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1.
The Journal of infectious diseases ; 2022.
Article in English | EuropePMC | ID: covidwho-1824578

ABSTRACT

Isolated reports of new-onset diabetes in patients with COVID-19 have led researchers to hypothesise that SARS-CoV-2 infects the human exocrine and endocrine pancreatic cells ex vivo and in vivo. However, existing research lacks experimental evidence indicating that SARS-CoV-2 can infect pancreatic tissue. Here, we found that cats infected with a high dose of SARS-CoV-2 exhibited hyperglycaemia. We also detected SARS-CoV-2 RNA in the pancreatic tissues of these cats, and immunohistochemical staining revealed the presence of SARS-CoV-2 nucleocapsid protein (NP) in the islet cells. SARS-CoV-2 NP and Spike proteins were primarily detected in Glu+ cells, and most Glu+ cells expressed ACE2. Additionally, immune protection experiments conducted on cats showed that the blood glucose levels of immunised cats did not increase post-challenge. Our data indicate the cat pancreas as a SARS-CoV-2 target and suggest that the infection of Glu+ cells could contribute to the metabolic dysregulation observed in SARS-CoV-2-infected cats.

2.
iScience ; : 104309, 2022.
Article in English | ScienceDirect | ID: covidwho-1804380

ABSTRACT

SUMMARY MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 COVID-19 patients using the high throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the COVID-19 patients, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection.

3.
China Economic Review ; : 101800, 2022.
Article in English | ScienceDirect | ID: covidwho-1797079

ABSTRACT

We consider a model of network interactions where the outcome of a unit depends on the outcomes of the connected units. We determine the key network link, i.e., the network link whose removal results in the largest reduction in the aggregate outcomes, and examine a measure that quantifies the contribution of a network link to the aggregate outcomes. We provide an example examining the spread of Covid-19 in China. Travel restrictions were imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, we examine the design of restrictions that target specific travel routes. Our approach may be generalized to multiple countries to guide policies during epidemics ranging from ex ante route-specific travel restrictions to ex post health measures based on travel histories, and from the initial travel restrictions to the phased reopening.

4.
Preprint in English | bioRxiv | ID: ppbiorxiv-488968

ABSTRACT

RationalePeople with pre-existing lung diseases like chronic obstructive pulmonary disease (COPD) are more likely to get very sick from SARS-CoV-2 disease 2019 (COVID-19), but an interrogation of the immune response to COVID-19 infection, spatial throughout the lung structure is lacking in patients with COPD. ObjectivesTo profile the immune microenvironment of lung parenchyma, airways, and vessels of never- and ever-smokers with or without COPD, whom all died of COVID-19, using spatial transcriptomic and proteomic profiling. FindingsThe parenchyma, airways, and vessels of COPD patients, compared to control lungs had: 1) significant enrichment for lung resident CD45RO+ memory T cells; 2) downregulation of genes associated with T cell antigen-priming and memory T cell differentiation; 3) higher expression of proteins associated with SARS-CoV-2 entry and major receptor ubiquitously across the ROIs and in particular the lung parenchyma, despite similar SARS-CoV-2 structural gene expression levels. ConclusionsThe lung parenchyma, airways, and vessels of COPD patients have increased T-lymphocytes with a blunted memory T cell response and a more invasive SARS-CoV-2 infection pattern, and may underlie the higher death toll observed with COVID-19.

5.
Front Psychiatry ; 13: 833865, 2022.
Article in English | MEDLINE | ID: covidwho-1775799

ABSTRACT

Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.

6.
Viruses ; 14(3)2022 02 27.
Article in English | MEDLINE | ID: covidwho-1765944

ABSTRACT

Porcine epidemic diarrhea virus (PEDV) is the major pathogen that causes diarrhea and high mortality in newborn piglets, with devastating impact on the pig industry. To further understand the molecular epidemiology and genetic diversity of PEDV field strains, in this study the complete genomes of four PEDV variants (HN2021, CH-HNYY-2018, CH-SXWS-2018, and CH-HNKF-2016) obtained from immunized pig farms in central China between 2016 to 2021 were characterized and analyzed. Phylogenetic analysis of the genome and S gene showed that the four strains identified in the present study had evolved into the subgroup G2a, but were distant from the vaccine strain CV777. Additionally, it was noteworthy that a new PEDV strain (named HN2021) belonging to the G2a PEDV subgroup was successfully isolated in vitro and it was further confirmed by RT-PCR that this isolate had a large natural deletion at 207-373 nt of the ORF3 gene, which has never been reported before. Particularly, in terms of pathogenicity evaluation, colostrum deprivation piglets challenged with PEDV HN2021 showed severe diarrhea and high mortality, confirming that PEDV HN2021 was a virulent strain. Hence, PEDV strain HN2021 of subgroup G2a presents a promising vaccine candidate for the control of recurring porcine epidemic diarrhea (PED) in China. This study lays the foundation for better understanding of the genetic evolution and molecular pathogenesis of PEDV.


Subject(s)
Coronavirus Infections , Porcine epidemic diarrhea virus , Swine Diseases , Vaccines , Animals , China/epidemiology , Diarrhea , Phylogeny , Swine , Virulence
7.
Cities ; 126: 103675, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1757209

ABSTRACT

Recent urban and regional studies have focused on identifying positive spillover effects from intensifying flows of people in city region networks. However, potential negative spillover effects have lacked attention. The article addresses this research gap focusing on the negative spillover effects represented by Covid-19 contagion in the Wuhan regional travel flow network, China. Drawing on central place theory and central flow theory, Covid-19 spatial spread simulation scenarios are explored using a combined micro-level epidemic compartment model and urban network approach. It is found that not only centrally positioned primate but secondary cities are highly risk exposed to contagion. In addition, these cities have enhanced transmission capacity in a balanced, well-connected travel flow network, whereas a centralised or locally clustered network would be more spread resilient. Both hierarchical position and horizontal flows are found relevant for explaining Covid-19 uneven spread and for informing mobility interventions for a potential future outbreak.

8.
J Med Internet Res ; 24(3): e31088, 2022 03 22.
Article in English | MEDLINE | ID: covidwho-1753280

ABSTRACT

BACKGROUND: Although timely and accurate information during the COVID-19 pandemic is essential for containing the disease and reducing mental distress, an infodemic, which refers to an overabundance of information, may trigger unpleasant emotions and reduce compliance. Prior research has shown the negative consequences of an infodemic during the pandemic; however, we know less about which subpopulations are more exposed to the infodemic and are more vulnerable to the adverse psychological and behavioral effects. OBJECTIVE: This study aimed to examine how sociodemographic factors and information-seeking behaviors affect the perceived information overload during the COVID-19 pandemic. We also investigated the effect of perceived information overload on psychological distress and protective behavior and analyzed the socioeconomic differences in the effects. METHODS: The data for this study were obtained from a cross-national survey of residents in 6 jurisdictions in Asia in May 2020. The survey targeted residents aged 18 years or older. A probability-based quota sampling strategy was adopted to ensure that the selected samples matched the population's geographical and demographic characteristics released by the latest available census in each jurisdiction. The final sample included 10,063 respondents. Information overload about COVID-19 was measured by asking the respondents to what extent they feel overwhelmed by news related to COVID-19. The measure of psychological distress was adapted from the Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5). Protective behaviors included personal hygienic behavior and compliance with social distancing measures. RESULTS: Younger respondents and women (b=0.20, 95% CI 0.14 to 0.26) were more likely to perceive information overload. Participants self-perceived as upper or upper-middle class (b=0.19, 95% CI 0.09 to 0.30) and those with full-time jobs (b=0.11, 95% CI 0.04 to 0.17) tended to perceive higher information overload. Respondents who more frequently sought COVID-19 information from newspapers (b=0.12, 95% CI 0.11 to 0.14), television (b=0.07, 95% CI 0.05 to 0.09), and family and friends (b=0.11, 95% CI 0.09 to 0.14) were more likely to feel overwhelmed. In contrast, obtaining COVID-19 information from online news outlets and social media was not associated with perceived information overload. There was a positive relationship between perceived information overload and psychological distress (b=2.18, 95% CI 2.09 to 2.26). Such an association was stronger among urban residents, full-time employees, and those living in privately owned housing. The effect of perceived information overload on protective behavior was not significant. CONCLUSIONS: Our findings revealed that respondents who were younger, were female, had a higher socioeconomic status (SES), and had vulnerable populations in the household were more likely to feel overwhelmed by COVID-19 information. Perceived information overload tended to increase psychological distress, and people with higher SES were more vulnerable to this adverse psychological consequence. Effective policies and interventions should be promoted to target vulnerable populations who are more susceptible to the occurrence and negative psychological influence of perceived information overload.


Subject(s)
COVID-19 , Psychological Distress , Adolescent , COVID-19/epidemiology , COVID-19/prevention & control , Cross-Sectional Studies , Female , Humans , Pandemics , Surveys and Questionnaires
9.
BMC Geriatr ; 22(1): 181, 2022 03 04.
Article in English | MEDLINE | ID: covidwho-1724420

ABSTRACT

BACKGROUND: Older adults who live alone and have difficulties in activities of daily living (ADLs) may have been more vulnerable during the COVID-19 pandemic. However, little is known about pandemic-related changes in ADL assistance (such as home care, domiciliary care) and its international variation. We examined international patterns and changes in provision of ADL assistance, and related these to country-level measures including national income and health service expenditure. METHODS: We analysed data covering 29 countries from three longitudinal cohort studies (Health and Retirement Study, English Longitudinal Study of Aging, and Survey of Health, Ageing and Retirement in Europe). Eligible people were aged ≥50 years and living alone. Outcomes included ADL difficulty status (assessed via six basic ADLs and five instrumental ADLs) and receipt of ADL assistance. Wealth-related inequality and need-related inequity in ADL assistance were measured using Erreygers' corrected concentration index (ECI). Correlations were estimated between prevalence/inequality/inequity in ADL assistance and national health-related indicators. We hypothesized these measures would be associated with health system factors such as affordability and availability of ADL assistance, as well as active ageing awareness. RESULTS: During COVID-19, 18.4% of older adults living alone reported ADL difficulties (ranging from 8.8% in Switzerland to 29.2% in the USA) and 56.8% of those reporting difficulties received ADL assistance (ranging from 38.7% in the UK to 79.8% in Lithuania). Females were more likely to receive ADL assistance than males in 16/29 countries; the sex gap increased further during the pandemic. Wealth-related ECIs indicated socioeconomic equality in ADL assistance within 24/39 countries before the pandemic, and significant favouring of the less wealthy in 18/29 countries during the pandemic. Needs-related ECIs indicated less equity in assistance with ADLs during the pandemic than before. Our hypotheses on the association between ADL provision measures and health system factors were confirmed before COVID-19, but unexpectedly disconfirmed during COVID-19. CONCLUSION: This study revealed an unequal (and in some countries, partly needs-mismatched) response from countries to older adults living alone during the COVID-19 pandemic. The findings might inform future research about, and policies for, older adults living alone, particularly regarding social protection responses during crises.


Subject(s)
Activities of Daily Living , COVID-19 , Aged , COVID-19/epidemiology , Female , Humans , Longitudinal Studies , Male , Pandemics , SARS-CoV-2
10.
Reference Module in Biomedical Sciences ; 2022.
Article in English | EuropePMC | ID: covidwho-1710780

ABSTRACT

Emerging infectious diseases are an ever-present threat to public health, and COVID-19 is the most recent example. There is an urgent need to develop a robust framework to combat the disease with safe and effective therapeutic options. Compared to de novo drug discovery, drug repurposing may offer a lower-cost and faster drug discovery paradigm to explore potential treatment options of existing drugs. This chapter elucidates the advantages of artificial intelligence (AI) in enhancing the drug repurposing process from a data science perspective, using COVID-19 as an example. First, we elaborate on how AI-powered drug repurposing benefits from the accumulated data and knowledge of COVID-19 natural history and pathogenesis. Second, we summarize the pros and cons of AI-powered drug repurposing strategies to facilitate fit-for-purpose selection. Finally, we outline challenges of AI-powered drug repurposing from a regulatory perspective and suggest some potential solutions. Key points • AI-powered drug purposing is promising for emerging treatments for COVID-19 infection.• Accumulated biological data profiles facilitate AI-based drug repurposing efforts for development of COVID-19 therapies.• The ‘fit-for-purpose selection of AI-powered drug repurposing strategies is key to uncovering hidden information among drugs, targets, and diseases.• Efforts from different stakeholders boost the adoption of AI-powered drug repurposing in the regulatory setting.

12.
Frontiers in public health ; 9, 2021.
Article in English | EuropePMC | ID: covidwho-1696034

ABSTRACT

The Coronavirus Disease (COVID) pandemic has aroused challenges to emotional well-being of the individuals. With 1,582 respondents from the Health and Retirement Survey (HRS), this study investigates the heterogeneity in older adults' vulnerability and examines the relationship between vulnerability types, aging attitudes, and emotional responses. International Positive and Negative Affect Schedule Short-form (I-PANAS-SF) and Attitudes toward own aging (ATOT) were used to assess the emotional experiences and aging attitudes, and 14 kinds of pandemic-related deprivations evaluated vulnerability of individuals. Latent class analysis (LCA) was used to explore the vulnerability types, and weighted linear regressions examined the relationship between vulnerability, aging attitudes, and emotional responses. The results showed that the proportion for individuals with mild vulnerability (MV), healthcare use vulnerability (HV), and dual vulnerability in healthcare use and financial sustainment (DVs) was 67, 22, and 11%, respectively. Older adults aged below 65, Hispanics and non-Hispanic Blacks, and those not eligible for Medicaid were more likely to have HV or DVs. The relationship between vulnerability and positive emotions (PAs) was non-significant, yet individuals with HV (beta = 0.10, standard error [SE] = 0.16) or DVs (beta = 0.09, SE = 0.28) were likely to have more negative emotions (NAs) than their mildly vulnerable counterparts. Furthermore, aging attitudes moderated the relationship between vulnerability and emotions. The salutary effect of positive aging attitudes on emotional well-being was more significant among people with DVs than those with MV (beta = 0.20, SE = 0.04 for positive responses;beta = −0.15, SE = 0.04 for negative responses). Thus, we urge more attention for vulnerable older adults in a pandemic context. Meanwhile, encouraging positive aging attitudes might be helpful for older adults to have better emotional well-being, especially for those with DVs.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325172

ABSTRACT

With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment is proposed. Establish a "Scrapy-Redis-Bloomfilter" distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, and can also reflect the depth of the seven emotions such as Hopeful, Happy, and Depressed. Finally, we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model. The results show that our model has better generalization ability and smaller discriminant error. We designed a large data visualization screen, which can clearly show the trend of public emotions, the proportion of various emotion categories, keywords, hot topics, etc., and fully and intuitively reflect the development of public opinion.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322239

ABSTRACT

Background: The current outbreak of coronavirus disease 2019 (COVID-19) has recently been declared as a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. Previous studies that applied the traditional epidemic models or machine learning models were subject to underfitting or overfitting problems. Methods: We propose a new model named Dynamic-Susceptible-Exposed-Infective-Quarantined (D-SEIQ), by making appropriate modifications of the Susceptible-Exposed-Infective-Recovered (SEIR) model and integrating machine learning based parameter optimization under epidemiological rational constraints. We used the model to predict the long-term reported cumulative numbers of COVID-19 cases in China from 27 January, 2020. Results: We evaluated our model on officially reported confirmed cases from three different regions in China, and the results proved the effectiveness of our model in terms of simulating and predicting the trend of COVID-19 outbreak. In China-Excluding-Hubei area within 7 days after the first public report, our model successfully and accurately predicted the 40 days long trend and the exact date of turning point. The predicted cumulative number (12,506) by 10, March 2020 was only 3·8% different with the actual number (13,005). The parameters obtained by our model proved the effectiveness of prevention and intervention strategies on epidemic control in China. Conclusions: The integrated approach of epidemic and machine learning models could accurately forecast the long-term trend of COVID-19 outbreak. The learned parameters suggested the effectiveness of intervention measures taken in China.

15.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319967

ABSTRACT

During the normalized phase of COVID-19, droplets or aerosol particles produced by infected personnel are considered as the potential source of infection with uncertain exposure risk. As such, in densely populated open spaces, it is necessary to adopt strategies to mitigate the risk of infection disease transmission while providing sufficient ventilation air. An example of such strategies is use of physical barriers. In this study, the impact of barrier heights on the spread of aerosol particles is investigated in an open office environment with the well-designed ventilation mode and supply air rate. The risk of infection disease transmission is evaluated using simulation of particle concentration in different locations and subject to a number of source scenarios. It was found that a barrier height of at least 60cm above the desk surface is needed to effectively prevent the transmission of viruses. For workstations within 4m from the outlet, a 70cm height is considered, and with a proper ventilation mode, it is shown that the barriers can reduce the risk of infection by 72%. However, for the workstations further away from the outlet (beyond 4m), the effect of physical barrier cannot be that significant. In summary, this study provides a theoretical analysis for implementing physical barriers, as a low-cost mitigation strategy, subject to various height scenarios and investigation of their effectiveness in reducing the infection transmission probability.

16.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-312713

ABSTRACT

Background: An ideal animal model to study SARS-coronavirus 2 (SARS-CoV-2) pathogenesis and evaluate therapies and vaccines should reproduce SARS-CoV-2 infection and recapitulate lung disease like those seen in humans. The angiotensin-converting enzyme 2 (ACE2) is a functional receptor for SARS-CoV-2, but mice are resistant to the infection because their ACE2 is incompatible with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Methods: We generated a mouse-adapted strain SARS-CoV-2 by serial passages in the lung of BALB/c mice. Complete genome deep sequencing of different generations of viruses was performed to characterize the dynamics of the adaptive mutations in SARS-CoV-2. Indirect immunofluorescence analysis and Biolayer interferometry experiments demonstrated that two mutations in RBD significantly increased its binding affinity towards mouse ACE2. Significantly, TLR7/8 agonist Resiquimod block SARS-CoV-2 in vitro and in vivo. Findings: We adapted a wild-type SARS-CoV-2 by serial passages in the lung of BALB/c mice. The mouse-adapted strain WBP-1 showed increased infectivity in BALB/c mice and led to severe interstitial pneumonia. We characterized the dynamics of the adaptive mutations in SARS-CoV-2 and demonstrated that Q493K and Q498H in RBD significantly increased its binding affinity towards mouse ACE2. Additionally, The TLR7/8 agonist Resiquimod was able to protect mice against WBP-1 challenge, demonstrating this mouse-adapted strain is a useful tool to investigate COVID-19 and develop new therapies. Interpretation: We found for the first time that the Q493K and Q498H mutations in the RBD of WBP-1 enhanced its interactive affinities with mACE2. The mouse-adapted SARS-CoV-2 provides a valuable tool for the evaluation of novel antiviral and vaccine strategies, especially in determining the immunopathological consequences of any intervention. This study also verified the antiviral activity of TLR7/8 agonist Resiquimod against SARS-CoV-2 in vitro and in vivo.Funding Statement: This research was funded by Emergency Science and Technology Project of Hubei Province(2020FCA046)and Independent Science and Technology Innovation Fund of Huazhong Agricultural University in 2020 (2662020PY002).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The animal experiments were approved by the Research Ethics Committee, Huazhong Agricultural University, Hubei, China (HZAUMO-2020-0007). All the animal experiments were conducted in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals from the Research Ethics Committee, Huazhong Agricultural University, Hubei, China.

17.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308282

ABSTRACT

Background: With the outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the effectiveness of providing mask protection is important for people. This article introduces a customized mask retainer to improve the fit performance of face masks. Methods: : The participant’s 3D face scans with and without a surgical mask were taken by using a 3D face scanner. The fitter was designed on the 3D face scan data according to the facial anthropometric landmarks, and examined and adjusted on the face scan data with a mask. The fitter was 3D printed using a metal printer for Titanium. The effectiveness of the fitter on augmentation of fit of surgical mask was test according to the Chinese Standard. Tests were repeated three times per participant, and compare differences between groups by Wilcoxon Matched-Pairs Signed-Ranks Test using software (a=.05). Results: : The effectiveness test of the retainer on augmentation of fit performance showed a result more than 25-fold increase of overall Fit Factor, which have met the fit requirement for KN95 respirators in China. Conclusions: : Fit Factor results indicated that by using the retainer, the Fit Factors of overall and each exercise have significantly increased as compared to that of face mask alone group. It may provide a solution to the shortage of N95 respirators the world is now encountering as fighting against the COVID-19 epidemic.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308278

ABSTRACT

We consider a model of network interactions where the outcome of a unit depends on the outcomes of the connected units. We determine the key network link, i.e., the network link whose removal results in the largest reduction in the aggregate outcomes, and provide a measure that quantifies the contribution of a network link to the aggregate outcomes, which complements the intercentrality measure of the key network node proposed by Ballester, Calv ́o-Armengol, and Zenou (2006). We provide an example examining the spread of Covid-19 in China. Travel restrictions were imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, we examine the design of restrictions that target specific travel routes. Our approach may be generalized to multiple countries to guide policies during epidemics ranging from ex ante route-specific travel restrictions to ex post health measures based on travel histories, and from the initial travel restrictions to the phased reopening.

19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307139

ABSTRACT

During the current COVID-19 pandemic, decision makers are tasked with implementing and evaluating strategies for both treatment and disease prevention. In order to make effective decisions, they need to simultaneously monitor various attributes of the pandemic such as transmission rate and infection rate for disease prevention, recovery rate which indicates treatment effectiveness as well as the mortality rate and others. This work presents a technique for monitoring the pandemic by employing an Susceptible, Exposed, Infected, Recovered Death model regularly estimated by an augmented particle Markov chain Monte Carlo scheme in which the posterior distribution samples are monitored via Multivariate Exponentially Weighted Average process monitoring. This is illustrated on the COVID-19 data for the State of Qatar.

20.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315973

ABSTRACT

Background: Pulmonary fibrosis is a common complication in patients with viral pneumonia, which causes restricted ventilation disorders and affects the prognosis of patients. However, the pulmonary function of patients with 2019 novel coronavirus (COVID-19)-induced pneumonia has not yet been reported. Methods: : A retrospective analysis of 137 patients with COVID-19-induced pneumonia who were discharged from the Enze Hospital, Taizhou Enze Medical Center (Group), from January 31, 2020, to March 11, 2020. Follow-up occurred two weeks after hospital discharge, whereupon patients received a pulmonary function test. Results: : Of the 137 patients who received a pulmonary function test two weeks after discharge, 51.8% were male, and the mean age was 47 years. Only 19.7% of the patients were identified as having severe novel coronavirus pneumonia. The pulmonary function test showed that for a small number of patients ((FEV1/FVC)/% <70%,) the mean ICV and FVC was 2.4±0.7 L, 3.2±0.8 L, respectively. In severe cases, 88.9% of patients had an IVC <80% of the predicted value and 55.6% of patients had an FVC <80% of the predicted value. The MEF25, MEF50, and MEF75 <70% values were 55.6%, 40.7%, and 25.9%, respectively. In the non-severe group, 79.1% of patients has an IVC <80% of the predicted value, and 16.4% of patients had an FVC <80% of the predicted value. The mean MEF25, MEF50, and MEF75 <70% values were 57.3%, 30%, and 13.6%, respectively. Conclusions: : In this study, the results suggest that the pulmonary function of patients with 2019 novel coronavirus (COVID-19)-induced pneumonia manifested as restrictive ventilation disorder and small airway obstruction. The incidence was increased among critically ill patients. Trial registration number: ChiCTR2000029866.

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