Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 122
Filter
1.
Environmental Pollution ; : 119420, 2022.
Article in English | ScienceDirect | ID: covidwho-1819485

ABSTRACT

China was seriously affected by air pollution in the past decade, especially for particulate matter (PM) and emerging ozone pollution recently. In this study, we systematically examined the spatiotemporal variations of six air pollutants and conducted ozone prediction using machine learning (ML) algorithms in the Beijing-Tianjin-Hebei (BTH) region. The annual-average concentrations of CO, PM10, PM2.5 and SO2 decreased at a rate of 141, 11.0, 6.6 and 5.6 μg/m3/year, while a pattern of initial increase and later decrease was observed for NO2 and O3_8 h. The concentration of SO2, CO and NO2 was higher in Tangshan and Xingtai, while northern BTH region has lower levels of CO, NO2 and PM. Spatial variations of ozone were relatively small in the BTH region. Monthly variations of PM10 displayed an increase in March probably due to wind-blown dusts from Northwest China. A seasonal and diurnal pattern with summer and afternoon peaks was found for ozone, which was contrast with other pollutants. Further ML algorithms such as Random Forest (RF) model and Decision tree (DT) regression showed good ozone prediction performance (daily: R2 = 0.83 and 0.73, RMSE = 30.0 and 37.3 μg/m3, respectively;monthly: R2 = 0.93 and 0.88, RMSE = 12.1 and 15.8 μg/m3, respectively) based on 10-fold cross-validation. Both RF model and DT regression relied more on the spatial trend as higher temporal prediction performance was achieved. Solar radiation- and temperature-related variables presented high importance at daily level, whereas sea level pressure dominated at monthly level. The spatiotemporal heterogeneity in variable importance was further confirmed using case studies based on RF model. In addition, variable importance was possibly influenced by the emission reductions due to COVID-19 pandemic. Despite its possible weakness to capture ozone extremes, RF model was beneficial and suggested for predicting spatiotemporal variations of ozone in future studies.

2.
Journal of Infection and Public Health ; 2022.
Article in English | ScienceDirect | ID: covidwho-1814760

ABSTRACT

Background Despite substantial resources deployed to curb SARS-CoV-2 transmission, controlling the COVID-19 pandemic has been a major challenge. New variants of the virus are frequently emerging leading to new waves of infection and re-introduction of control measures. In this study, we assessed the effectiveness of containment strategies implemented in the early phase of the pandemic. Methods Real-world data for COVID-19 cases was retrieved for the period Jan 1 to May 1, 2020 from a number of different sources, including PubMed, MEDLINE, Facebook, Epidemic Forecasting and Google Mobility Reports. We analyzed data for 18 countries/regions that deployed containment strategies such as travel restrictions, lockdowns, stay-at-home requests, school/public events closure, social distancing, and exposure history information management (digital contact tracing, DCT). Primary outcome measure was the change in the number of new cases over 30 days before and after deployment of a control measure. We also compared the effectiveness of centralized versus decentralized DCT. Time series data for COVID-19 were analyzed using Mann-Kendall (M-K) trend tests to investigate the impact of these measures on changes in the number of new cases. The rate of change in the number of new cases was compared using M-K z-values and Sen’s slope. Results In spite of the widespread implementation of conventional strategies such as lockdowns, travel restrictions, social distancing, school closures, and stay-at-home requests, analysis revealed that these measures could not prevent the spread of the virus. However, countries which adopted DCT with centralized data storage were more likely to contain the spread. Conclusions Centralized DCT was more effective in containing the spread of COVID-19. Early implementation of centralized DCT should be considered in future outbreaks. However, challenges such as public acceptance, data security and privacy concerns will need to be addressed.

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331212

ABSTRACT

Background Evidence to date has shown that inequality in health, and vaccine coverage in particular, can have ramifications to wider society. However, whilst individual studies have sought to characterise these heterogeneities in immunisation coverage at national level, few have taken a broad and quantitative view of the contributing factors to heterogeneity in vaccine coverage and impact. This systematic review aims to highlight these geographic, demographic, and sociodemographic characteristics through a qualitative and quantitative approach, vital to prioritise and optimise vaccination policies. Methods A systematic review of two databases (PubMed and Web of Science) was undertaken using Medical Subject Headings (MeSH) and keywords to identify studies examining factors on vaccine inequality and heterogeneity in vaccine coverage. Inclusion criteria were applied independently by two researchers. Studies including data on key characteristics of interest were further analysed through a meta-analysis to produce a pooled estimate of the risk ratio using a random effects model for that characteristic. Results One hundred and eight studies were included in this review. We found that inequalities in wealth, education, and geographic access can affect vaccine impact and vaccine dropout. We estimated those living in rural areas were not significantly different in terms of full vaccination status compared to urban areas but noted considerable heterogeneity between countries. We found that females were 3% (95%CI[1%, 5%]) less likely to be fully vaccinated than males. Additionally, we estimated that children whose mothers had no formal education were 28% (95%CI[18%,47%]) less likely to be fully vaccinated than those whose mother had primary level, or above, education. Finally, we found that individuals in the poorest wealth quintile were 27% (95%CI [16%,37%]) less likely to be fully vaccinated than those in the richest. Conclusions We found a nuanced picture of inequality in vaccine coverage and access with wealth disparity dominating, and likely driving, other disparities. This review highlights the complex landscape of inequity and further need to design vaccination strategies targeting missed subgroups to improve and recover vaccination coverage following the COVID-19 pandemic. Registration Prospero CRD42021261927

4.
Int J Infect Dis ; 118: 203-210, 2022 Mar 04.
Article in English | MEDLINE | ID: covidwho-1768175

ABSTRACT

OBJECTIVES: This study aims to examine and explain the differences at city level in cumulative COVID-19 cases and time from first to last infection during the first 6 weeks of the epidemic in China. METHODS: A quantitative study is conducted in China based on the multisource spatial data of 315 Chinese cities. Firstly, the spatial discrepancy of COVID-19 transmission was examined based on spatial autocorrelation analysis and hot pot analysis. Next, a comprehensive indicator framework was established by including a wide range of factors such as human mobility, geographical features, public health measures, and residents' awareness. Finally, multivariate regression models using these variables were constructed to identify the determinants of COVID-19 transmission. RESULTS: Significant spatial discrepancy of transmission was proved, and 10 determinants were identified. CONCLUSIONS: The transmission consequence (measured by the number of cumulative cases) was mostly correlated with the migration scale from Wuhan, followed by socioeconomic factors. Transmission duration (measured as the time from the first to last case within the city) was mostly determined by total migration scale and lockdown speed, which suggests that timely implementation of public health measures facilitated fast control of transmission. Residents' attention to COVID-19 was proved to be not only helpful for reducing confirmed cases, but also in favor of rapid transmission control. Altitude produced slight but significant effect on transmission duration. These conclusions are expected to provide decision support for the local governments of China and other jurisdictions.

5.
Front Cell Infect Microbiol ; 12: 802147, 2022.
Article in English | MEDLINE | ID: covidwho-1753359

ABSTRACT

Owing to the outbreak of the novel coronavirus (SARS-CoV-2) worldwide at the end of 2019, the development of a SARS-CoV-2 vaccine became an urgent need. In this study, we developed a type 9 adeno-associated virus vectored vaccine candidate expressing a dimeric receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S protein) and evaluated its immunogenicity in a murine model. The vaccine candidate, named AAV9-RBD virus, was constructed by inserting a signal peptide to the N-terminus of two copies of RBD, spaced by a linker, into the genome of a type 9 adeno-associated virus. In vitro assays showed that HeLa cells infected by the recombinant AAV virus expressed high levels of the recombinant RBD protein, mostly found in the cell culture supernatant. The recombinant AAV9-RBD virus was cultured and purified. The genome titer of the purified recombinant AAV9-RBD virus was determined to be 2.4 × 1013 genome copies/mL (GC/mL) by Q-PCR. Balb/c mice were immunized with the virus by intramuscular injection or nasal drip administration. Eight weeks after immunization, neutralizing antibodies against the new coronavirus pseudovirus were detected in the sera of all mice; the mean neutralizing antibody EC50 values were 517.7 ± 292.1 (n=10) and 682.8 ± 454.0 (n=10) in the intramuscular injection group and nasal drip group, respectively. The results of this study showed that the recombinant AAV9-RBD virus may be used for the development of a SARS-CoV-2 vaccine.


Subject(s)
COVID-19 Vaccines , COVID-19 , Animals , COVID-19/prevention & control , Dependovirus/genetics , HeLa Cells , Humans , Mice , Mice, Inbred BALB C , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus
6.
World journal of psychiatry ; 12(2):338-347, 2022.
Article in English | EuropePMC | ID: covidwho-1749852

ABSTRACT

BACKGROUND Frontline nurses in Wuhan directly fighting severe acute respiratory syndrome coronavirus-2 diseases are at a high risk of infection and are extremely susceptible to psychological stress, especially due to the global coronavirus disease 2019 (COVID-19) pandemic. The psychological after-effects of this public health emergency on frontline nurses will last for years. AIM To assess factors influencing post-traumatic stress disorder (PTSD) among frontline nurses in Wuhan 6 mo after the COVID-19 pandemic began. METHODS A total of 757 frontline nurses from five hospitals in Wuhan, China, participated in an online survey from July 27 to August 13, 2020. This cross-sectional online study used a demographic information questionnaire, the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders, the Connor-Davidson Resilience Scale, and the Patient Health Questionnaire-4. The chi-square test and logistic regression were used to analyze the association of demographics, COVID-19-related variables, and PTSD. Logistic regression was also conducted to investigate which variables were associated with PTSD outcomes. RESULTS A total of 13.5%, 24.3%, and 21.4% of the frontline nurses showed symptoms of PTSD, depression, and anxiety, respectively. The multivariate logistic regression analysis showed that the following factors were strongly associated with PTSD: Having a relative, friend, or colleague who died of COVID-19;experiencing stigma;or having psychological assistance needs, depressive symptoms or anxiety. Showing resilience and receiving praise after the COVID-19 outbreak were protective factors. CONCLUSION Frontline nurses still experienced PTSD (13.5%) six months after the COVID-19 outbreak began. Peer support, social support, official recognition, reward mechanisms, exercise, better sleep, and timely provision of information (such as vaccine research progress) by the government via social media, and adequate protective supplies could mitigate the level of PTSD among nurses responding to COVID-19. Stigmatization, depression, and anxiety might be associated with a greater risk of PTSD among nurses.

7.
International Journal of Hospitality Management ; 103:103200, 2022.
Article in English | ScienceDirect | ID: covidwho-1729817

ABSTRACT

With a longitudinal dataset merging hotel performance and guest survey insights, this study examines the impact of hotel occupancy rates on the guest experience. Findings revealed a non-constant effect of hotel occupancy on the guest experience. Specifically, at low occupancy levels, the hotel occupancy rate was positively related to the overall guest experience due to an improvement in the environmental vibe. Conversely, at high occupancy levels, the hotel occupancy rate was negatively related to the overall guest experience, as high occupancy diminished guest experiences’ during service interactions. Findings from this research make notable contributions to theory, presenting a fuller account of the complex relationship between hotel occupancy on the guest experience. In addition, these results are practically relevant, shedding light on how hotels can prepare for the post-COVID occupancy rebound.

8.
Front Cell Neurosci ; 16: 831977, 2022.
Article in English | MEDLINE | ID: covidwho-1715021

ABSTRACT

Microglia are intrinsic immune cells of the central nervous system and play a dual role (pro-inflammatory and anti-inflammatory) in the homeostasis of the nervous system. Neuroinflammation mediated by microglia serves as an important stage of ischemic hypoxic brain injury, cerebral hemorrhage disease, neurodegeneration and neurotumor of the nervous system and is present through the whole course of these diseases. Microglial membrane protein or receptor is the basis of mediating microglia to play the inflammatory role and they have been found to be upregulated by recognizing associated ligands or sensing changes in the nervous system microenvironment. They can then allosterically activate the downstream signal transduction and produce a series of complex cascade reactions that can activate microglia, promote microglia chemotactic migration and stimulate the release of proinflammatory factor such as TNF-α, IL-ß to effectively damage the nervous system and cause apoptosis of neurons. In this paper, several representative membrane proteins or receptors present on the surface of microglia are systematically reviewed and information about their structures, functions and specific roles in one or more neurological diseases. And on this basis, some prospects for the treatment of novel coronavirus neurological complications are presented.

9.
Environ Int ; 162: 107153, 2022 04.
Article in English | MEDLINE | ID: covidwho-1706132

ABSTRACT

Since December 2019, coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a great challenge to the world's public health system. Nosocomial infections have occurred frequently in medical institutions worldwide during this pandemic. Thus, there is an urgent need to construct an effective surveillance and early warning system for pathogen exposure and infection to prevent nosocomial infections in negative-pressure wards. In this study, visualization and construction of an infection risk assessment of SARS-CoV-2 through aerosol and surface transmission in a negative-pressure ward were performed to describe the distribution regularity and infection risk of SARS-CoV-2, the critical factors of infection, the air changes per hour (ACHs) and the viral variation that affect infection risk. The SARS-CoV-2 distribution data from this model were verified by field test data from the Wuhan Huoshenshan Hospital ICU ward. ACHs have a great impact on the infection risk from airborne exposure, while they have little effect on the infection risk from surface exposure. The variant strains demonstrated significantly increased viral loads and risks of infection. The level of protection for nurses and surgeons should be increased when treating patients infected with variant strains, and new disinfection methods, electrostatic adsorption and other air purification methods should be used in all human environments. The results of this study may provide a theoretical reference and technical support for reducing the occurrence of nosocomial infections.


Subject(s)
COVID-19 , SARS-CoV-2 , Aerosols , Humans , Patient Isolators , Risk Assessment
10.
Applied Research in Quality of Life ; : 1-26, 2022.
Article in English | EuropePMC | ID: covidwho-1695362

ABSTRACT

Since the early days of COVID-19, university teaching has changed from face-to-face format to online mode. With the gradual containment of the pandemic, there is no need for school lockdown. As a result, the teaching format has changed to HyFlex mode integrating both face-to-face and online modes. Obviously, it is necessary to understand the academic quality of life among students under the Hyflex teaching mode. In this paper, we report an evaluation study on a leadership subject in Hong Kong delivered via HyFlex teaching using a post-lecture evaluation strategy. In one of the lectures, we covered law-abiding leadership in university students, including abiding by the Hong Kong National Security Law. The post-lecture evaluation showed that students generally held positive views toward the HyFlex teaching and they perceived that the subject promoted their well-being indexed by psychosocial competence. Regarding the lecture on law-abiding leadership, students agreed that the lecture promoted their psychosocial competence, personal development, knowledge about law-abiding behavior and national security (including the Hong Kong National Security Law), and readiness to serve as socially responsible leaders. Positive perceptions of the lecture design, teacher performance, lecture content of law-abiding leadership and national security, and benefits positively predicted students’ overall satisfaction with the lecture on law-abiding leadership and national security.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325304

ABSTRACT

In recent years, deep learning-based image analysis methods have been widely applied in computer-aided detection, diagnosis and prognosis, and has shown its value during the public health crisis of the novel coronavirus disease 2019 (COVID-19) pandemic. Chest radiograph (CXR) has been playing a crucial role in COVID-19 patient triaging, diagnosing and monitoring, particularly in the United States. Considering the mixed and unspecific signals in CXR, an image retrieval model of CXR that provides both similar images and associated clinical information can be more clinically meaningful than a direct image diagnostic model. In this work we develop a novel CXR image retrieval model based on deep metric learning. Unlike traditional diagnostic models which aims at learning the direct mapping from images to labels, the proposed model aims at learning the optimized embedding space of images, where images with the same labels and similar contents are pulled together. It utilizes multi-similarity loss with hard-mining sampling strategy and attention mechanism to learn the optimized embedding space, and provides similar images to the query image. The model is trained and validated on an international multi-site COVID-19 dataset collected from 3 different sources. Experimental results of COVID-19 image retrieval and diagnosis tasks show that the proposed model can serve as a robust solution for CXR analysis and patient management for COVID-19. The model is also tested on its transferability on a different clinical decision support task, where the pre-trained model is applied to extract image features from a new dataset without any further training. These results demonstrate our deep metric learning based image retrieval model is highly efficient in the CXR retrieval, diagnosis and prognosis, and thus has great clinical value for the treatment and management of COVID-19 patients.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325193

ABSTRACT

Objectives: To investigated the relationship between the neutrophil-to-lymphocyte ratio (NLR) and the severity of lung injury in corona virus disease 2019 (COVID-19) patients.Methods The clinical data, laboratory examination, and chest computed tomography (CT) findings of 167 patients with confirmed COVID-19 admitted to 5 hospitals in Chongqing, China from January 2020 to February 2020 were retrospectively reviewed. According to the diagnostic criteria sixth edition of the “Diagnosis and Treatment of New Coronavirus Pneumonitis” published by the China National Health Commission, the patients were stratified by the severity of their illness to 3 groups: mild (n = 17), moderate (n = 119), or severe (n = 31).Results Differences of the NLR among the three groups and between each of the groups were significant (all p < 0.001). The NLR and CT severity score were positively correlated (r = 0.823, p < 0.001). Receiver operating characteristic (ROC) curve analysis found that NLR had diagnostic and prognostic value in COVID-19 patients with either negative or positive CT results. The area under curve (AUC) was 0.819 (95% CI: 0.729-0.910, p < 0.001), the sensitivity was 61.3%, specificity was 94.1%, and the optimal NLR cutoff value was 3.634.Conclusion NLR reflected the degree of lung injury and predicted the progression of COVID-19. NLR is a low-cost, convenient, bedside alternative to chest CT scanning to indicate the severity of lung injury in patients with COVID-19, especially in relatively underdeveloped areas.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324780

ABSTRACT

Two typical features of uncontrolled inflammation, cytokine storm and lymphopenia, are associated with the severity of coronavirus disease 2019 (COVID-19), demonstrating that both innate and adaptive immune responses are involved in the development of this disease. Recent studies have explored the contribution of innate immune cells to the pathogenesis of the infection. However, the impact of adaptive immunity on this disease remains unknown. In order to clarify the role of adaptive immune response in COVID-19, we characterized the phenotypes of lymphocytes in PBMCs from patients at different disease stages using single-cell RNA sequencing (scRNA-seq) technology. Dynamics of the effector cell levels in lymphocytes revealed a distinct feature of adaptive immunity in severely affected patients, the coincidence of impaired cellular and enhanced humoral immune responses, suggesting that dysregulated adaptive immune responses advanced severe COVID-19. Excessive activation and exhaustion were observed in CD8 T effector cells, which might contribute to the lymphopenia. Interestingly, expression of Prothymosin alpha (PTMA), the proprotein of Tα1, was significantly increased in a group of CD8 T memory stem cells, but not in excessively activated T cells. We further showed that Tα1 significantly promoted the proliferation of activated T cells in vitro and relieved the lymphopenia in COVID-19 patients. Our data suggest that protection of T cells from excessive activation might be critical for the prevention of severe COVID-19.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324235

ABSTRACT

Background: The Coronavirus Disease 2019 (COVID-19) pandemic is a world-wide health crisis. Limited information is available regarding which patients will experience more severe disease symptoms. We evaluated hospitalized patients who were initially diagnosed with moderate COVID-19 for clinical parameters and radiological feature that showed an association with progression to severe/critical symptoms. Methods: : This study, a retrospective single-center study at the Central Hospital of Wuhan, enrolled 243 patients with confirmed COVID­19 pneumonia. Forty of these patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory, and radiological data were extracted from electronic medical records and compared between moderate- and severe/critical-type symptoms. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression. Results: : Patients with severe/critical symptoms were older (p<0.001) and more often male (p=0.046). A combination of chronic obstructive pulmonary disease (COPD) and high maximum chest computed tomography (CT) score was associated with disease progression. Maximum CT score (>11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve was 0.861 ( 95% confidence interval: 0.811-0.902). Conclusions: : Maximum CT score and COPD were associated with patient deterioration. Maximum CT score (>11) was associated with severe illness.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312752

ABSTRACT

Background: In this COVID-19 pandemic, the differential diagnosis of different viral types of pneumonia is still challenging. We aimed to assess the classification performance of computed tomography (CT)-based CT signs and radiomics features for discriminating COVID-19 pneumonia and other viral pneumonia. Methods: : A total of 181 patients with confirmed viral pneumonia (COVID-19: 89 cases, Non-COVID-19: 92 cases;training cohort: 126 cases;test cohort: 55 cases) were collected retrospectively in this study. Pneumonia signs and radiomics features were extracted from the initial unenhanced chest CT images to build independent and combined models. The predictive performance of the radiomics model and the combined model were evaluated using an intra-cross validation cohort. Diagnostic performance of two models was assessed via receiver operating characteristic (ROC) analysis. Results: : The combined models consisted of 3 significant CT signs and 14 selected features and demonstrated better discrimination performance between COVID-19 and Non-COVID-19 pneumonia than the single radiomics model. For the radiomics model along, the area under the ROC curve (AUC) were 0.904 (sensitivity, 85.5%;specificity, 84.4%;accuracy, 84.9%) in the training cohort and 0.866 (sensitivity, 77.8%;specificity, 78.6%;accuracy, 78.2%) in the test cohort. After combining CT signs and radiomics features, AUC of the combined model for the training cohort was 0.956 (sensitivity, 91.9%;specificity, 85.9%;accuracy, 88.9%), while that for the test cohort was 0.943 (sensitivity, 88.9%;specificity, 85.7%;accuracy, 87.3%). Conclusion: CT-based radiomics combined with signs might be a potential method for distinguishing COVID-19 and other viral pneumonia with satisfactory performance.

16.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312744

ABSTRACT

Background: Multicenter retrospective comparison of the first high-resolution computed tomography (HRCT) findings of coronavirus disease 2019 (COVID-19) and other viral pneumonias. Methods: : We retrospectively collected clinical and imaging data from 254 cases of confirmed viral pneumonia in 20 hospitals in Yunnan Province, China, from March 1, 2015, to March 15, 2020. According to the virus responsible for the pneumonia, the pneumonias were divided into non-COVID-19 (133 cases) and COVID-19 (121 cases). The non-COVID-19 pneumonias included 3 types: cytomegalovirus (CMV) (31 cases), influenza A virus (82 cases), and influenza B virus (20 cases). The differences in the basic clinical characteristics, lesion distribution, location and imaging signs among the four viral pneumonias were analyzed and compared. Results: : Fever and cough were the most common clinical symptoms of the four viral pneumonias. Compared with the COVID-19 patients, the non-COVID-19 patients had higher proportions of fatigue, sore throat, expectorant and chest tightness (all p <0.000). In addition, in the CMV pneumonia patients, the proportion of patients with combined acquired immunodeficiency syndrome (AIDS) and leukopenia were high (all p <0.000). Comparisons of the imaging findings of the four viral pneumonias showed that pulmonary lesions of COVID-19 were more likely to occur in the peripheral and lower lobes of both lungs, while those of CMV pneumonia were diffusely distributed. Compared with the non-COVID-19 pneumonias, COVID-19 pneumonia was more likely to present as ground-glass opacity (GGO), intralobular interstitial thickening, vascular thickening and halo sign (all p <0.05). In addition, in the early stage of COVID-19, extensive consolidation, fibrous stripes, subpleural lines, crazy-paving pattern, tree-in-bud, mediastinal lymphadenectasis, pleural thickening and pleural effusion were rare (all p <0.05). Conclusion: The HRCT findings of COVID-19 pneumonia and other viral pneumonias overlapped significantly, but many important differential imaging features could still be observed.

17.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307414

ABSTRACT

COVID-19 patient triaging with predictive outcome of the patients upon first present to emergency department (ED) is crucial for improving patient prognosis, as well as better hospital resources management and cross-infection control. We trained a deep feature fusion model to predict patient outcomes, where the model inputs were EHR data including demographic information, co-morbidities, vital signs and laboratory measurements, plus patient's CXR images. The model output was patient outcomes defined as the most insensitive oxygen therapy required. For patients without CXR images, we employed Random Forest method for the prediction. Predictive risk scores for COVID-19 severe outcomes ("CO-RISK" score) were derived from model output and evaluated on the testing dataset, as well as compared to human performance. The study's dataset (the "MGB COVID Cohort") was constructed from all patients presenting to the Mass General Brigham (MGB) healthcare system from March 1st to June 1st, 2020. ED visits with incomplete or erroneous data were excluded. Patients with no test order for COVID or confirmed negative test results were excluded. Patients under the age of 15 were also excluded. Finally, electronic health record (EHR) data from a total of 11060 COVID-19 confirmed or suspected patients were used in this study. Chest X-ray (CXR) images were also collected from each patient if available. Results show that CO-RISK score achieved area under the Curve (AUC) of predicting MV/death (i.e. severe outcomes) in 24 hours of 0.95, and 0.92 in 72 hours on the testing dataset. The model shows superior performance to the commonly used risk scores in ED (CURB-65 and MEWS). Comparing with physician's decisions, CO-RISK score has demonstrated superior performance to human in making ICU/floor decisions.

18.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315872

ABSTRACT

The outbreak of COVID-19, caused by SARS-CoV-2 has spread across many countries globally. Greatly limited study concerned the effect of airborne pollutants on COVID-19 infection, while exposure to airborne pollutants may harm human health. This paper aimed to examine the associations of acute exposure to ambient atmospheric pollutants to daily newly COVID-19 confirmed cases in 41 Chinese cities. Using a generalized additive model with Poisson distribution controlling for temperature and relative humidity, we evaluated the association between pollutant concentrations and daily COVID-19 confirmation at single-city level and multi-city level. We observed a 10 μg/m 3 rise in levels of PM 2.5 (lag 0−14), O 3 (lag 0−1), SO 2 (lag 0) and NO 2 (lag 0−14) were positively associated with relative risks of 1.050 (95% CI: 1.028, 1.073), 1.011 (1.007, 1.015), 1.052 (1.022, 1.083) and 1.094 (1.028, 1.164) of daily newly confirmed cases, respectively. Further adjustment for other pollutants did not change the associations materially (excepting in the model for SO 2 ). Our results indicated that COVID-19 incidence may be susceptible to airborne pollutants such as PM 2.5 , O 3 , SO 2 and NO 2 , and mitigation strategies of environmental factors are required to prevent spreading.

19.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315683

ABSTRACT

Background: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. Methods: Based on the reported cases, the effective reproduction number (B) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between a and NPIs through a generalized linear model (GLM). Results: Different NPIs were found to have led to different levels of reduction in c. Stay-at-home contributed approximately 51% (95% CI 46%-57%), wearing (face) masks 29% (15%-42%), gathering ban (more than 10 people) 19% (14%-24%), non-essential business closure 16% (10%-21%), declaration of emergency 13% (8%-17%), interstate travel restriction 11% (5%-16%), school closure 10% (7%-14%), initial business closure 10% (6%-14%), and gathering ban (more than 50 people) 7% (2%-11%). Conclusions: : This retrospective assessment of NPIs on k has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

20.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315570

ABSTRACT

With the COVID-19 epidemic quickly under control in China within the early months of 2020, importing the SARS-CoV-2 virus to the country now poses great challenges in epidemic control and prevention. Asymptomatic carriers play a critical role in the transmission of the virus and transmission on a large-scale poses enormous concern. We obtained data from new cluster outbreak regions with COVID-19 caused by asymptomatic carriers from June 2020 to January 2021, and reported the epidemiological characteristics, clinical data and the possible routes of viral transmission and infection. These results indicate the importance of regularly screening high-risk populations critical for epidemic control and provide the basis for suppressing the spread of the SARS-CoV-2 virus.

SELECTION OF CITATIONS
SEARCH DETAIL