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1.
Frontiers in Public Health ; 10:933075, 2022.
Article in English | MEDLINE | ID: covidwho-2215404

ABSTRACT

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.617.2 (also named the Delta variant) was declared as a variant of concern by the World Health Organization (WHO). This study aimed to describe the outbreak that occurred in Nanjing city triggered by the Delta variant through the epidemiological parameters and to understand the evolving epidemiology of the Delta variant.

2.
Ieee Transactions on Cybernetics ; 2022.
Article in English | Web of Science | ID: covidwho-2192081

ABSTRACT

Automated detecting lung infections from computed tomography (CT) data plays an important role for combating coronavirus 2019 (COVID-19). However, there are still some challenges for developing AI system: 1) most current COVID-19 infection segmentation methods mainly relied on 2-D CT images, which lack 3-D sequential constraint;2) existing 3-D CT segmentation methods focus on single-scale representations, which do not achieve the multiple level receptive field sizes on 3-D volume;and 3) the emergent breaking out of COVID-19 makes it hard to annotate sufficient CT volumes for training deep model. To address these issues, we first build a multiple dimensional-attention convolutional neural network (MDA-CNN) to aggregate multiscale information along different dimension of input feature maps and impose supervision on multiple predictions from different convolutional neural networks (CNNs) layers. Second, we assign this MDA-CNN as a basic network into a novel dual multiscale mean teacher network ((DMT)-T-2-Net) for semi-supervised COVID-19 lung infection segmentation on CT volumes by leveraging unlabeled data and exploring the multiscale information. Our (DMT)-T-2-Net encourages multiple predictions at different CNN layers from the student and teacher networks to be consistent for computing a multiscale consistency loss on unlabeled data, which is then added to the supervised loss on the labeled data from multiple predictions of MDA-CNN. Third, we collect two COVID-19 segmentation datasets to evaluate our method. The experimental results show that our network consistently outperforms the compared state-of-the-art methods.

3.
Innov Aging ; 6(Suppl 1):334, 2022.
Article in English | PubMed Central | ID: covidwho-2188905

ABSTRACT

Nursing facilities (NFs) have historically struggled to maintain adequate nurse staffing. We used PBJ data linked with other publicly available sources and conducted stakeholder interviews to understand nurse staffing between 2019 and 2020. We found large declines in the population of NF residents and in staffing hours. Measured in hours per resident day (HPRD) to account for the size of the NF resident population, there were slight increases in staffing. Staffing was nonetheless a major challenge for NFs because they required increased staffing due to the impact of the pandemic. NFs in higher quartiles of percentage of minority residents lost nurse staffing HPRD relative to NFs in the lowest quartile of minority residents. Stakeholders explained that NFs with more minority residents were likely to employ staff who live in more vulnerable communities with a greater concentration of minorities, who were more impacted by COVID.

4.
Innov Aging ; 6(Suppl 1):333-4, 2022.
Article in English | PubMed Central | ID: covidwho-2188904

ABSTRACT

The media has reported recent increases in nursing home closures. This study examined closures from 2011-2019, identified facility and market characteristics associated with closures, and assessed the impact of closures on quality and access. We identified closures using termination dates and gaps in certification surveys and conducted descriptive and multivariate analysis. We identified 1,220 closures, with large increases in closure rates in 2018 and 2019 and geographic clusters. Chain facilities, urban facilities and smaller facilities were more likely to close, as were facilities with higher percentages of non-white and Medicaid residents. Staffing and quality five-star ratings had a nonlinear relationship with closure, which suggests Medicaid funding may impact closures rates. We found both the number of beds per 1,000 elderly and occupancy rates decreased, including in high-quality facilities. Closures should be examined further in the context of the COVID-19 pandemic.

5.
Brief Bioinform ; 2023.
Article in English | PubMed | ID: covidwho-2188256

ABSTRACT

The proliferation of single-cell multimodal sequencing technologies has enabled us to understand cellular heterogeneity with multiple views, providing novel and actionable biological insights into the disease-driving mechanisms. Here, we propose a comprehensive end-to-end single-cell multimodal analysis framework named Deep Parametric Inference (DPI). DPI transforms single-cell multimodal data into a multimodal parameter space by inferring individual modal parameters. Analysis of cord blood mononuclear cells (CBMC) reveals that the multimodal parameter space can characterize the heterogeneity of cells more comprehensively than individual modalities. Furthermore, comparisons with the state-of-the-art methods on multiple datasets show that DPI has superior performance. Additionally, DPI can reference and query cell types without batch effects. As a result, DPI can successfully analyze the progression of COVID-19 disease in peripheral blood mononuclear cells (PBMC). Notably, we further propose a cell state vector field and analyze the transformation pattern of bone marrow cells (BMC) states. In conclusion, DPI is a powerful single-cell multimodal analysis framework that can provide new biological insights into biomedical researchers. The python packages, datasets and user-friendly manuals of DPI are freely available at https://github.com/studentiz/dpi.

6.
Scientific Reports ; 12(1):21779, 2022.
Article in English | MEDLINE | ID: covidwho-2186033

ABSTRACT

Elevated serum cytokine production in COVID-19 patients is associated with disease progression and severity. However, the stimuli that initiate cytokine production in patients remain to be fully revealed. Virus-infected cells release virus-associated exosomes, extracellular vesicles of endocytic origin, into the blood to deliver viral cargoes able to regulate immune responses. Here, we report that plasma exosomes of COVID-19 patients contain SARS-CoV-2 double stranded RNA (dsRNA) and stimulate robust production of interleukin-6 (IL-6), IL-8, tumor necrosis factor-alpha (TNF-alpha), and other inflammatory cytokines and chemokines by human peripheral mononuclear cells. Exosome depletion abolished these stimulated responses. COVID-19 plasma exosomes induced proinflammatory responses in CD4+ T cells, CD8+ T cells, and CD14+ monocytes but not significantly in regulatory T cells, Th17 T cells, or central memory T cells. COVID-19 plasma exosomes protect the SARS-CoV-2 dsRNA cargo from RNase and deliver the dsRNA into recipient cells. These exosomes significantly increase expression of endosomal toll-like receptor 3 (TLR3), TLR7, TLR8, and TLR9 in peripheral T cells and monocytes. A pharmacological inhibitor of TLR3 considerably reduced cytokine and chemokine production by CD4+ and CD8+ T cells but not by CD14+ monocytes, highlighting divergent signaling pathways of immune cells in response to COVID-19 plasma exosomes. Our results identify a novel model of intercellular crosstalk following SARS-CoV-2 infection that evoke immune responses positioned to contribute to elevated cytokine production associated with COVID-19 progression, severity, and long-haul symptoms.

7.
Arch Virol ; 168(2):64, 2023.
Article in English | PubMed | ID: covidwho-2174219

ABSTRACT

BACKGROUND: Stringent nonpharmaceutical interventions (NPIs) have been implemented worldwide to combat the COVID-19 pandemic, and the circulation and seasonality of common respiratory viruses have subsequently changed. There have been few multicentre studies or comparisons of the prevalence of respiratory viruses accounting for community-acquired pneumonia (CAP) in hospitalized children between the pre-COVID period and the period after community and school reopening in the setting of the zero-COVID policy. METHODS: We included 1543 children with CAP who required hospitalization from November 1, 2020 to April 30, 2021 (period 1), and 629 children with the same conditions from November 1, 2018, to April 30, 2019 (period 2), in our study. All respiratory samples from these patients were screened for six respiratory viruses (respiratory syncytial virus [RSV], adenovirus [ADV], influenza A virus [Flu A], influenza B virus [Flu B], parainfluenza virus type 1 [PIV1], and parainfluenza virus type 3 [PIV3]) using a multiplex real-time PCR assay. RESULTS AND CONCLUSIONS: The median ages of the enrolled patients at the time of diagnosis were 1.5 years and 1.0 years for period 1 and period 2, respectively. In period 1, viral pathogens were detected in 50.3% (776/1543) of the enrolled patients. The most frequently identified viral pathogen was RSV (35.9%, 554/1543), followed by PIV3 (9.6%, 148/1543), PIV1 (3.6%, 56/1543), ADV (3.4%, 52/1543), Flu A (1.0%, 16/1543), and Flu B (0.8%, 13/1543). The total detection rates of these six viruses in the peak season of CAP were at the pre-COVID level. The prevalence of Flu A decreased dramatically, and circulation activity was low compared to pre-COVID levels, while the incidence of PIV3 increased significantly. There were no significant differences in the detection rates of RSV, ADV, Flu B, and PIV1 between the two periods. Our results showed that respiratory viruses accounted for CAP in hospitalized children at pre-COVID levels as communities and schools reopened within the zero-COVID policy, although the prevalence aetiology spectrum varied.

8.
Frontiers in Public Health ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2163164

ABSTRACT

BackgroundSince January 2020, the continuous and severe COVID-19 epidemic has ravaged various countries around the world and affected their emergency medical systems (EMS). The total number of emergency calls and the number of emergency calls for central nervous system (CNS) symptoms during the 2020 COVID-19 outbreak in Hangzhou, China (January 20-March 20) were investigated, and it was investigated whether these numbers had decreased as compared with the corresponding period in 2019. MethodsThe number of daily emergency calls, ambulance dispatches, and rescues at the Hangzhou Emergency Center (HEC) was counted. The CNS symptoms considered in this study included those of cerebrovascular diseases, mental and behavioral disorders, and other neurological diseases. ResultsIt was found that, during the 2020 study period, the number of emergency calls was 33,563, a decrease of 19.83% (95% CI: 14.02-25.41%) as compared to the 41,863 emergency calls in 2019 (P < 0.01). The number of ambulances dispatched was 10,510, a decrease of 25.55% (95 %CI: 18.52-35.11%) as compared to the 14,117 ambulances dispatched in 2019 (P < 0.01). The number of rescues was 7,638, a decrease of 19.67% (95% CI: 16.12-23.18%) as compared with the 9,499 rescues in 2019 (P < 0.01). It was also found that the number of emergency calls related to CNS symptoms, including symptoms of cerebrovascular diseases, mental and behavioral disorders, and other neurological diseases, was significantly reduced (P < 0.01). ConclusionThe total number of medical emergency calls and the number of emergency calls for CNS symptoms occurring in a large city in China decreased significantly during the COVID-19 epidemic.

9.
International Journal of Social Psychiatry ; : 207640221141784, 2022.
Article in English | MEDLINE | ID: covidwho-2162135

ABSTRACT

BACKGROUND: Returning to social life after the lifting of COVID-19 lockdown may increase risk of social anxiety, which is highly co-morbid with depression. However, few studies have reported the association between them.

10.
Journal of Theoretical Biology ; 556:111296, 2022.
Article in English | MEDLINE | ID: covidwho-2105497

ABSTRACT

Seroprevalence studies can estimate proportions of the population that have been infected or vaccinated, including infections that were not reported because of the lack of symptoms or testing. Based on information from studies in the United States from mid-summer 2020 through the end of 2021, we describe proportions of the population with antibodies to SARS-CoV-2 as functions of age and time. Slices through these surfaces at arbitrary times provide initial and target conditions for simulation modeling. They also provide the information needed to calculate age-specific forces of infection, attack rates, and - together with contact rates - age-specific probabilities of infection on contact between susceptible and infectious people. We modified the familiar Susceptible-Exposed-Infectious-Removed (SEIR) model to include features of the biology of COVID-19 that might affect transmission of SARS-CoV-2 and stratified by age and location. We consulted the primary literature or subject matter experts for contact rates and other parameter values. Using time-varying Oxford COVID-19 Government Response Tracker assessments of US state and DC efforts to mitigate the pandemic and compliance with non-pharmaceutical interventions (NPIs) from a YouGov survey fielded in the US during 2020, we estimate that the efficacy of social-distancing when possible and mask-wearing otherwise at reducing susceptibility or infectiousness was 31% during the fall of 2020. Initialized from seroprevalence among people having commercial laboratory tests for purposes other than SARS-CoV-2 infection assessments on 7 September 2020, our age- and location-stratified SEIR population model reproduces seroprevalence among members of the same population on 25 December 2020 quite well. Introducing vaccination mid-December 2020, first of healthcare and other essential workers, followed by older adults, people who were otherwise immunocompromised, and then progressively younger people, our metapopulation model reproduces seroprevalence among blood donors on 4 April 2021 less well, but we believe that the discrepancy is due to vaccinations being under-reported or blood donors being disproportionately vaccinated, if not both. As experimenting with reliable transmission models is the best way to assess the indirect effects of mitigation measures, we determined the impact of vaccination, conditional on NPIs. Results indicate that, during this period, vaccination substantially reduced infections, hospitalizations and deaths. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics."

11.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(10): 1395-1400, 2022 Oct 06.
Article in Chinese | MEDLINE | ID: covidwho-2090421

ABSTRACT

In the context of the global pandemic of COVID-19, the epidemic intensity, epidemic characteristics and infection risk of influenza have presented new features. COVID-19 and influenza have simultaneously emerged in many regions of the world. COVID-19 and influenza are similar in terms of transmission mode, clinical symptoms and other aspects. There are also similarities in the mechanism of influenza virus and novel coronavirus on cells. At the same time, it is feasible and significant to do a good job in the prevention and control of COVID-19 and influenza. This paper discusses the relevant strategies and measures for the joint prevention and control of influenza and novel coronavirus from the aspects of influenza vaccination to prevent co-infection, simultaneous vaccination of influenza vaccine and novel coronavirus vaccine, etc., and puts forward corresponding thoughts and suggestions, in order to provide scientific support for the formulation of strategies on seasonal influenza vaccine and novel coronavirus vaccination.


Subject(s)
COVID-19 , Influenza Vaccines , Influenza, Human , Humans , Influenza, Human/prevention & control , Influenza, Human/epidemiology , COVID-19 Vaccines , COVID-19/prevention & control , Seasons , Vaccination , SARS-CoV-2
12.
18th International Conference on Intelligent Computing, ICIC 2022 ; 13394 LNCS:722-730, 2022.
Article in English | Scopus | ID: covidwho-2085270

ABSTRACT

COVID-19 and SARS virus are two related coronaviruses. In recent years, the increasingly serious epidemic situation has become the focus of all human beings, and has brought a significant impact on daily life. So, we proposed a link analysis of the two viruses. We obtained all the required COVID-19 and SARS virus data from the Uniprot database website, and we preprocessed the data after obtaining the data. In the prediction of the binding site of the COVID-19 and SARS, it is to judge the validity between the two binding sites. In response to this problem, we used Adaboost, voting-classifier and SVM classifier, and compared different classifier strategies through experiments. Among them, Metal binding site can effectively improve the accuracy of protein binding site prediction, and the effect is more obvious. Provide assistance for bioinformatics research. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

13.
Chinese Science Bulletin-Chinese ; 67(16):1783-1795, 2022.
Article in Chinese | Web of Science | ID: covidwho-1928264

ABSTRACT

In response to the construction process of Healthy China. it is rather important to create a safe, healthy and energy-efficient indoor environment for public buildings. The public building space is often densely populated, with a large flow of people and many types of air pollution, which presents non-uniform dynamic distribution characteristics. This brings great challenges to the control of indoor air safety, especially during the pandemic period of COVID-19. Excessive ventilation may not only cause large energy waste. but also lead to cross-contamination and even a cluster of infection. In this paper, an operation and maintenance (O&M) control system for indoor air safety is developed based on the core concepts and basic methods of human ergonomics. In this system, one of the important human environmental variables is focused for control, i.e.. indoor air pollution level. Especially after the outbreak of COVID-19. droplets and droplet nuclei from respiration are the most significant air pollution categories required for mitigation. Towards the efficient control of air pollution in large public buildings. it should further take into account the interaction of human, equipment and machines (i.e., ventilation_ air purification and disinfection and intelligent control system) and building environment. Firstly, on the basis of the online monitoring of indoor air pollution concentration and personnel flow, the non-uniform dynamic distribution of indoor pollutants and personnel can be obtained by using the non-uniform and low-dimensional rapid prediction models and computer vision processing. Then, the optimal setting results of ventilation parameters (e.g., ventilation modes, supply air rate. etc.) can be outputted by the environmental control decision system. Finally, based on a combination of monitoring sensors, controllers and actuator hardware equipment (at the location of fans or dampers), the intelligent regulation and control of ventilation system can be realized, aimed at minimizing energy consumption and reducing pollutant concentration and exposure level. Meanwhile, the air purification and disinfection system (especially for the disinfection of virus particles) are operated under the condition of the ventilated environment, which can serve as a powerful auxiliary to the maintenance of indoor air safety. The workflow and effect of the O&M control system are demonstrated by an engineering application case of the front hall in the International Convention and Exhibition Center. The results indicate that the non-uniform and low-dimensional rapid prediction model for pollutant concentration is effective for the ventilation control with the average prediction difference of 11.9%. The implementation of the intelligent ventilation system can reduce the risk of human infection to less than 4%. and its energy-saving ratio for the ventilation can be as high as about 45%. Through optimizing the layout strategies of disinfection devices based on the intelligent ventilation control, the space accessibility of negative oxygen ions can be well accepted, to further increase the removal efficiency of air pollution. The calculated value of space disinfection rate is more than 99%, which can further reduce the risk of infection by 1-2 orders of magnitude. This study can provide an important reference for the promotion and upgrading of O&M control system for indoor air safety.

14.
Hong Kong Journal of Paediatrics ; 27(2):118-125, 2022.
Article in English | Scopus | ID: covidwho-1843202

ABSTRACT

Since the first report of COVID-19 in Wuhan, China, the disease has rapidly spread to many countries worldwide. The initial reports showed that the incidence rate in adults was higher, while children and adolescents had fewer cases of infection. However, the number of COVID-19 cases has gradually increased in children and adolescents. Therefore, this study aimed to assess the percentage of children and/or adolescents of the total patients diagnosed with COVID-19. PubMed, Embase, Web of Science and the Cochrane Library were searched to find relevant studies. All statistical analyses were conducted using StataMP 14 software. A total of 12 studies met the inclusion criteria. The final results showed that the percentage of children and/or adolescents of all COVID-19 cases was 0.06 [95% confidence interval (CI), 0.04-0.07], which meant an average of 6 cases in children per 10,000 COVID-19 cases. The percentage of children and/or adolescents with COVID-19 was 0.03 (95% CI, 0.01-0.05), 0.09 (95% CI, 0.08-0.09), 0.09 (95% CI, 0.03-0.16) and 0.04 (95% CI, 0.00-0.10) in Asia, South America, North America and Europe, respectively. The present study showed a low percentage of COVID-19 cases of children and/or adolescents, but not without infection risk. Therefore, we should pay attention to the cases of children and/or adolescents during the COVID-19 period and raise our vigilance. © 2022, Medcom Limited. All rights reserved.

16.
China CDC Weekly ; 2(6):83-86, 2020.
Article in English | MEDLINE | ID: covidwho-1445121
17.
Journal of Real Estate Finance and Economics ; : 35, 2021.
Article in English | Web of Science | ID: covidwho-1384540

ABSTRACT

Using recently available GRESB ESG public disclosure data for REITs around the world, we examine how ESG disclosure is related to REIT debt financing and firm value. We find that REITs with higher levels of ESG disclosure have lower cost of debt, higher credit ratings, and higher unsecured debt to total debt ratio, controlling for key firm characteristics. These findings suggest that improving ESG disclosure can help REITs to gain better access to the capital markets and enhance corporate financial flexibility, as lenders have paid close attention to a firm's ESG disclosure and integrated evaluation of ESG factors into their lending decisions. Moreover, firm value of REITs is positively associated with their ESG disclosure level. When using the Covid-19 pandemic as a quasi-experimental setting, we find evidence that REITs with higher ESG disclosure levels before the pandemic exhibit higher firm value during the pandemic. These results indicate that investors do value active ESG disclosure by REITs. Additional analyses show that ESG disclosure level is sensitive to institutional ownership, implying that institutional investors may drive REIT ESG disclosure efforts. Taken together, this paper suggests that effective ESG disclosure can have a positive impact on REIT debt financing and firm value due to the increased corporate transparency, and the ESG reporting framework developed by GRESB appears to be effective to provide transparency and comparability across the global real estate industry.

18.
Applied Sciences (Switzerland) ; 11(16), 2021.
Article in English | Scopus | ID: covidwho-1365591

ABSTRACT

The world today is being hit by COVID-19. As opposed to fingerprints and ID cards, facial recognition technology can effectively prevent the spread of viruses in public places because it does not require contact with specific sensors. However, people also need to wear masks when entering public places, and masks will greatly affect the accuracy of facial recognition. Accurately performing facial recognition while people wear masks is a great challenge. In order to solve the problem of low facial recognition accuracy with mask wearers during the COVID-19 epidemic, we propose a masked-face recognition algorithm based on large margin cosine loss (MFCosface). Due to insufficient masked-face data for training, we designed a masked-face image generation algorithm based on the detection of the detection of key facial features. The face is detected and aligned through a multi-task cascaded convolutional network;and then we detect the key features of the face and select the mask template for coverage according to the positional information of the key features. Finally, we generate the corresponding masked-face image. Through analysis of the masked-face images, we found that triplet loss is not applicable to our datasets, because the results of online triplet selection contain fewer mask changes, making it difficult for the model to learn the relationship between mask occlusion and feature mapping. We use a large margin cosine loss as the loss function for training, which can map all the feature samples in a feature space with a smaller intra-class distance and a larger inter-class distance. In order to make the model pay more attention to the area that is not covered by the mask, we designed an Att-inception module that combines the Inception-Resnet module and the convolutional block attention module, which increases the weight of any unoccluded area in the feature map, thereby enlarging the unoccluded area’s contribution to the identification process. Experiments on several masked-face datasets have proved that our algorithm greatly improves the accuracy of masked-face recognition, and can accurately perform facial recognition with masked subjects. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

19.
Indoor and Built Environment ; 30(6):727-731, 2021.
Article in English | EMBASE | ID: covidwho-1338899
20.
Zhonghua Yi Xue Za Zhi ; 101(26): 2029-2036, 2021 Jul 13.
Article in Chinese | MEDLINE | ID: covidwho-1317266

ABSTRACT

The disease burden and economic burden of seasonal influenza is substantial in China, and the Coronavirus disease 2019 (COVID-19) pandemic has brought new challenges to the prevention and control of influenza. As a priority group of influenza vaccination, the elderly are at higher risk of influenza-associated severe symptoms and deaths, and they are more price-sensitive vaccine users with better cost-effectiveness of vaccination program. Therefore, a reasonable financing mechanism of influenza vaccination should be designed for the elderly to increase their vaccination rate. This study proposes three financing strategies of influenza vaccination for the elderly in China, trying to explore the distribution of vaccination costs among individuals, central government and local governments under different financing strategies, including the individual-central-local mechanism (strategy 1), the central-local mechanism (strategy 2), and the local payment mechanism (strategy 3). Strategy 1 is feasible and sustainable for most regions in the short term. Strategy 2 is conducive to further increasing the vaccine coverage rate of the elderly. Strategy 3 encourages local fiscal payments to help relieve the financial pressure of the central government. The results revealed a relatively heavy financial burden of influenza vaccination for the elderly, and it is recommended to promote the development of a multiparty co-payment mechanism gradually based on local conditions.


Subject(s)
COVID-19 , Influenza, Human , Aged , China , Cost-Benefit Analysis , Humans , Influenza, Human/prevention & control , SARS-CoV-2 , Vaccination
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