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1.
Frontiers in Immunology ; 13, 2022.
Article in English | Web of Science | ID: covidwho-2022731

ABSTRACT

To cope with the decline in COVID-19 vaccine-induced immunity caused by emerging SARS-CoV-2 variants, a heterologous immunization regimen using chimpanzee adenovirus vectored vaccine expressing SARS-CoV-2 spike (ChAd-S) and an inactivated vaccine (IV) was tested in mice and non-human primates (NHPs). Heterologous regimen successfully enhanced or at least maintained antibody and T cell responses and effectively protected against SARS-CoV-2 variants in mice and NHPs. An additional heterologous booster in mice further improved and prolonged the spike-specific antibody response and conferred effective neutralizing activity against the Omicron variant. Interestingly, priming with ChAd-S and boosting with IV reduced the lung injury risk caused by T cell over activation in NHPs compared to homologous ChAd-S regimen, meanwhile maintained the flexibility of antibody regulation system to react to virus invasion by upregulating or preserving antibody levels. This study demonstrated the satisfactory compatibility of ChAd-S and IV in prime-boost vaccination in animal models.

2.
Microbiology Spectrum ; : e0226322, 2022.
Article in English | MEDLINE | ID: covidwho-2019798

ABSTRACT

We investigated the distribution, virulence, and pathogenic characteristics of mutated SARS-CoV-2 to clarify the association between virulence and the viral spreading ability of current and future circulating strains. Chinese rhesus macaques were infected with ancestral SARS-CoV-2 strain GD108 and Beta variant B.1.351 (B.1.351) and assessed for clinical signs, viral distribution, pathological changes, and pulmonary inflammation. We found that GD108 replicated more efficiently in the upper respiratory tract, whereas B.1.351 replicated more efficiently in the lower respiratory tract and lung tissue, implying a reduced viral shedding and spreading ability of B.1.351 compared with that of GD108. Importantly, B.1.351 caused more severe lung injury and dramatically elevated the level of inflammatory cytokines compared with those observed after infection with GD108. Moreover, both B.1.351 and GD108 induced spike-specific T-cell responses at an early stage of infection, with higher levels of interferon gamma (IFN-gamma) and tumor necrosis factor alpha (TNF-alpha) in the B.1.351 group and higher levels of interleukin 17 (IL-17) in the GD108 group, indicating a divergent pattern in the T-cell-mediated inflammatory "cytokine storm." This study provides a basis for exploring the pathogenesis of SARS-CoV-2 variants of concern (VOCs) and establishes an applicable animal model for evaluating the efficacy and safety of vaccines and drugs. IMPORTANCE One of the priorities of the current SARS-CoV-2 vaccine and drug research strategy is to determine the changes in transmission ability, virulence, and pathogenic characteristics of SARS-CoV-2 variants. In addition, nonhuman primates (NHPs) are suitable animal models for the study of the pathogenic characteristics of SARS-CoV-2 and could contribute to the understanding of pathogenicity and transmission mechanisms. As SARS-CoV-2 variants continually emerge and the viral biological characteristics change frequently, the establishment of NHP infection models for different VOCs is urgently needed. In the study, the virulence and tissue distribution of B.1.351 and GD108 were comprehensively studied in NHPs. We concluded that the B.1.351 strain was more virulent but exhibited less viral shedding than the latter. This study provides a basis for determining the pathogenic characteristics of SARS-CoV-2 and establishes an applicable animal model for evaluating the efficacy and safety of vaccines and drugs.

3.
Journal of Child & Adolescent Trauma ; : 1-10, 2022.
Article in English | MEDLINE | ID: covidwho-2014628

ABSTRACT

Children are more likely to experience maltreatment and parental conflict in a pandemic context, which can exacerbate their vulnerability to psychological disorders. The purpose of the present study was to examine mental health symptoms in children aged 0 to 10 years and consider related factors from the perspectives of maltreatment and parental conflict during the COVID-19 lockdown. Participants were 1286 parents aged 18 years and over with children aged 0 to 10 years were included. Several multivariable linear regressions were used to analyze the data. The largest variance in child mental health was explained by child maltreatment, as more maltreatment predicted higher reported psychological problems (standardized beta = 0.49, P < 0.001). Comparatively, parental conflict predicted less variance in mental health problems than maltreatment (standardized beta = 0.18, P < 0.001). Children who experienced more maltreatment experience and exposure to COVID-19 showed elevated levels of mental health symptoms (standardized beta = 0.06, p < 0.05), as did those who experienced parental conflict and pandemic exposure (standardized beta = 0.06, p < 0.05). The findings highlight that tailored programs that focus on a healthy family environment and strategic parental support services may be particularly effective in reducing children's mental health problems due to COVID-19 exposure.

4.
Viruses ; 14(8), 2022.
Article in English | MEDLINE | ID: covidwho-2010309

ABSTRACT

Porcine viral diarrhea diseases affect the swine industry, resulting in significant economic losses. Porcine epidemic diarrhea virus (PEDV) genotypes G1 and G2, and groups A and C of the porcine rotavirus, are major etiological agents of severe gastroenteritis and profuse diarrhea, particularly among piglets, with mortality rates of up to 100%. Based on the high prevalence rate and frequent co-infection of PEDV, RVA, and RVC, close monitoring is necessary to avoid greater economic losses. We have developed a multiplex TaqMan probe-based real-time PCR for the rapid simultaneous detection and differentiation of PEDV subtypes G1 and G2, RVA, and RVC. This test is highly sensitive, as the detection limits were 20 and 100 copies/μL for the G1 and G2 subtypes of PEDV, respectively, and 50 copies/μL for RVA and RVC, respectively. Eighty-eight swine clinical samples were used to evaluate this new test. The results were 100% in concordance with the standard methods. Since reassortment between porcine and human rotaviruses has been reported, this multiplex test not only provides a basis for the management of swine diarrheal viruses, but also has the potential to impact public health as well.

5.
BMC Health Serv Res ; 22, 2022.
Article in English | PMC | ID: covidwho-2009395

ABSTRACT

Objective: This study aimed to explore the causes and factors behind medical disputes that occurred across eight hospitals in Shanghai over a three-year period (January 2018 to December 2020), thus providing targeted suggestions for amelioration. Methods: Stratified sampling was employed to collect 561 cases in which medical disputes occurred at two tertiary hospitals, two secondary hospitals, and four primary hospitals in Shanghai. The causes were analyzed using descriptive statistics, while the factors affecting the dispute level (i.e., 1 through 4, with 1 being most severe) were analyzed via one-way ANOVA and logistic regression analyses.  Results: Doctors and patients variously contributed to the medical disputes;86.1% were related to doctors, while 13.9% were related to patients. For doctors, there are seventeen factors that influenced medical disputes. In particular, the insufficient communication (28.82%) is the most prominent factor in the doctors’ factors. For patients, there are seven factors that influenced medical disputes. In particular, the misunderstanding of medical behavior (43.48%) is the most prominent factor in the patients’ factors. Of all investigated medical disputes, 406 were level 4 (78%), 95 were level 3 (18%), and 19 were level 2 (4%);there were no level 1 disputes. The reasons for different level placements included the disease classification, treatment effect, diagnosis and treatment regulation violations by doctors, and low technical levels. Conclusions: In addition to strengthening training about clinical and communication skills, the hospitals should establish quality control mechanisms for case records and construct rapid, standardized referral mechanisms. The doctors should attach great importance to the quality and urgency of treatment given to critically ill patients, who must be informed about their prognoses in a timely manner to avoid medical disputes and physical deterioration. The patients should actively cooperate with their doctors in the treatment process, moderate any unrealistic expectations that patients may have about the outcomes. During the COVID-19 pandemic particularly, doctors and patients should strengthen empathy and mutual trust more, then defeat disease together. Supplementary Information: The online version contains supplementary material available at 10.1186/s12913-022-08490-5.

6.
14th International Conference on Machine Learning and Computing, ICMLC 2022 ; : 455-460, 2022.
Article in English | Scopus | ID: covidwho-1932812

ABSTRACT

The COVID-19 infections segmentation is a challenging task due to the high variation in shape, size and position of infections or lesions in medical images. To solve it, we propose a deep learning-based segmentation method for COVID-19 chest CT images that can automatically segment COVID-19 lung lesions. Based on the U-Net model, we introduce a feature fusion and an attention block for increasing the multi-scale feature learning capacity. Moreover, the network is also equipped with a residual block and a deep supervision mechanism to improve model segmentation accuracy and completeness rate. Experimental results show that the method has a good test effect after training, and the Dice index can reach 63.26%, which is beneficial for the diagnosis of the coronary pneumonia. © 2022 ACM.

7.
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice ; 42(6):1678-1693, 2022.
Article in Chinese | Scopus | ID: covidwho-1924681

ABSTRACT

Since December 2019, COVID-19 epidemic is continuing to spread globally. It not only jeopardizing the lives and health of people around the world seriously and putting a severe test on the public medical and health system, but also causes a huge impact on economic and trade activities and has a deep influence on the international community. In order to help researchers and policy makers understand the mechanism of virus transmission and adopt reasonable anti-epidemic policies to inhibit the further spread of the virus, some studies have adopted mathematical prediction models to simulate the spread of the virus and the development of the epidemic. However, the existing research has certain limitations, such as single method selection, excessive reliance on model parameters selection, and virus transmission and policy adjustments caused time variability of data. To solve the above problems, this paper proposes a comprehensive ensemble forecasting framework, which bases on six single prediction models, including time-varying Jackknife model averaging (TVJMA), time-varying parameters (TVP), time-varying parameter SIR (vSIR), logistic regression (LR), polynomial regression (PNR), autoregressive moving average (ARMA). The proposed method is used to predict the cumulative number of confirmed cases in the 6 most severely affected countries in different regions. Empirical results show that for a single prediction method, the TVJMA method outperforms the other five methods;the comprehensive ensemble forecasting method is significantly better than any single method in most cases, especially, the multi-model combined forecasting method based on error correction weights improves the prediction accuracy significantly. For different prediction steps, the comprehensive ensemble forecasting method is robust. © 2022, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.

8.
Journal of Resources and Ecology ; 13(4):679-686, 2022.
Article in English | Scopus | ID: covidwho-1912030

ABSTRACT

Resilience has become an important concept for the ski resorts of China, which have suffered heavy losses due to COVID-19. In order to help China’s ski resort service industry successfully adapt to the crisis and achieve sustainable development, the goal of this paper is to develop the definition of resilience of the ski resort service industry through interviews based on the concept and general analysis framework of resilience. The ski resort resilience theory analysis framework is then constructed from the three basic elements (market, skiing, and stakeholders) and four system features (flexibility, adaptability, and collaborative learning ability). The results indicate several measures that can be taken to spread risk: enrich the product supply;eliminate risks and build a multi-agent networked industrial governance system;and establish a risk prevention and management mechanism based on a multi-organization alternative learning mechanism to overcome the difficulties encountered in the development of ski resorts. © 2022, Editorial office of Journal of Resources and Ecology. All rights reserved.

9.
Nature Food ; 3(5):325-330, 2022.
Article in English | Web of Science | ID: covidwho-1886238

ABSTRACT

The COVID-19 pandemic has curtailed lives and livelihoods, leading to price spikes for some foods and declines for others. We compare monthly retail food prices in up to 181 countries from January 2019 to June 2021, test for differences over time and find that average prices rose significantly, especially for more nutritious food groups in countries with higher COVID-19 case counts. Analysis of retail prices by food group complements data on farm commodity prices and overall consumer price indexes, helping to guide policy for resilience and response to shocks. Price fluctuations associated with the COVID-19 pandemic have been key determinants of food security in the recent past. A comparison of monthly retail prices in 181 countries from January 2019 to June 2021 reveals which regions and food items have been most affected.

10.
Ieee Journal of Selected Topics in Signal Processing ; 16(2):261-275, 2022.
Article in English | English Web of Science | ID: covidwho-1883128

ABSTRACT

The fast transmission rate of COVID-19 worldwide has made this virus the most important challenge of year 2020. Many mitigation policies have been imposed by the governments at different regional levels (country, state, county, and city) to stop the spread of this virus. Quantifying the effect of such mitigation strategies on the transmission and recovery rates, and predicting the rate of new daily cases are two crucial tasks. In this paper, we propose a hybrid modeling framework which not only accounts for such policies but also utilizes the spatial and temporal information to characterize the pattern of COVID-19 progression. Specifically, a piecewise susceptible-infected-recovered (SIR) model is developed while the dates at which the transmission/recover rates change significantly are defined as "break points" in this model. A novel and data-driven algorithm is designed to locate the break points using ideas from fused lasso and thresholding. In order to enhance the forecasting power and to describe additional temporal dependence among the daily number of cases, this model is further coupled with spatial smoothing covariates and vector auto-regressive (VAR) model. The proposed model is applied to several U.S. states and counties, and the results confirm the effect of "stay-at-home orders" and some states' early "re-openings" by detecting break points close to such events. Further, the model provided satisfactory short-term forecasts of the number of new daily cases at regional levels by utilizing the estimated spatio-temporal covariance structures. They were also better or on par with other proposed models in the literature, including flexible deep learning ones. Finally, selected theoretical results and empirical performance of the proposed methodology on synthetic data are reported which justify the good performance of the proposed method.

11.
Journal of Sport & Exercise Psychology ; 44:S64-S65, 2022.
Article in English | English Web of Science | ID: covidwho-1879963
12.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(5): 659-667, 2022 May 06.
Article in Chinese | MEDLINE | ID: covidwho-1875840

ABSTRACT

Coronavirus disease 19 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 has spread all over the world. Streptococcus pneumoniae as a common pathogen of community-acquired pneumonia shares similar high-risk susceptible populations with COVID-19. Streptococcus pneumoniae co-infection is a key risk factor for severe COVID-19 and death. Pneumococcal vaccination has a beneficial impact on reducing the incidence and mortality of COVID-19. The vaccination rate of streptococcus pneumoniae is still low in China. Streptococcus pneumoniae vaccination may be one of effective strategies in the management of COVID-19 for high-risk population such as the elderly and those who have underlying chronic diseases.


Subject(s)
COVID-19 , Coinfection , Pneumococcal Infections , Aged , Humans , Pneumococcal Infections/prevention & control , Streptococcus pneumoniae , Vaccination
13.
2022 International Conference on Big Data, Information and Computer Network, BDICN 2022 ; : 128-131, 2022.
Article in English | Scopus | ID: covidwho-1846057

ABSTRACT

The outbreak of COVID-19 not only affects people's health, but also hinders the pace of economic progress of various countries. Our goal was to develop a prediction model based on machine learning, which could be used to predict development trend of COVID-19 in the future. It can provide governments and health authorities with useful information conducive to decision-making. Considering that the propagation of COVID-19 is affected by many factors and a single prediction model lacks all-round monitoring of the data set, the ARIMA-SVM integration model was established by using the global cumulative number of confirmed cases. The individual models of ARIMA and SVM were used to predict the COVID-19 trend. Based on the prediction results of the above prediction model, a new integration forecast model was formed through a combination of weighted weights. Finally, the forecast results of the combined model and the individual model were compared. The prediction performance of models were compared according to Mean Absolute Percentage Error (MAPE). The prediction results showed that the MAPE values of ARIMA model, SVM model and ARIMA-SVM integration model were 15.843%, 1.251%, 1.132% respectively. Compared with the traditional machine learning models ARIMA and SVM, the combined model has reduced the average absolute error percentage by 92.103% and 9.51%, respectively, and can achieve more accurate and reliable COVID-19 trend prediction. It used two single models to complement each other, reduced the systematic error of the prediction model, and significantly improved the prediction effect. © 2022 IEEE.

14.
Asian Journal of Organic Chemistry ; 2022.
Article in English | Scopus | ID: covidwho-1825833

ABSTRACT

A sequential protocol of α-diazophosphonates with isatins to access a series of α-diazo-β-hydroxyphosphonate derivatives via the inorganic base catalysis was reported. The resulting α-diazo-β-hydroxyphosphonates could then be readily transformed to 4-phosphonylated-3-hydroxyquinolin-2(1H)-ones with moderate to excellent yields through a catalyst-free regioselective ring-expansion rearrangement. Control experiment demonstrates that intramolecular cyclization pathway is more reasonable for the ring-expansion process. In addition, a benzo[b]thiophene-derived isatin featured with the inhibition of SARS-CoV Mpro was also suitable for this transformation and generated the corresponding scaffolds with potential anti-virus activities for further development. © 2022 Wiley-VCH GmbH.

15.
Frontiers in Physics ; 10, 2022.
Article in English | Scopus | ID: covidwho-1785394

ABSTRACT

Given the worldwide pandemic of the novel coronavirus disease 2019 (COVID-19) and its continuing threat brought by the emergence of virus variants, there are great demands for accurate surveillance and monitoring of outbreaks. A valuable metric for assessing the current risk posed by an outbreak is the time-varying reproduction number ((Formula presented.)). Several methods have been proposed to estimate (Formula presented.) using different types of data. We developed a new tool that integrated two commonly used approaches into a unified and user-friendly platform for the estimation of time-varying reproduction numbers. This tool allows users to perform simulations and yield real-time tracking of local epidemic of COVID-19 with an R package. Copyright © 2022 Liu, Xu, Bai, Xu, Lau, Cowling and Du.

16.
Frontiers in Physics ; 10:5, 2022.
Article in English | Web of Science | ID: covidwho-1686526

ABSTRACT

We present an R package developed to quantify coronavirus disease 2019 (COVID-19) importation risk. Quantifying and visualizing the importation risk of COVID-19 from inbound travelers is urgent and imperative to trigger public health responses, especially in the early stages of the COVID-19 pandemic and emergence of new SARS-CoV-2 variants. We provide a general modeling framework to estimate COVID-19 importation risk using estimated pre-symptomatic prevalence of infection and air traffic data from the multi-origin places. We use Hong Kong as a case study to illustrate how our modeling framework can estimate the COVID-19 importation risk into Hong Kong from cities in Mainland China in real time. This R package can be used as a complementary component of the pandemic surveillance system to monitor spread in the next pandemic.

17.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-296526

ABSTRACT

Omicron, a fast-spreading SARS-CoV-2 variant of concern reported to the World Health Organization on November 24, 2021, has raised international alarm. We estimated there is at least 50% chance that Omicron had been introduced by travelers from South Africa into all of the 30 countries studied by November 27, 2021.

18.
Kexue Tongbao/Chinese Science Bulletin ; 66(31):3925-3931, 2021.
Article in Chinese | Scopus | ID: covidwho-1523391

ABSTRACT

Left unmitigated, climate change poses a catastrophic risk to human health, demanding an urgent and concerted response from every country. The 2015 Lancet Commission on Health and Climate Change and The Lancet Countdown: Tracking Progress on Health and Climate Change have been initiated to map out the impacts of climate change and the necessary policy responses. To meet these challenges, Tsinghua University, partnering with the University College London and 17 Chinese and international institutions, has prepared the Chinese Lancet Countdown report, which has a national focus and builds on the work of the global Lancet Countdown: Tracking Progress on Health and Climate Change. Drawing on international methodologies and frameworks, this report aims to deepen the understanding of the links between public health and climate change at the national level and track them with 23 indicators. This work is part of the Lancet's Countdown broader efforts to develop regional expertise on this topic, and coincides with the launch of the Lancet Countdown Regional Centre in Asia, based at Tsinghua University. The data and results of this report are presented at the provincial level, where possible, to facilitate targeted response strategies for local decision-makers. Based on the data and findings of the 2020 Chinese Lancet Countdown report, five recommendations are proposed to key stakeholders in health and climate change in China: (1) Enhance inter-departmental cooperation. Climate change is a challenge that demands an integrated response from all sectors, urgently requiring substantial inter-departmental cooperation among health, environment, energy, economic, financial, and education authorities. (2) Strengthen health emergency preparedness. Knowledge and findings on current and future climate-related health threats still lack the required attention and should be fully integrated into the emergency preparedness and response system. (3) Support research and raise awareness. Additional financial support should be allocated to health and climate change research in China to enhance health system adaptation, mitigation measures, and their health benefits. At the same time, media and academia should be fully motivated to raise the public and politicians' awareness of this topic. (4) Increase climate change mitigation. Speeding up the phasing out of coal is necessary to be consistent with China's pledge to be carbon neutral by 2060 and to continue to reduce air pollution. Fossil fuel subsidies must also be phased out. (5) Ensure the recovery from COVID-19 to protect health now and in the future. China's efforts to recover from COVID-19 will shape public health for years to come. Climate change should be a priority in these interventions. © 2021, Science Press. All right reserved.

19.
Chinese Journal of Applied Clinical Pediatrics ; 36(18):1368-1372, 2021.
Article in Chinese | Scopus | ID: covidwho-1481061

ABSTRACT

Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still worldwide.As a vulnerable group, severe and dead pediatric cases are also reported.Under this severe epidemic situation, children should be well protected.With the widespread vaccination of SARS-CoV-2 vaccine in adults, the infection rate have decreased.Therefore, SARS-CoV-2 vaccine inoculation for children groups step by step is of great significance to the protection of children and the prevention and control of corona virus disease 2019(COVID-19) as a whole.But the safety of children vaccinated with SARS-CoV-2 vaccine is a main concern of parents.Therefore, in order to ensure the safety of vaccination and the implementation of vaccination work, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health and the Society of Pediatrics, Chinese Medical Association organized experts to interpret the main issue of parents about SARS-CoV-2 vaccine for children, in order to answer the doubts of parents. Copyright © 2021 by the Chinese Medical Association.

20.
Chinese Journal of Applied Clinical Pediatrics ; 36(18):1361-1367, 2021.
Article in Chinese | Scopus | ID: covidwho-1481060

ABSTRACT

At present, severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still rampant worldwide.As of September 10, 2021, there were about 222 million confirmed cases of corona virus disease 2019(COVID-19)and more than 4.6 million deaths worldwide.With the development of COVID-19 vaccines and the gradual vaccination worldwide, the increasing number of cases in children and unvaccinated young people has drawn attention.According to World Health Organization surveillance data, the proportion of COVID-19 infection cases in children gradually increased, and the proportion of cases in the age groups of under 5 years and 5-14 years increased from 1.0% and 2.5% in January 2020 to 2.0% and 8.7% in July 2021, respectively.At present, billions of adults have been vaccinated with various COVID-19 vaccines worldwide, and their protective effects including reducing infection and transmission, reducing severe disease and hospitalization, and reducing death, as well as high safety have been confirmed.Canada, the United States, Europe and other countries have approved the emergency COVID-19 vaccination in children and adolescents aged 12 to 17 years, and China has also approved the phased vaccination of COVID-19 vaccination in children and adolescents aged 3 to 17 years. For smooth advancement and implementation of COVID-19 vaccination in children, academic institutions, including National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, and The Society of Pediatrics, Chinese Medical Association organized relevant experts to reach this consensus on COVID-19 vaccination in children. Copyright © 2021 by the Chinese Medical Association.

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