. We compared the coexpression patterns of the entry receptor angiotensin-converting enzyme 2 (ACE2) and the spike protein priming enzyme transmembrane serine protease (TMPRSS)/cathepsin L among the specimens. Result(s): The SARS-CoV-2 entry receptor ACE2 and the spike protein priming enzyme TMPRSS/cathepsin L were coexpressed by pericytes in brain tissue;this coexpression was confirmed by immunohistochemistry. In the nasal epithelium, ciliated cells and sustentacular cells exhibited strong coexpression of ACE2 and TMPRSS. Neurons and glia in the brain and nasal epithelium did not exhibit coexpression of ACE2 and TMPRSS. However, coexpression was present in ciliated cells, vascular smooth muscle cells, and fibroblasts in tracheal tissue;ciliated cells and goblet cells in bronchial tissue;and alveolar epithelium type 1 cells, AT2 cells, and ciliated cells in lung tissue. Conclusion(s): Neurological symptoms in patients with coronavirus disease 2019 could be associated with SARS-CoV-2 invasion across the blood-brain barrier via pericytes. Additionally, SARS-CoV-2-induced olfactory disorders could be the result of localized cell damage in the nasal epithelium.Copyright © Wolters Kluwer Health, Inc. All rights reserved.

PQSCT: Pseudo-Siamese BERT for Concept Tagging With Both Questions and Solutions

The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which extracts knowledge index structures and knowledge representations for exercises. Unfortunately, to the best of our knowledge, existing tagging approaches based on exercise content either ignore multiple components of exercises, or ignore that exercises may contain multiple concepts. To this end, in this paper, we present a study of concept tagging. First, we propose an improved pre-trained BERT for concept tagging with both questions and solutions (QSCT). Specifically, we design a question-solution prediction task and apply the BERT encoder to combine questions and solutions, ultimately obtaining the final exercise representation through feature augmentation. Then, to further explore the relationship between questions and solutions, we extend the QSCT to a pseudo-siamese BERT for concept tagging with both questions and solutions (PQSCT). We optimize the feature fusion strategy, which integrates five different vector features from local and global into the final exercise representation. Finally, we conduct extensive experiments on real-world datasets, which clearly demonstrate the effectiveness of our proposed models for concept tagging. IEEE

CCTwins: A Weakly-Supervised Transformer-based Crowd Counting Method with Adaptive Scene Consistency Attention

Recently, crowd counting has attracted significant attention, particularly in the context of the COVID-19 pandemic, due to its ability to automatically provide accurate crowd numbers in images. To address the challenges of location-level labeling, several transformer-based crowd counting methods have been proposed with only count-level supervision. However, these methods directly use the transformer as an encoder without considering the uneven crowd distribution. To address this issue, we propose CCTwins, a novel transformer-based crowd counting method with only count-level supervision. Specifically, we introduce an adaptive scene consistency attention mechanism to enhance the transformer-based model Twins-SVT-L for feature extraction in crowded scenes. Additionally, we design a multi-level weakly-supervised loss function that generates estimated crowd numbers in a coarse-to-fine manner, making it more appropriate for weakly-supervised settings. Moreover, intermediate features supervised by count-level labels are utilized to fuse multi-scale features. Experimental results on four public datasets demonstrate that our proposed method outperforms the state-of-the-art weakly-supervised methods, achieving up to a 16.6% improvement in MAE and up to a 13.8% improvement in RMSE across all evaluation settings. Moreover, the proposed CCTwins obtains competitive counting performance, even when compared to the state-of-the-art fully-supervised methods. IEEE

Wearing Masks Implies Refuting Trump?: Towards Target-specific User Stance Prediction across Events in COVID-19 and US Election 2020

People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such connections, which we call connected behavior, gives researchers a unique opportunity to predict how one would behave for a future event given their past behaviors. In this work, we propose a framework to conduct connected behavior analysis. Neural stance detection models are trained on Twitter data collected on three seemingly independent topics, i.e., wearing a mask, racial equality, and Trump, to detect people's stance, which we consider as their online behavior in each topic-related event. Our results reveal a strong connection between the stances toward the three topical events and demonstrate the power of past behaviors in predicting one's future behavior. © 2023 ACM.

Clinical characteristics of 654 patients with COVID-19 in Dongxihu Shelter Hospital in Wuhan

Objective To analyze the clinical features of patients with coronavirus disease 2019COVID-19in Wuhan, and we provide reference for further prevention and control of the disease. Methods We collected the clinical data of patients with COVID-19 in Dongxihu Shelter Hospital of Wuhan from February 7 to March 6, 2020. The main symptoms, blood test results, lung CT results, and nucleic acid negative conversion were analyzed. Results A total of 654 patients were included, 17526.76%were mild, and 47973.24%were general. There were 344 males (52.60%), and 310 females (47.40%). The patients were with a mean age of49.36+/-10.30years, and 97 patients (14.83%) with a history of hypertension, 51 patients (7.80%) had a history of diabetes. The main clinical symptoms were fever with 547(83.64%) patients, 186 cases (28.44%) had chills, 15 cases (2.29%) had shiver, 342(52.29%) had fatigue symptoms, 413(63.15%) had cough, 137(20.95%) had chest tightness, and 109(16.67%) had diarrhea during the course of the disease. Blood routine tests of 395 patients, the white blood cell count (WBC) was (4.12+/-1.46)x109/L. The total white blood cell count was normal in 378 cases(95.70%), increased in 7(1.77%), and decreased in 10(2.53%). The lymphocyte percentage was (23.10+/-10.02)%, lymphocyte1.06+/-0.37x109/L. The percentage and count of lymphocyte were low. All the 654 cases were examined by CT, 175 cases (26.76%) showed normal lung CT, 422 cases (64.52%) showed patchy or segmental ground-glass opacity, and 57 cases (8.72%) showed multilobar consolidation, ground-glass shadow coexisted with consolidation or streak shadow. The interval between positive nucleic acid test before admission and negative test after admission was as short as 5 days and as long as 24 days, the average was (12.35+/-3.73) days. Conclusion Fever, coughing, and fatigue are the main symptoms in patients with COVID-19. The typical lung CT findings can be used as the basis for clinical diagnosis and disease evaluation. Patients with mild and common type had better prognosis.Copyright © 2021 Editorial Office of Chinese Journal of Schistosomiasis Control. All rights reserved.

Epidemiological characteristics of four times of community transmission of COVID-19 in Hebei

Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81:1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers' markets, medical workers and other key areas and groups, and ensure early detection and timely response.Copyright © 2022 China Tropical Medicine. All rights reserved.

Heterogeneous influence of individuals' behavior on mask efficacy in gathering environments

Wearing masks is an easy way to operate and popular measure for preventing epidemics. Although masks can slow down the spread of viruses, their efficacy in gathering environments involving heterogeneous person-to-person contacts remains unknown. Therefore, we aim to investigate the epidemic prevention effect of masks in different real-life gathering environments. This study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering environments. The transmission of COVID-19 is simulated using the Monte Carlo simulation method. The heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general society. Furthermore, the heterogeneity of gathering environments causes the epidemic prevention effect of masks to differ. Wearing masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools, high schools, and hospitals. However, the use of masks alone in primary schools and hospitals cannot control outbreaks. In high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse, masks can meet the need for prevention. Given the heterogeneity of individual behavior, if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing, the epidemic prevention effect of masks can be improved. Finally, asymptomatic infection has varying effects on the prevention effect of masks in different environments. The effect can be weakened or eliminated by increasing the usage rate of masks in high schools and workplaces. However, the effect on primary schools and hospitals cannot be weakened. This study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention. © 2022, Higher Education Press.

QUASAR Induction Study 1 Cumulative Response to Guselkumab in Patients With Moderately to Severely Active Ulcerative Colitis

Introduction: Guselkumab (GUS), an IL-23p19 antagonist, had greater efficacy than placebo (PBO) in achieving clinical response and clinical remission atWeek (Wk) 12 in the randomized, controlled Phase 2b QUASAR Induction Study 1 (NCT04033445) in patients with moderately to severely active ulcerative colitis (UC).1 Patients who were not in clinical response at Wk 12 received GUS treatment through Wk 24. Here, we report GUS cumulative efficacy and safety results for Induction Study 1. Method(s): Eligible patients had moderately to severely active UC (modified Mayo score of 5 to 9 with a Mayo endoscopy subscore >=2) at baseline. Patients were randomized 1:1:1 to IV GUS 200mg, 400mg, or PBO at Wks 0, 4, and 8. Patients who were not in clinical response to IV induction at Wk 12 received GUS treatment (PBO IV->GUS 200mg IV;GUS 200mg IV->GUS 200mg SC;GUS 400mg IV->GUS 200mg SC) at Wks 12, 16, and 20 and were evaluated at Wk 24 (Figure). Matching IV or SC PBO was administered to maintain the blind. Result(s): Three hundred thirteen patients were randomized and treated at baseline. Demographic and disease characteristics at baseline were similar among the treatment groups, and approximately 50% had a prior inadequate response or intolerance to advanced UC therapy. AtWk 12, clinical response was achieved by 61.4% (62/101) and 60.7% (65/107) of patients randomized to GUS 200mg and GUS 400mg IV vs 27.6 % (29/105) of patients randomized to PBO IV (both p< 0.001). Of the patients in the GUS groups who were not in clinical response at Wk 12, 54.3% (19/35) in the GUS 200mg IV->200mg SC group and 50.0% (19/38) in the GUS 400mg IV->200mg SC group achieved clinical response at Wk 24. Clinical response atWk 12 or 24 was achieved by 80.2% of patients who were randomized to GUS 200mg IV and 78.5% of patients who were randomized to GUS 400mg IV. For patients who received PBO IV->GUS 200mg IV, clinical response at Wk 24 (65.2%) was similar toWk 12 clinical response following GUS 200mg IV induction (61.4%). The most frequent adverse events among all GUS-treated pts (n=274) were anemia (7.7%), headache (5.1%), worsening UC (4.4%), COVID-19 (3.6%), arthralgia (2.9%) and abdominal pain (2.6%) which are consistent with Wk 12 results. Conclusion(s): Overall, approximately 80% of patients randomized to receive GUS achieved clinical response at Wk 12 or 24. Continued treatment with SC GUS allowed 50-54.3% of IV GUS Wk 12 clinical nonresponders to achieve clinical response at Wk 24. No new safety concerns for GUS were identified. (Figure Presented).

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance. © Wolters Kluwer Health, Inc. All rights reserved.

An imported case of ovale malaria in Xinjiang during the epidemic period of COVID-19.

On December 13, 2020, Yutian County People's hospital reported one imported malaria case in Hotan, Xinjiang. The patient had worked and lived in Yaounde, Cameroon, from January to September 2020. He was infected with malaria twice in March and May 2020. Antimalarial treatment was administrated by the team doctor for 2-3 days in each treatment. The treatment was stopped after the symptoms improved. The patient returned to China on September 16 and was hospitalized on December 13 due to a high fever of 39! and upper respiratory symptoms. Multiple detections of COVID-19 nucleic acid showed negative results. Peripheral blood from the patient was taken for Plasmodium rapid diagnostic test (RDT), which showed a positive result suggesting non Plasmodium falciparum infection. Ring stage P. ovale was found in the blood smear. Nested PCR showed positive for P. ovale. A diagnosis of imported ovale malaria was made. The patient was administrated with 4 dihydroartemisinin piperaquine tablets and 3 primaquine phosphate tablets daily. The malaria parasite test became negative after 8 days of treatment. The patient was followed up for 3 months after discharge and had no symptoms of chills or fever.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.

Multi-scale Mechanisms of Maxing Shigantang in Treating Pneumonia Based on Transcriptomic Data.

Objective: Pneumonia is an infectious inflammation of the alveoli,distal airway,and interstitium caused by bacterial,viral,and other pathogens. Maxing Shigantang,originated from Treatise On Cold Damage Diseases,is a classic prescription for treating pneumonia,with significant clinical efficacy. However,its treatment mechanism is still elusive. Method(s): In that paper,the transcriptome-based multi-scale network pharmacology was used to reveal the overall pharmacological mechanism of Maxing Shigantang in treating pneumonia from six scales of tissue,cell,pathological process,biological process,signaling pathway, and target. Result(s):At the tissue level,Maxing Shigantang mainly acted on the focal tissue of pneumonia-lung and the main inflammatory immune tissues-blood and spleen. Analysis of cell,pathological process and biological process suggested that Maxing Shigantang could treat pneumonia by reversing inflammatory and immune functions and improving cardiopulmonary and vascular injury caused by pneumonia. Analysis of signaling pathway and target showed that Maxing Shigantang regulated inflammatory immune response pathways such as "coronavirus disease-COVID-19" and "Toll-like receptor signaling pathway",and related targets such as "MAPKAPK3" and "NRG1". Conclusion(s):This paper,from molecular to tissue levels,indicated Maxing Shigantang treated pneumonia mainly by regulating inflammatory immune response and improving cardiopulmonary and vascular injury.Copyright © 2023, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

Pharmacokinetics Informs Remdesivir Dosing for Patients with Severe Renal Impairment

Background: Despite renal impairment (RI) being a risk factor for severe COVID-19, there are no approved antiviral treatment options for patients with severely impaired kidney function (eGFR less than 30 mL/min/1.73 m2 or kidney failure) in the US. At the time remdesivir (RDV) was initially approved for the treatment of COVID-19, the impact of renal impairment (RI) on pharmacokinetics (PK) of RDV, its metabolites, and the excipient, sulfobutylether beta-cyclodextrin sodium (SBECD), was not known. Method(s): Here, we report the PK data supporting dosing of RDV in COVID-19 patients with severely impaired kidney function. PK samples for RDV and metabolites (GS-704277, GS-441524) were collected in the Phase 3 REDPINE study in hospitalized COVID-19 patients with severely impaired kidney function. Participants in this double-blind study were randomized 2:1 to intravenous (IV) remdesivir (200 mg on Day 1, then 100 mg daily up to Day 5) or IV saline as placebo-to-match. SBECD PK was analyzed in a phase 1 study in non-COVID-19 participants with normal kidney function, mild and moderate RI who received 100 mg dose of remdesivir (containing 3000 mg SBECD). The population PK analysis included observations from healthy and COVID-19 patients with full range of renal function across all adult studies. Result(s): Geometric mean exposures (AUCtau) observed in REDPINE Study as compared to PINETREE Study increased up to 553% for the GS-441524 metabolite (dependent on renal elimination) and to a lesser degree GS-704277 (294%, minor renal elimination) and RDV (78.9%;an increase explained by factors other than renal function, namely, hospitalization and body weight) (Table 1). The increased PK exposures were not associated with new safety signals in this study (n=163 remdesivir, n=80 placebo). Population PK analysis identified baseline eGFR as a significant covariate for GS-704277 and GS-441524 clearance, but not for RDV itself. SBECD PK was characterized by short half-life (t1/2) (1.6 hours in normal renal function to 3.8 hours in moderate RI) and fast plasma clearance (7.9 L/h in normal renal function). Analysis of SBECD in severe RI (REDPINE) is ongoing, but accumulation is not expected based on its observed short plasma t1/2. Conclusion(s): Given the observed PK and the absence of any new safety signals associated with increased metabolite levels in patients with severely impaired kidney function, no dose adjustment is recommended for RDV in COVID-19 patients with eGFR < 30 mL/min/1.73 m2, regardless of the need for dialysis.

COVID-19 and preventive strategy

In December 2019, an unprecedented outbreak of the novel coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) began to spread internationally, now impacting more than 293,750,692 patients with 5,454,131 deaths globally as of January 5, 2022. COVID-19 is highly pathogenic and contagious which has caused a large-scale epidemic impacting more deaths than the severe acute respiratory syndrome (SARS) epidemic in 2002-2003 or the Middle East respiratory syndrome (MERS) epidemic in 2012-2013. Although COVID-19 symptoms are mild in most people, in those with pre-existing comorbidities there is an increased risk of progression to severe disease and death. In an attempt to mitigate this pandemic, urgent public health measures including quarantining exposed individuals and social distancing have been implemented in most states, while some states have even started the process of re-opening after considering both the economic and public health consequences of social distancing measures. While prevention is crucial, both novel agents and medications already in use with other indications are being investigated in clinical trials for patients with COVID-19. The collaboration between healthcare providers, health systems, patients, private sectors, and local and national governments is needed to protect both healthcare providers and patients to ultimately overcome this pandemic. The purpose of this review is to summarize the peer-reviewed and preprint literature on the epidemiology, transmission, clinical presentation, and available therapies as well as to propose a preventive strategy to overcome the present global pandemic.

GeoInfographic design of the multi-spatiality of borders: A case study of epidemic prevention and control in Ruili, China

We live in a world of borders, which influence our perception and movement. Traditional mapping techniques show limitations as borders have become shifting and complex, and borders' multi-scale and multi-spatial properties have been strengthened significantly. To fill the knowledge gap, we explored the multi-spatiality of borders and provided approaches for border symbol design and visualization by taking the coronavirus-hit border city, Ruili, China, as an example. This work could shed light on multi-spatial geographic visualization and policy-making.

Guest Editorial Introduction to the Special Issue on Intelligent Transportation Systems in Epidemic Areas

The COVID-19 pandemic has posed significant challenges to transportation systems in various aspects, such as transferring patients and medical resources, enforcing physical distancing in public transportation, and controlling virus transmission through transportation networks. To address these challenges, a variety of artificial intelligence technologies, such as autonomous driving, big data analytics, intelligent vehicle routing and scheduling, and intelligent traffic control, have been employed in the design of intelligent transportation systems. This Special Issue provides a forum for researchers and practitioners to present the most recent advances in presenting and applying intelligent technologies to promote transportation systems in large-scale epidemics.