Vaccination increased host antiviral gene expression and reduced COVID-19 severity during the Omicron variant outbreak in Fuyang City, China.

BACKGROUND: The differences in host antiviral gene expression and disease severity between vaccinated and non-vaccinated coronavirus disease 2019 (COVID-19) patients are not well characterized. We sought to compare the clinical characteristics and host antiviral gene expression patterns of vaccinated and non-vaccinated cohorts at the Second People's Hospital of Fuyang City. METHODS: In this case-control study, we retrospectively analyzed 113 vaccinated patients with a COVID-19 Omicron variant infection, 46 non-vaccinated COVID-19 patients, and 24 healthy subjects (no history of COVID-19) recruited from the Second People's Hospital of Fuyang City. Blood samples were collected from each study participant for RNA extraction and PCR. We compared host antiviral gene expression profiles between healthy controls and COVID-19 patients who were either vaccinated or non-vaccinated at the time of infection. RESULTS: In the vaccinated group, most patients were asymptomatic, with only 42.9 % of patients developing fever. Notably, no patients had extrapulmonary organ damage. In contrast, 21.4 % of patients in the non-vaccinated group developed severe/critical (SC) disease and 78.6 % had mild/moderate (MM) disease, with fever occurring in 74.2 % patients. We found that Omicron infection in COVID-19 vaccinated patients was associated with significantly increased expression of several important host antiviral genes including IL12B, IL13, CXCL11, CXCL9, IFNA2, IFNA1, IFNγ, and TNFα. CONCLUSION: Vaccinated patients infected with the Omicron variant were mostly asymptomatic. In contrast, non-vaccinated patients frequently developed SC or MM disease. Older patients with SC COVID-19 also had a higher occurrence of mild liver dysfunction. Omicron infection in COVID-19 vaccinated patients was associated with the activation of key host antiviral genes and thus may play a role in reducing disease severity.

Functionalized protein microparticles targeting hACE2 as a novel preventive strategy for SARS-CoV-2 infection.

The coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), resulting in a serious burden on public health and social economy worldwide. SARS-CoV-2 infection is mainly initialized in the nasopharyngeal cavity through the binding of viral spike (S) protein to human angiotensin-converting enzyme 2 (hACE2) receptors which are widely expressed in many human cells. Thus, blockade of the interaction between viral S protein and hACE2 receptor in the primary entry site is a promising prevention strategy for the management of COVID-19. Here we showed protein microparticles (PMPs) decorated with hACE2 could bind and neutralize SARS-CoV-2 S protein-expressing pseudovirus (PSV) and protect host cells from infection in vitro. In the hACE2 transgenic mouse model, administration of intranasal spray with hACE2-decorated PMPs markedly decreased the viral load of SARS-CoV-2 in the lungs though the inflammation was not attenuated significantly. Our results provided evidence for developing functionalized PMPs as a potential strategy for preventing emerging air-borne infectious pathogens, such as SARS-CoV-2 infection.

Peginterferon lambda for the treatment of hospitalized patients with mild COVID-19: A pilot phase 2 randomized placebo-controlled trial

Background This study aimed to investigate the efficacy and safety of subcutaneous injection of peginterferon lambda in patients hospitalized with COVID-19. Methods In this study (NCT04343976), patients admitted to hospital with COVID-19 confirmed by RT-PCR from nasopharyngeal swab were randomly assigned within 48 h to receive peginterferon lambda or placebo in a 1:1 ratio. Participants were subcutaneously injected with a peginterferon lambda or saline placebo at baseline and day 7 and were followed up until day 14. Results We enrolled 14 participants;6 participants (85.7%) in the peginterferon lambda group and 1 participant (14.3%) in the placebo group were treated with remdesivir prior to enrollment. Fifty percent of participants were SARS-CoV-2 RNA negative at baseline although they tested SARS-CoV-2 RNA positive within 48 h of randomization. Among participants who were SARS-CoV-2 positive at baseline, 2 out of 5 participants (40%) in the peginterferon lambda group became negative at day 14, while 0 out of 2 participants (0%) in the placebo group achieved negativity for SARS-CoV-2 by day 14 (p > 0.05). The median change in viral load (log copies per ml) was +1.72 (IQR −2.78 to 3.19) in the placebo group and −2.22 (IQR −3.24 to 0.55) in the peginterferon lambda group at day 14 (p = 0.24). Symptomatic changes did not differ between the two groups. Peginterferon lambda was well tolerated with a few treatment-related adverse effects. Conclusion Peginterferon lambda appears to accelerate SARS-CoV-2 viral load decline and improve plasma disease progression markers in hospitalized patients with COVID-19.

Peginterferon lambda for the treatment of hospitalized patients with mild COVID-19: A pilot phase 2 randomized placebo-controlled trial.

Background: This study aimed to investigate the efficacy and safety of subcutaneous injection of peginterferon lambda in patients hospitalized with COVID-19. Methods: In this study (NCT04343976), patients admitted to hospital with COVID-19 confirmed by RT-PCR from nasopharyngeal swab were randomly assigned within 48 h to receive peginterferon lambda or placebo in a 1:1 ratio. Participants were subcutaneously injected with a peginterferon lambda or saline placebo at baseline and day 7 and were followed up until day 14. Results: We enrolled 14 participants; 6 participants (85.7%) in the peginterferon lambda group and 1 participant (14.3%) in the placebo group were treated with remdesivir prior to enrollment. Fifty percent of participants were SARS-CoV-2 RNA negative at baseline although they tested SARS-CoV-2 RNA positive within 48 h of randomization. Among participants who were SARS-CoV-2 positive at baseline, 2 out of 5 participants (40%) in the peginterferon lambda group became negative at day 14, while 0 out of 2 participants (0%) in the placebo group achieved negativity for SARS-CoV-2 by day 14 (p > 0.05). The median change in viral load (log copies per ml) was +1.72 (IQR -2.78 to 3.19) in the placebo group and -2.22 (IQR -3.24 to 0.55) in the peginterferon lambda group at day 14 (p = 0.24). Symptomatic changes did not differ between the two groups. Peginterferon lambda was well tolerated with a few treatment-related adverse effects. Conclusion: Peginterferon lambda appears to accelerate SARS-CoV-2 viral load decline and improve plasma disease progression markers in hospitalized patients with COVID-19.

Performance of D-dimer to lymphocyte ratio in predicting the mortality of COVID-19 patients.

Background: Nowadays, there is still no effective treatment developed for COVID-19, and early identification and supportive therapies are essential in reducing the morbidity and mortality of COVID-19. This is the first study to evaluate D-dimer to lymphocyte ratio (DLR) as a prognostic utility in patients with COVID-19. Methods: We retrospectively analyzed 611 patients and separated them into groups of survivors and non-survivors. The area under the curve (AUC) of various predictors integrated into the prognosis of COVID-19 was compared using the receiver operating characteristic (ROC) curve. In order to ascertain the interaction between DLR and survival in COVID-19 patients, the Kaplan-Meier (KM) curve was chosen. Results: Age (OR = 1.053; 95% CI, 1.022-1.086; P = 0.001), NLR (OR = 1.045; 95% CI, 1.001-1.091; P = 0.046), CRP (OR = 1.010; 95% CI, 1.005-1.016; P < 0.001), PT (OR = 1.184; 95% CI, 1.018-1.377; P = 0.029), and DLR (OR = 1.048; 95% CI, 1.018-1.078; P = 0.001) were the independent risk factors related with the mortality of COVID-19. DLR had the highest predictive value for COVID-19 mortality with the AUC of 0.924. Patients' survival was lower when compared to those with lower DLR (Log Rank P <0.001). Conclusion: DLR might indicate a risk factor in the mortality of patients with COVID-19.

A hnRNPA2B1 agonist effectively inhibits HBV and SARS-CoV-2 omicron in vivo.

The twenty-first century has already recorded more than ten major epidemics or pandemics of viral disease, including the devastating COVID-19. Novel effective antivirals with broad-spectrum coverage are urgently needed. Herein, we reported a novel broad-spectrum antiviral compound PAC5. Oral administration of PAC5 eliminated HBV cccDNA and reduced the large antigen load in distinct mouse models of HBV infection. Strikingly, oral administration of PAC5 in a hamster model of SARS-CoV-2 omicron (BA.1) infection significantly decreases viral loads and attenuates lung inflammation. Mechanistically, PAC5 binds to a pocket near Asp49 in the RNA recognition motif of hnRNPA2B1. PAC5-bound hnRNPA2B1 is extensively activated and translocated to the cytoplasm where it initiates the TBK1-IRF3 pathway, leading to the production of type I IFNs with antiviral activity. Our results indicate that PAC5 is a novel small-molecule agonist of hnRNPA2B1, which may have a role in dealing with emerging infectious diseases now and in the future.

The Association Between Alveolar-Arterial Oxygen Tension Difference and the Severity of COVID-19 in Patients.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) emerged as a global pandemic and resulted in a significantly high death toll. Therefore, there is an urgent need to find a potential biomarker related to the disease severity that can facilitate early-stage intervention. METHODS: In the present study, we collected 242 laboratory-confirmed COVID-19-infected patients. The patients were grouped according to the alveolar to arterial oxygen tension difference (PA-aO2) value of COVID-19 infection after admission. RESULTS: Among the 242 laboratory-confirmed COVID-19- infected patients, 155 (64.05%) had an abnormal PA-aO2 value on admission. Compared with the normal PA-aO2 group, the median age of the abnormal PA-aO2 group was significantly older (p = 0.032). Symptoms such as fever, cough, and shortness of breath were more obvious in the abnormal PA-aO2 group. The proportion of severe events in the abnormal PA-aO2 group was higher than the normal PA-aO2 group (10.34% vs. 23.23%, p = 0.013). The abnormal PA-aO2 group had a higher possibility of developing severe events compared with the normal PA-aO2 group (HR 2.622, 95% CI 1.197-5.744, p = 0.016). After adjusting for age and common comorbidities (hypertension and cardiovascular disease), the abnormal PA-aO2 group still exhibited significantly elevated risks of developing severe events than the normal PA-aO2 group (HR 2.986, 95% CI 1.220-7.309, p = 0.017). Additionally, the abnormal PA-aO2 group had more serious inflammation/coagulopathy/fibrinolysis parameters than the normal PA-aO2 group. CONCLUSION: Abnormal PA-aO2 value was found to be common in COVID-19 patients, was strongly related to severe event development, and could be a potential biomarker for the prognosis of COVID-19 patients.

Development of a multiplex RT-PCR method for the detection of four porcine enteric coronaviruses.

Porcine enteric coronaviruses are pathogens that cause viral diarrhea in pigs and are widely prevalent worldwide. Moreover, studies have shown that some porcine enteric coronaviruses can infect humans and poultry. In order to effectively monitor these viruses, it is necessary to establish a multiple detection method to understand their prevalence and conduct in-depth research. Common porcine enteric coronaviruses include Porcine epidemic diarrhea virus (PEDV), Porcine transmissible gastroenteritis virus (TGEV), Porcine delta coronavirus (PDCoV), and Swine acute diarrhea syndrome coronavirus (SADS-CoV). Pigs infected with these viruses have the common clinical symptoms that are difficult to distinguish. A quadruplex RT-PCR (reverse transcription-polymerase chain reaction) method for the simultaneous detection of PEDV, PDCoV, TGEV and SADS-CoV was developed. Four pairs of specific primers were designed for the PEDV M gene, PDCoV N gene, TGEV S gene and SADS-CoV RdRp gene. Multiplex RT-PCR results showed that the target fragments of PDCoV, SADS-CoV, PEDV and TGEV could be amplified by this method. and the specific fragments with sizes of 250 bp, 368 bp, 616 bp and 801 bp were amplified, respectively. This method cannot amplify any fragment of nucleic acids of Seneca Valley virus (SVV), Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and Atypical Porcine Pestivirus (APPV), and has good specificity. The lowest detection limits of PDCoV, PEDV, TGEV and SADS-CoV were 5.66 × 105 copies/µL, 6.48 × 105 copies/µL, 8.54 × 105 copies/µL and 7.79 × 106 copies/µL, respectively. A total of 94 samples were collected from pig farms were analyzed using this method. There were 15 positive samples for PEDV, 3 positive samples for mixed infection of PEDV and PDCoV, 2 positive samples for mixed infection of PEDV and TGEV, and 1 positive sample for mixed infection of PEDV, TGEV, and PDCoV. Multiplex RT-PCR method could detect four intestinal coronaviruses (PEDV, PDCoV, TGEV, and SADS-CoV) in pigs efficiently, cheaply and accurately, which can be used for clinical large-scale epidemiological investigation and diagnosis.

Potential links between COVID-19 and periodontitis: a bioinformatic analysis based on GEO datasets.

BACKGROUND: 2019 Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic has already had a serious influence on human existence, causing a huge public health concern for countries all around the world. Because SARS-CoV-2 infection can be spread by contact with the oral cavity, the link between oral illness and COVID-19 is gaining traction. Through bioinformatics approaches, we explored the possible molecular mechanisms linking the COVID-19 and periodontitis to provide the basis and direction for future research. METHODS: Transcriptomic data from blood samples of patients with COVID-19 and periodontitis was downloaded from the Gene Expression Omnibus database. The shared differentially expressed genes were identified. The analysis of Gene Ontology, Kyoto Encyclopedia of Genesand Genomes pathway, and protein-protein interaction network was conducted for the shared differentially expressed genes. Top 5 hub genes were selected through Maximal Clique Centrality algorithm. Then mRNA-miRNA network of the hub genes was established based on miRDB database, miRTarbase database and Targetscan database. The Least absolute shrinkage and selection operator regression analysis was used to discover possible biomarkers, which were then investigated in relation to immune-related genes. RESULTS: Fifty-six shared genes were identified through differential expression analysis in COVID-19 and periodontitis. The function of these genes was enriched in regulation of hormone secretion, regulation of secretion by cell. Myozenin 2 was identified through Least absolute shrinkage and selection operator regression Analysis, which was down-regulated in both COVID-19 and periodontitis. There was a positive correlation between Myozenin 2 and the biomarker of activated B cell, memory B cell, effector memory CD4 T cell, Type 17 helper cell, T follicular helper cell and Type 2 helper cell. CONCLUSION: By bioinformatics analysis, Myozenin 2 is predicted to correlate to the pathogenesis and immune infiltrating of COVID-19 and periodontitis. However, more clinical and experimental researches are needed to validate the function of Myozenin 2.

Ventricular septal defect complicating myocardial infarction: A case of delayed percutaneous transcatheter closure.

A 57-year-old man suffered chest pain during the COVID-19 pandemic, but he delayed medical treatment due to fear of infection. After 4 months, symptoms of chest tightness and shortness of breath appeared. Electrocardiogram (ECG) revealed old myocardial infarction; color sonography and myocardial computed tomography revealed apical myocardial defect. He refused surgery and percutaneous transcatheter closure, and follow-up observation. After 22 months, the symptoms of chest tightness and shortness of breath aggravated. He recovered after percutaneous transcatheter closure, and was discharged. This case shows delayed closure is one of the possible options for patients without severe organ dysfunction or hemodynamic disturbance.

How online food delivery platforms contributed to the resilience of the urban food system in China during the COVID-19 pandemic

We use high-frequency data to quantify the nature and performance of online food delivery platforms during the COVID-19 pandemic in urban China, and to estimate the short- and long-term effects of lockdown and reopening measures. A staggered difference-in-differences (DID) estimation strategy and event study approach are used to identify the effects of lockdown and reopening measures on the performance of online food delivery platforms and restaurants. The results indicate that some restaurants continued to operate and offer online food delivery while lockdowns were in effect. Both the number of operating restaurants and their online food delivery services rebounded and experienced further growth after lockdowns were lifted. The adjustment path of the online food delivery business following the implementation of lockdowns differed from the adjustment path following the lifting of lockdowns. The lockdown and reopening measures did not affect all types of restaurant/cuisine equally. We also examine possible impact mechanisms of lockdown measures on online food delivery and restaurants, and conduct robustness checks to confirm the stability of the main findings. This study contributes to the existing literature by confirming the positive contribution of online food delivery to the resilience of urban food systems in response to unexpected external shocks. Our results have implications for the design of policies to guarantee food supply and help urban food systems adapt to unexpected shocks.

Association between inflammatory cytokines and anti-SARS-CoV-2 antibodies in hospitalized patients with COVID-19.

BACKGROUND: COVID-19 patients may experience "cytokine storm" when human immune system produces excessive cytokines/chemokines. However, it remains unclear whether early responses of inflammatory cytokines would lead to high or low titers of anti-SARS-CoV-2 antibodies. METHODS: This retrospective study enrolled a cohort of 272 hospitalized patients with laboratory-confirmed SARS-CoV-2. Laboratory assessments of serum cytokines (IL-2R, IL-6, IL-8, IL-10, TNF-α), anti-SARS-CoV-2 IgG/IgM antibodies, and peripheral blood biomarkers were conducted during hospitalization. RESULTS: At hospital admission, 36.4% patients were severely ill, 51.5% patients were ≥ 65 years, and 60.3% patients had comorbidities. Higher levels of IL-2R and IL-6 were observed in older patients (≥65 years). Significant differences of IL-2R (week 2 to week ≥5 from symptom onset), IL-6 (week 1 to week ≥5), IL-8 (week 2 to week ≥5), and IL-10 (week 1 to week 3) were observed between moderately-ill and severely ill patients. Anti-SARS-CoV-2 IgG titers were significantly higher in severely ill patients than in moderately ill patients, but such difference was not observed for IgM. High titers of early-stage IL-6, IL-8, and TNF-α (≤2 weeks after symptom onset) were positively correlated with high titers of late-stage IgG (≥5 weeks after symptom onset). Deaths were mostly observed in severely ill older patients (45.9%). Survival analyses revealed risk factors of patient age, baseline COVID-19 severity, and baseline IL-6 that affected survival time, especially in severely ill older patients. CONCLUSION: Early responses of elevated cytokines such as IL-6 reflect the active immune responses, leading to high titers of IgG antibodies against COVID-19.

Effect of quantitative assessment of nosocomial infection management in normalized prevention and control phase of the COVID-19 pneumonia epidemic

OBJECTIVE To evaluate the implementation of normalization prevention and control measures for the COVID-2019 epidemic by quantitative assessment, and to evaluated the effectiveness of epidemic prevention and control and its impact on the quality of nosocomial infection management. METHODS The infection control measures of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology were summarized and refined them into 16 quantitative assessment indicators, which will be inspected and assessed throughout the hospital from from Jul. to Dec. 2020. Data on epidemic prevention and control, incidence of nosocomial infection, hand hygiene related data during the same period were collected. RESULTS No confirmed cases of novel coronavirus pneumonia were found, and no asymptomatic infection cases were found to infect others. The incidence of nosocomial infection from July to December 2020 decreased compared with the same period in 2019. Stratified analysis showed that the infection of upper respiratory tract, urinary tract and gastrointestinal tract were significantly reduced, while there was no significant change in the infection rate of the type I incision surgical sites, the incidence of intravascular catheter related bloodstream infection, the incidence of ventilator-associated pneumonia and the incidence of catheter-related urinary tract infection. The compliance of hand hygiene, the accuracy of hand hygiene and the standard rate of hand disinfectant consumption were significantly improved, while there was no significant change in the consumption of dry hand tissue and hand sanitizer. CONCLUSION Quantitative assessment can effectively evaluate the implementation of normalized prevention and control measures of epidemic situation. The timely detection and elimination of potential epidemic hazards will have a positive impact on the improvement of the quality of nosocomial infection management.

ULNet for the detection of coronavirus (COVID-19) from chest X-ray images.

Novel coronavirus disease 2019 (COVID-19) is an infectious disease that spreads very rapidly and threatens the health of billions of people worldwide. With the number of cases increasing rapidly, most countries are facing the problem of a shortage of testing kits and resources, and it is necessary to use other diagnostic methods as an alternative to these test kits. In this paper, we propose a convolutional neural network (CNN) model (ULNet) to detect COVID-19 using chest X-ray images. The proposed architecture is constructed by adding a new downsampling side, skip connections and fully connected layers on the basis of U-net. Because the shape of the network is similar to UL, it is named ULNet. This model is trained and tested on a publicly available Kaggle dataset (consisting of a combination of 219 COVID-19, 1314 normal and 1345 viral pneumonia chest X-ray images), including binary classification (COVID-19 vs. Normal) and multiclass classification (COVID-19 vs. Normal vs. Viral Pneumonia). The accuracy of the proposed model in the detection of COVID-19 in the binary-class and multiclass tasks is 99.53% and 95.35%, respectively. Based on these promising results, this method is expected to help doctors diagnose and detect COVID-19. Overall, our ULNet provides a quick method for identifying patients with COVID-19, which is conducive to the control of the COVID-19 pandemic.

One-year follow-up of chest CT findings in patients after SARS-CoV-2 infection.

BACKGROUND: Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge. METHODS: A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated. RESULTS: A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0-2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older (p = 0.01), with higher rate in current smokers (p = 0.04), higher rate in hypertensives (p = 0.05), lower SaO2 (p = 0.004), and higher prevalence of secondary bacterial infections during acute phase (p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01-1.15, p = 0.02). Pulmonary functions of total lung capacity (p = 0.008) and residual volume (p < 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores. CONCLUSION: During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.

Use of Electronic Medical Records to Estimate Changes in Pregnancy and Birth Rates During the COVID-19 Pandemic.

Importance: The influence of the COVID-19 pandemic on fertility rates has been suggested in the lay press and anticipated based on documented decreases in fertility and pregnancy rates during previous major societal and economic shifts. Anticipatory planning for birth rates is important for health care systems and government agencies to accurately estimate size of economy and model working and/or aging populations. Objective: To use projection modeling based on electronic health care records in a large US university medical center to estimate changes in pregnancy and birth rates prior to and after the COVID-19 pandemic societal lockdowns. Design, Setting, and Participants: This cohort study included all pregnancy episodes within a single US academic health care system retrospectively from 2017 and modeled prospectively to 2021. Data were analyzed September 2021. Exposures: Pre- and post-COVID-19 pandemic societal shutdown measures. Main Outcomes and Measures: The primary outcome was number of new pregnancy episodes initiated within the health care system and use of those episodes to project birth volumes. Interrupted time series analysis was used to assess the degree to which COVID-19 societal changes may have factored into pregnancy episode volume. Potential reasons for the changes in volumes were compared with historical pregnancy volumes, including delays in starting prenatal care, interruptions in reproductive endocrinology and infertility services, and preterm birth rates. Results: This cohort study documented a steadily increasing number of pregnancy episodes over the study period, from 4100 pregnancies in 2017 to 4620 in 2020 (28 284 total pregnancies; median maternal [interquartile range] age, 30 [27-34] years; 18 728 [66.2%] White women, 3794 [13.4%] Black women; 2177 [7.7%] Asian women). A 14% reduction in pregnancy episode initiation was observed after the societal shutdown of the COVID-19 pandemic (risk ratio, 0.86; 95% CI, 0.79-0.92; P < .001). This decrease appeared to be due to a decrease in conceptions that followed the March 15 mandated COVID-19 pandemic societal shutdown. Prospective modeling of pregnancies currently suggests that a birth volume surge can be anticipated in summer 2021. Conclusions and Relevance: This cohort study using electronic medical record surveillance found an initial decline in births associated with the COVID-19 pandemic societal changes and an anticipated increase in birth volume. Future studies can further explore how pregnancy episode volume changes can be monitored and birth rates projected in real-time during major societal events.

Emergency logistics network design based on space–time resource configuration

The occurrence of natural disasters or accidents causes the obstruction or interruption of road traffic connectivity and affects the transportation of essential materials, especially for cross-regional delivery under emergency situations. Affected by COVID-19, government administrators establish cross-regional quarantine roadblocks to reduce the risk of virus transmission caused by cross-regional transportation. In this study, we propose an emergency logistics network design problem with resource sharing under collaborative alliances. We construct a state–space–time network-based bi-objective mixed integer programming model to optimize the vehicle routes in order to meet customer demands for essential materials with the lowest cost and highest emergency response speed under limited transportation resources. A two-stage hybrid heuristic algorithm is then proposed to find good-quality solutions for the problem. Clustering results are obtained using a 3D k-means clustering algorithm with the consideration of time and space indices. The optimization of the initial population generated by the improved Clarke and Wright saving method and improved nondominated sorting genetic algorithm-II with elite retention strategy provides stable and excellent performance for the searching of Pareto frontier. The cost difference of the entire emergency logistics network before and after collaboration, i.e., the profit, is fairly allocated to the participants (i.e., logistics service providers) through the Shapley value method. A real-world case in Chongqing City, China is used to validate the effectiveness of the proposed model and algorithm. This study contributes to smart transportation and logistics system in emergency planning and has particular implications for the optimal response of existing logistics system to the current COVID-19 pandemic.

Fine-Scale Space-Time Cluster Detection of COVID-19 in Mainland China Using Retrospective Analysis.

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a different maximum clustering radius at the family-level based on case dates of onset. The results show that the detected clusters vary with the clustering radius. Forty-three space-time clusters were detected with a maximum clustering radius of 100 km and 88 clusters with a maximum clustering radius of 10 km from 2 December 2019 to 20 June 2020. Using a smaller clustering radius may identify finer clusters. Hubei has the most clusters regardless of scale. In addition, most of the clusters were generated in February. That indicates China's COVID-19 epidemic prevention and control strategy is effective, and they have successfully prevented the virus from spreading from Hubei to other provinces over time. Well-developed provinces or cities, which have larger populations and developed transportation networks, are more likely to generate space-time clusters. The analysis based on the data of cases from onset may detect the start times of clusters seven days earlier than similar research based on diagnosis dates. Our analysis of space-time clustering based on the data of cases on the family-level can be reproduced in other countries that are still seriously affected by the epidemic such as the USA, India, and Brazil, thus providing them with more precise signals of clustering.

Resilience, coping style, and COVID-19 stress: effects on the quality of life in frontline health care workers.

The aims of the study were to assess the contribution of resilience, coping style, and COVID-19 stress on the quality of life (QOL) in frontline health care workers (HCWs). The study was a cross-sectional surveyperformed among 309 HCWs in a tertiaryhospital during the outbreak of COVID-19 in China. Data were collected through an anonymous, self-rated questionnaire, including demographic data, a 10-item COVID-19 stress questionnaire, Generic QOL Inventory-74, Connor-Davidson Resilience Scale, and the Simplified Coping Style Questionnaire. Hierarchical regression was used to analyse the relationship between the study variables and the QOL. Among the 309 participants, resilience and active coping were positively correlated with the QOL (P<0.001), whereas, working in confirmed case wards, COVID-19 stress, and passive coping were negatively correlated with the QOL (P<0.001). Resilience and the active coping were negatively correlated with COVID-19 stress (P<0.001). Resilience, coping style,and COVID-19 stressaccounted for 32%, 13%, and 8% of the variance in predicting the Global QOL, respectively. In conclusion, working in confirmed COVID-19 case wards and COVID-19 stress impaired the QOL in HCWs. Psychological intervention to improve the resilience and coping style, and reduce COVID-19 stress are important in improving the QOL and mental health of HCWs.