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1.
J Affect Disord ; 2022 Jan 13.
Article in English | MEDLINE | ID: covidwho-1620777

ABSTRACT

BACKGROUND: The outbreak of COVID-19 has been a big challenge for senior high school students in China who are facing tremendous pressure of the highly competitive College Entrance Examination. METHODS: To evaluate the psychological impact of the event in the population, we conducted an anonymous online survey among senior high school students in China between 26 Feb and 4 March, 2020. Information collected included demographic characteristics, attitude toward medical study, infection of COVID-19 in acquaintances, anxiety symptoms evaluated using the GAD-7, and health literacy level measured using the IDSHL. RESULTS: Of 21,085 participants, 3,575 (17.0%), 943 (4.5%) and 448 (2.1%) reported with mild, moderate, and severe anxiety. Female, higher academic year, worse self-evaluated academic performance, negative attitude toward medical study, living in Hubei province and having acquaintance infected with COVID-19 were significantly associated with anxiety level, while higher education level of mother and higher IDSHL score were associated with a lower risk. The score of IDSHL, particularly of the domain "infectious disease prevention", was associated with the GAD-7 score in a linear pattern (ß=-0.0371, p<0.01). LIMITATIONS: Limitations included the cross-sectional study design unable to infer the casual relationship, anonymous survey, selection bias and self-reported anxiety disorder levels. CONCLUSIONS: The results suggested that COVID-19 outbreak may increase anxiety level in senior high school students in China. The anxiety related factors observed in this study may help to identify vulnerable individuals and develop interventions.

2.
Chinese Journal of Integrated Traditional and Western Medicine ; 41(3):330-337, 2021.
Article in Chinese | CAB Abstracts | ID: covidwho-1602741

ABSTRACT

Objective: To explore the mechanism of Hanshi Zufei Formula (HSZFF) treating coronavirus disease 2019 (COVID-19) by the data mining analysis of network pharmacology and the molecular docking.

4.
PLoS One ; 17(1): e0257963, 2022.
Article in English | MEDLINE | ID: covidwho-1608831

ABSTRACT

In times of crisis, including the current COVID-19 pandemic, the supply chain of filtering facepiece respirators, such as N95 respirators, are disrupted. To combat shortages of N95 respirators, many institutions were forced to decontaminate and reuse respirators. While several reports have evaluated the impact on filtration as a measurement of preservation of respirator function after decontamination, the equally important fact of maintaining proper fit to the users' face has been understudied. In the current study, we demonstrate the complete inactivation of SARS-CoV-2 and preservation of fit test performance of N95 respirators following treatment with dry heat. We apply scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS), X-ray diffraction (XRD) measurements, Raman spectroscopy, and contact angle measurements to analyze filter material changes as a consequence of different decontamination treatments. We further compared the integrity of the respirator after autoclaving versus dry heat treatment via quantitative fit testing and found that autoclaving, but not dry heat, causes the fit of the respirator onto the users face to fail, thereby rendering the decontaminated respirator unusable. Our findings highlight the importance to account for both efficacy of disinfection and mask fit when reprocessing respirators to for clinical redeployment.


Subject(s)
COVID-19/prevention & control , Decontamination/methods , Equipment Reuse , N95 Respirators/virology , SARS-CoV-2/physiology , COVID-19/transmission , Equipment and Supplies , Health Personnel , Hot Temperature , Humans , Pandemics
5.
Front Public Health ; 9: 737817, 2021.
Article in English | MEDLINE | ID: covidwho-1608735

ABSTRACT

Background: Prevention and control of HIV/AIDS and other sexually transmitted diseases (STDs) are major public health priorities in China, but are influenced by the COVID-19 epidemic. In this study, we aimed to quantitatively explore the impact of the COVID-19 epidemic and its control measures on five major STD epidemics in China. Methods: A monthly number of newly reported cases of HIV/AIDS, hepatitis B and C, gonorrhea, and syphilis from January 2010 to December 2020 were extracted to establish autoregressive integrated moving average (ARIMA) models. Each month's absolute percentage error (APE) between the actual value and model-predicted value of each STD in 2020 was calculated to evaluate the influence of the COVID-19 epidemic on the STDs. Pearson correlation analysis was conducted to explore the confirmed COVID-19 case numbers and the COVID-19 control measures' correlations with the case numbers and the APEs of five STDs in 2020. Results: The actual number of five STDs in China was more than 50% lower than the predicted number in the early days of the COVID-19 epidemic, especially in February. Among them, the actual number of cases of hepatitis C, gonorrhea, and syphilis in February 2020 was more than 100% lower than the predicted number (APE was -102.3, -109.0, and -100.4%, respectively). After the sharply declines of STDs' reported cases in early 2020, the case numbers recovered quickly after March. The epidemic of STDs was negatively associated with the COVID-19 epidemic and its control measures, especially for restrictions on gathering size, close public transport, and stay-at-home requirements (p < 0.05). Conclusion: COVID-19 had a significant but temporary influence on the STD epidemic in China. The effective control of COVID-19 is vital for STD prevention. STD services need to be improved to prevent STDs from becoming a secluded corner in the shadow of COVID-19.


Subject(s)
COVID-19 , Epidemics , Sexually Transmitted Diseases , China/epidemiology , Humans , SARS-CoV-2 , Sexually Transmitted Diseases/epidemiology
6.
Brief Bioinform ; 2021 Dec 30.
Article in English | MEDLINE | ID: covidwho-1598417

ABSTRACT

The outbreak of COVID-19 caused by SARS-coronavirus (CoV)-2 has made millions of deaths since 2019. Although a variety of computational methods have been proposed to repurpose drugs for treating SARS-CoV-2 infections, it is still a challenging task for new viruses, as there are no verified virus-drug associations (VDAs) between them and existing drugs. To efficiently solve the cold-start problem posed by new viruses, a novel constrained multi-view nonnegative matrix factorization (CMNMF) model is designed by jointly utilizing multiple sources of biological information. With the CMNMF model, the similarities of drugs and viruses can be preserved from their own perspectives when they are projected onto a unified latent feature space. Based on the CMNMF model, we propose a deep learning method, namely VDA-DLCMNMF, for repurposing drugs against new viruses. VDA-DLCMNMF first initializes the node representations of drugs and viruses with their corresponding latent feature vectors to avoid a random initialization and then applies graph convolutional network to optimize their representations. Given an arbitrary drug, its probability of being associated with a new virus is computed according to their representations. To evaluate the performance of VDA-DLCMNMF, we have conducted a series of experiments on three VDA datasets created for SARS-CoV-2. Experimental results demonstrate that the promising prediction accuracy of VDA-DLCMNMF. Moreover, incorporating the CMNMF model into deep learning gains new insight into the drug repurposing for SARS-CoV-2, as the results of molecular docking experiments reveal that four antiviral drugs identified by VDA-DLCMNMF have the potential ability to treat SARS-CoV-2 infections.

7.
Lancet Infect Dis ; 2021 Dec 07.
Article in English | MEDLINE | ID: covidwho-1565673

ABSTRACT

BACKGROUND: Large-scale vaccination against COVID-19 is being implemented in many countries with CoronaVac, an inactivated vaccine. We aimed to assess the immune persistence of a two-dose schedule of CoronaVac, and the immunogenicity and safety of a third dose of CoronaVac, in healthy adults aged 18 years and older. METHODS: In the first of two single-centre, double-blind, randomised, placebo-controlled phase 2 clinical trials, adults aged 18-59 years in Jiangsu, China, were initially allocated (1:1) into two vaccination schedule cohorts: a day 0 and day 14 vaccination cohort (cohort 1) and a day 0 and day 28 vaccination cohort (cohort 2); each cohort was randomly assigned (2:2:1) to either a 3 µg dose or 6 µg dose of CoronaVac or a placebo group. Following a protocol amendment on Dec 25, 2020, half of the participants in each cohort were allocated to receive an additional dose 28 days (window period 30 days) after the second dose, and the other half were allocated to receive a third dose 6 months (window period 60 days) after the second dose. In the other phase 2 trial, in Hebei, China, participants aged 60 years and older were assigned sequentially to receive three injections of either 1·5 µg, 3 µg, or 6 µg of vaccine or placebo, administered 28 days apart for the first two doses and 6 months (window period 90 days) apart for doses two and three. The main outcomes of the study were geometric mean titres (GMTs), geometric mean increases (GMIs), and seropositivity of neutralising antibody to SARS-CoV-2 (virus strain SARS-CoV-2/human/CHN/CN1/2020, GenBank accession number MT407649.1), as analysed in the per-protocol population (all participants who completed their assigned third dose). Our reporting is focused on the 3 µg groups, since 3 µg is the licensed formulation. The trials are registered with ClinicalTrials.gov, NCT04352608 and NCT04383574. FINDINGS: 540 (90%) of 600 participants aged 18-59 years were eligible to receive a third dose, of whom 269 (50%) received the primary third dose 2 months after the second dose (cohorts 1a-14d-2m and 2a-28d-2m) and 271 (50%) received a booster dose 8 months after the second dose (cohorts 1b-14d-8m and 2b-28d-8m). In the 3 µg group, neutralising antibody titres induced by the first two doses declined after 6 months to near or below the seropositive cutoff (GMT of 8) for cohort 1b-14d-8m (n=53; GMT 3·9 [95% CI 3·1-5·0]) and for cohort 2b-28d-8m (n=49; 6·8 [5·2-8·8]). When a booster dose was given 8 months after a second dose, GMTs assessed 14 days later increased to 137·9 (95% CI 99·9-190·4) for cohort 1b-14d-8m and 143·1 (110·8-184·7) 28 days later for cohort 2b-28d-8m. GMTs moderately increased following a primary third dose, from 21·8 (95% CI 17·3-27·6) on day 28 after the second dose to 45·8 (35·7-58·9) on day 28 after the third dose in cohort 1a-14d-2m (n=54), and from 38·1 (28·4-51·1) to 49·7 (39·9-61·9) in cohort 2a-28d-2m (n=53). GMTs had decayed to near the positive threshold by 6 months after the third dose: GMT 9·2 (95% CI 7·1-12·0) in cohort 1a-14d-2m and 10·0 (7·3-13·7) in cohort 2a-28d-2m. Similarly, in adults aged 60 years and older who received booster doses (303 [87%] of 350 participants were eligible to receive a third dose), neutralising antibody titres had declined to near or below the seropositive threshold by 6 months after the primary two-dose series. A third dose given 8 months after the second dose significantly increased neutralising antibody concentrations: GMTs increased from 42·9 (95% CI 31·0-59·4) on day 28 after the second dose to 158·5 (96·6-259·2) on day 28 following the third dose (n=29). All adverse reactions reported within 28 days after a third dose were of grade 1 or 2 severity in all vaccination cohorts. There were three serious adverse events (2%) reported by the 150 participants in cohort 1a-14d-2m, four (3%) by 150 participants from cohort 1b-14d-8m, one (1%) by 150 participants in each of cohorts 2a-28d-2m and 2b-28d-8m, and 24 (7%) by 349 participants from cohort 3-28d-8m. INTERPRETATION: A third dose of CoronaVac in adults administered 8 months after a second dose effectively recalled specific immune responses to SARS-CoV-2, which had declined substantially 6 months after two doses of CoronaVac, resulting in a remarkable increase in the concentration of antibodies and indicating that a two-dose schedule generates good immune memory, and a primary third dose given 2 months after the second dose induced slightly higher antibody titres than the primary two doses. FUNDING: National Key Research and Development Program, Beijing Science and Technology Program, and Key Program of the National Natural Science Foundation of China. TRANSLATION: For the Mandarin translation of the abstract see Supplementary Materials section.

8.
TrAC Trends in Analytical Chemistry ; : 116507, 2021.
Article in English | ScienceDirect | ID: covidwho-1559776

ABSTRACT

Wastewater surveillance is a powerful tool to understand community profiling in terms of health monitoring. Tracking biomarkers such as inorganic and organic pollutants, drugs, and pathogens in wastewater gives a general idea about the lifestyle and health status of a population as well as pollutant exposure caused by various toxic chemicals. Notably, tracing pathogenic clues could help predict and prevent disease outbreaks such as the ongoing COVID-19 pandemic in communities. To this end, developing portable biosensing platforms will facilitate the on-site monitoring of water contamination without requiring complex equipment. New technological developments in synthetic biology have advanced both synthetic gene circuit-based biosensors and new in vitro detection strategies coupled with easy-to-interpret visualization methods. Here, we summarize the latest advances in synthetic biology tools and discuss how they enable the development of rapid, low-cost, ease-to-use and field-deployable biosensors for monitoring a variety of water contaminants and health-related biomarkers in the environment.

9.
Preprint in English | Other preprints | ID: ppcovidwho-296407

ABSTRACT

In times of crisis, including the current COVID-19 pandemic, the supply chain of filtering facepiece respirators, such as N95 respirators, are disrupted. To combat shortages of N95 respirators, many institutions were forced to decontaminate and reuse respirators. While several reports have evaluated the impact on filtration as a measurement of preservation of respirator function after decontamination, the equally important fact of maintaining proper fit to the users’ face has been understudied. In the current study, we demonstrate the complete inactivation of SARS-CoV-2 and preservation of fit test performance of N95 respirators following treatment with dry heat. We apply scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS), X-ray diffraction (XRD) measurements, Raman spectroscopy, and contact angle measurements to analyze filter material changes as a consequence of different decontamination treatments. We further compared the integrity of the respirator after autoclaving versus dry heat treatment via quantitative fit testing and found that autoclaving, but not dry heat, causes the fit of the respirator onto the users face to fail, thereby rendering the decontaminated respirator unusable. Our findings highlight the importance to account for both efficacy of disinfection and mask fit when reprocessing respirators to for clinical redeployment.

10.
Carbohydrate Polymers ; : 118971, 2021.
Article in English | ScienceDirect | ID: covidwho-1549670

ABSTRACT

Ligusticum chuanxiong, the dried rhizome of Ligusticum chuanxiong Hort, has been widely applied in traditional Chinese medicine for treating plague, and it has appeared frequently in the prescriptions against COVID-19 lately. Ligusticum chuanxiong polysaccharide (LCPs) is one of the effective substances, which has various activities, such as, anti-oxidation, promoting immunity, anti-tumor, and anti-bacteria. The purified fractions of LCPs are considered to be pectic polysaccharides, which are mainly composed of GalA, Gal, Ara and Rha, and are generally linked by α-1,4-d-GalpA, α-1,2-l-Rhap, α-1,5-l-Araf, β-1,3-d-Galp and β-1,4-d-Galp, etc. The pectic polysaccharide shows an anti-infective inflammatory activity, which is related to antiviral infection of Ligusticum chuanxiong. In this article, the isolation, purification, structural features, and biological activities of LCPs in recent years are reviewed, and the potential of LCPs against viral infection as well as questions that need future research are discussed.

11.
EPMA J ; : 1-18, 2021 Jul 16.
Article in English | MEDLINE | ID: covidwho-1544595

ABSTRACT

Aims: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. Methods: Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. "Gene Score" and "Drug Score" were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. Results: Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. Conclusion: We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-021-00247-0.

12.
Nature ; 2021 Nov 25.
Article in English | MEDLINE | ID: covidwho-1532072

ABSTRACT

During the current SARS-CoV-2 pandemic, a variety of mutations have accumulated in the viral genome, and currently, four variants of concern (VOCs) are considered potentially hazardous to human society1. The recently emerged B.1.617.2/Delta VOC is closely associated with the COVID-19 surge that occurred in India in the spring of 20212. However, its virological properties remain unclear. Here, we show that the B.1.617.2/Delta variant is highly fusogenic and notably more pathogenic than prototypic SARS-CoV-2 in infected hamsters. The P681R mutation in the spike protein, which is highly conserved in this lineage, facilitates spike protein cleavage and enhances viral fusogenicity. Moreover, we demonstrate that the P681R-bearing virus exhibits higher pathogenicity than its parental virus. Our data suggest that the P681R mutation is a hallmark of the virological phenotype of the B.1.617.2/Delta variant and is associated with enhanced pathogenicity.

13.
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(3): 427-432, 2021 Mar 10.
Article in Chinese | MEDLINE | ID: covidwho-1534262

ABSTRACT

Objective: To investigate the clusters of COVID-19 associated with a market (market Y) in Haidian District, Beijing, and analyze the chain of transmission and provide reference for effective prevention and control of COVID-19. Methods: The investigation of field epidemiology and cluster epidemic was used to describe the distributions of all COVID-19 cases. The time sequence diagram of the cases, disease onset was drawn and transmission chains were analyzed. Real-time RT-PCR assay was conducted for SARS-CoV-2 nucleic acid test by using the respiratory samples of the cases. Results: The COVID-19 epidemic, originated from a wholesale farm produce market (market X) in Fengtai District, Beijing, was introduced by a marketer in the market Y who had exposed to market X, causing 8 clusters of 20 confirmed cases of COVID-19 and one asymptomatic case, including 8 men and 13 women, in market Y, surrounding communities, food plaza, companies,families and other places. The incidence peaked during June 10-14, 2020; the median age of the cases was 45 years, ranging from 5 years to 87 years. The initial symptoms of the cases included fever (10/20) and pharynx discomfort (7/20). The median of incubation period was 5 days (IQR:3-8). The median of serial interval between primary case and secondary cases was 5 days with a secondary attack rate of 3.7%(20/538), and the secondary attack rate in household close-contacts was 14.0% (7/50). Conclusions: The clusters of COVID-19 associated with market Y were caused by several modes of transmission, including human-to-human, contaminated material-to-human, etc. The combined public-health response measures were effective to control the COVID-19 epidemic in Haidian district of Beijing.


Subject(s)
COVID-19 , Epidemics , Beijing/epidemiology , Female , Humans , Incidence , Male , Middle Aged , SARS-CoV-2
14.
Infect Drug Resist ; 14: 4641-4655, 2021.
Article in English | MEDLINE | ID: covidwho-1523538

ABSTRACT

Objective: COVID-19 may have a demonstrable influence on disease patterns. However, it remained unknown how tuberculosis (TB) epidemics are impacted by the COVID-19 outbreak. The purposes of this study are to evaluate the impacts of the COVID-19 outbreak on the decreases in the TB case notifications and to forecast the epidemiological trends in China. Methods: The monthly TB incidents from January 2005 to December 2020 were taken. Then, we investigated the causal impacts of the COVID-19 pandemic on the TB case reductions using intervention analysis under the Bayesian structural time series (BSTS) method. Next, we split the observed values into different training and testing horizons to validate the forecasting performance of the BSTS method. Results: The TB incidence was falling during 2005-2020, with an average annual percentage change of -3.186 (95% confidence interval [CI] -4.083 to -2.281), and showed a peak in March-April and a trough in January-February per year. The BSTS method assessed a monthly average reduction of 14% (95% CI 3.8% to 24%) in the TB case notifications from January-December 2020 owing to COVID-19 (probability of causal effect=99.684%, P=0.003), and this method generated a highly accurate forecast for all the testing horizons considering the small forecasting error rates and estimated a continued downward trend from 2021 to 2035 (annual percentage change =-2.869, 95% CI -3.056 to -2.681). Conclusion: COVID-19 can cause medium- and longer-term consequences for the TB epidemics and the BSTS model has the potential to forecast the epidemiological trends of the TB incidence, which can be recommended as an automated application for public health policymaking in China. Considering the slow downward trend in the TB incidence, additional measures are required to accelerate the progress of the End TB Strategy.

15.
J Infect Public Health ; 15(1): 13-20, 2021 Nov 18.
Article in English | MEDLINE | ID: covidwho-1517346

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic continues to escalate intensively worldwide. Massive studies on general populations with SARS-CoV-2 infection have revealed that pre-existing comorbidities were a major risk factor for the poor prognosis of COVID-19. Notably, 49-75% of COVID-19 patients had no comorbidities, but this cohort would also progress to severe COVID-19 or even death. However, risk factors contributing to disease progression and death in patients without chronic comorbidities are largely unknown; thus, specific clinical interventions for those patients are challenging. METHODS: A multicenter, retrospective study based on 4806 COVID-19 patients without chronic comorbidities was performed to identify potential risk factors contributing to COVID-19 progression and death using LASSO and a stepwise logistic regression model. RESULTS: Among 4806 patients without pre-existing comorbidities, the proportions with severe progression and mortality were 34.29% and 2.10%, respectively. The median age was 47.00 years [interquartile range, 36.00-56.00], and 2162 (44.99%) were men. Among 51 clinical parameters on admission, age ≥ 47, oxygen saturation < 95%, increased lactate dehydrogenase, neutrophil count, direct bilirubin, creatine phosphokinase, blood urea nitrogen levels, dyspnea, increased blood glucose and prothrombin time levels were associated with COVID-19 mortality in the entire cohort. Of the 3647 patients diagnosed with non-severe COVID-19 on admission, 489(13.41%) progressed to severe disease. The risk factors associated with COVID-19 progression from non-severe to severe illness were increased procalcitonin levels, SpO2 < 95%, age ≥ 47, increased LDH, activated partial thromboplastin time levels, decreased high-density lipoprotein cholesterol levels, dyspnea and increased D-dimer levels. CONCLUSIONS: COVID-19 patients without pre-existing chronic comorbidities have specific traits and disease patterns. COVID-19 accompanied by severe bacterial infections, as indicated by increased procalcitonin levels, was highly associated with disease progression from non-severe to severe. Aging, impaired respiratory function, coagulation dysfunction, tissue injury, and lipid metabolism dysregulation were also associated with disease progression. Once factors for multi-organ damage were elevated and glucose increased at admission, these findings indicated a higher risk for mortality. This study provides information that helps to predict COVID-19 prognosis specifically in patients without chronic comorbidities.

16.
Front Pharmacol ; 12: 721769, 2021.
Article in English | MEDLINE | ID: covidwho-1512050

ABSTRACT

Coronavirus disease (COVID-19) patients with cardiovascular and metabolic disorders have been found to have a high risk of developing severe conditions with high mortality, further affecting the prognosis of COVID-19. However, the effect of hypertension and angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blocker (ARB) agents on the clinical characteristics and inflammatory immune responses in COVID-19 patients is still undefined. In this study, 90 COVID-19 patients were divided into hypertension and nonhypertension groups. The hypertension group was divided into well-controlled and poorly controlled subgroups based on blood pressure levels; moreover, hypertensive patients were also divided into ACEI/ARB and non-ACEI/ARB subgroups according to the administration of ACEI/ARB antihypertensive agents. The clinical characteristics of and inflammatory immune biomarker levels in the different groups of COVID-19 patients were compared, and the association between the combined effect of hypertension with ACEI/ARB antihypertensive agents and the severity of COVID-19 was examined. The results showed that the levels of aminotransferase (AST) and hs-cTnI were higher in the hypertension group compared with the nonhypertension group. The long-term use of ACEI/ARB agents in patients had statistically significantly lower AST, low-density lipoprotein cholesterol (LDL-C), and oxygen uptake and lower white cell count, neutrophil count, and levels of CD4, CD8, CRP, and PCT but without statistical significance. In addition, compared with COVID-19 patients without hypertension, hypertensive patients without the use of ACEI/ARB had a higher risk of developing severity of COVID-19 (for poorly controlled patients: OR = 3.97, 95% CI = 1.03-15.30; for well-controlled patients: OR = 6.48, 95% CI = 1.77-23.81). Hypertension could cause organ damage in COVID-19 patients, but the long-term use of ACEI/ARB agents may be beneficial to alleviate this injury.

17.
Sci Rep ; 11(1): 21413, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1493222

ABSTRACT

In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), called the EEMD-ARIMA-NARANN model, to perform time series modeling and forecasting based on the COVID-19 prevalence and mortality data from 28 February 2020 to 27 June 2020 in South Africa and Nigeria. By comparing the accuracy level of forecasting measurements with the basic ARIMA and NARANN models, it was shown that this novel data-driven hybrid model did a better job of capturing the dynamic changing trends of the target data than the others used in this work. Our proposed mixture technique can be deemed as a helpful policy-supportive tool to plan and provide medical supplies effectively. The overall confirmed cases and deaths were estimated to reach around 176,570 [95% uncertainty level (UL) 173,607 to 178,476] and 3454 (95% UL 3384 to 3487), respectively, in South Africa, along with 32,136 (95% UL 31,568 to 32,641) and 788 (95% UL 775 to 804) in Nigeria on 12 July 2020 using this data-driven EEMD-ARIMA-NARANN hybrid technique. The contributions of this study include three aspects. First, the proposed hybrid model can better capture the dynamic dependency characteristics compared with the individual models. Second, this new data-driven hybrid model is constructed in a more reasonable way relative to the traditional mixture model. Third, this proposed model may be generalized to estimate the epidemic patterns of COVID-19 in other regions.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Models, Statistical , Neural Networks, Computer , Pandemics/prevention & control , SARS-CoV-2 , COVID-19/transmission , COVID-19/virology , Data Accuracy , Forecasting/methods , Humans , Nigeria/epidemiology , Prevalence , South Africa/epidemiology , Uncertainty
18.
Front Psychol ; 12: 553234, 2021.
Article in English | MEDLINE | ID: covidwho-1485094

ABSTRACT

In February 2020, an inpatient in Peking University People's Hospital (PKUPH), China, was confirmed positive for the novel coronavirus. In this case, 143 hemodialysis patients were labeled as close contacts and required to be placed under the hospital-based group medical quarantine (HB-GMQ) for 2 weeks by the authorities. After the case was reported, false or misleading information about the case flourished on social media platforms, which led to infodemic. Under this context, PKUPH adopted patient-centered humanistic care to implement the HB-GMQ, through the synergy of administrative, healthcare, logistical, and other measures under the model of patient-centered care of the Massachusetts Medical Society (MMS). As a result, all the patients tided over the HB-GMQ with no COVID-19 infection and no unanticipated adverse events, and all met the criteria for lifting the HB-GMQ. According to the questionnaires taken during the HB-GMQ, a high level of satisfaction was found among the quarantined and no symptomatic increase of anxiety and depression in the patients before and during the HB-GMQ, by comparing the Zung self-rating anxiety scale (SAS) and self-rating depression scale (SDS) conducted in December 2019 and on the 12th day of the HB-GMQ. This article is to brief on PKUPH's experience in implementing patient-centered humanistic care tailored to hemodialysis patients under the HB-GMQ, and to validate the hypothesis that patient-centered humanistic care is effective and helpful to help them tide over the HB-GMQ, so as to shed light on how to implement the HB-GMQ and cope with the HB-GMQ-induced problems in other hospitals.

19.
Infect Drug Resist ; 14: 3849-3862, 2021.
Article in English | MEDLINE | ID: covidwho-1459502

ABSTRACT

Objective: We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS). Methods: The HFRS morbidity data from January 1995 to December 2020 were taken, and subsequently, the data were split into six different training and testing segments (including 12, 24, 36, 60, 84, and 108 holdout monthly data) to investigate its predictive ability of the TBATS method, and its forecasting performance was compared with the seasonal autoregressive integrated moving average (SARIMA). Results: The TBATS (0.27, {0,0}, -, {<12,4>}) and SARIMA (0,1,(1,3))(0,1,1)12 were selected as the best TBATS and SARIMA methods, respectively, for the 12-step ahead prediction. The mean absolute deviation, root mean square error, mean absolute percentage error, mean error rate, and root mean square percentage error were 91.799, 14.772, 123.653, 0.129, and 0.193, respectively, for the preferred TBATS method and were 144.734, 25.049, 161.671, 0.203, and 0.296, respectively, for the preferred SARIMA method. Likewise, for the 24-, 36-, 60-, 84-, and 108-step ahead predictions, the preferred TBATS methods produced smaller forecasting errors over the best SARIMA methods. Further validations also suggested that the TBATS model outperformed the Error-Trend-Seasonal framework, with little exception. HFRS had dual seasonal behaviors, peaking in May-June and November-December. Overall a notable decrease in the HFRS morbidity was seen during the study period (average annual percentage change=-6.767, 95% confidence intervals: -10.592 to -2.778), and yet different stages had different variation trends. Besides, the TBATS model predicted a plateau in the HFRS morbidity in the next ten years. Conclusion: The TBATS approach outperforms the SARIMA approach in estimating the long-term epidemic seasonality and trends of HFRS, which is capable of being deemed as a promising alternative to help stakeholders to inform future preventive policy or practical solutions to tackle the evolving scenarios.

20.
BMC Public Health ; 21(1): 1762, 2021 09 27.
Article in English | MEDLINE | ID: covidwho-1440921

ABSTRACT

BACKGROUND: The novel coronavirus SARS-CoV-2 (coronavirus disease 2019, COVID-19) has caused serious consequences on many aspects of social life throughout the world since the first case of pneumonia with unknown etiology was identified in Wuhan, Hubei province in China in December 2019. Note that the incubation period distribution is key to the prevention and control efforts of COVID-19. This study aimed to investigate the conditional distribution of the incubation period of COVID-19 given the age of infected cases and estimate its corresponding quantiles from the information of 2172 confirmed cases from 29 provinces outside Hubei in China. METHODS: We collected data on the infection dates, onset dates, and ages of the confirmed cases through February 16th, 2020. All the data were downloaded from the official websites of the health commission. As the epidemic was still ongoing at the time we collected data, the observations subject to biased sampling. To address this issue, we developed a new maximum likelihood method, which enables us to comprehensively study the effect of age on the incubation period. RESULTS: Based on the collected data, we found that the conditional quantiles of the incubation period distribution of COVID-19 vary by age. In detail, the high conditional quantiles of people in the middle age group are shorter than those of others while the low quantiles did not show the same differences. We estimated that the 0.95-th quantile related to people in the age group 23 ∼55 is less than 15 days. CONCLUSIONS: Observing that the conditional quantiles vary across age, we may take more precise measures for people of different ages. For example, we may consider carrying out an age-dependent quarantine duration in practice, rather than a uniform 14-days quarantine period. Remarkably, we may need to extend the current quarantine duration for people aged 0 ∼22 and over 55 because the related 0.95-th quantiles are much greater than 14 days.


Subject(s)
COVID-19 , Epidemics , China/epidemiology , Humans , Middle Aged , Quarantine , SARS-CoV-2
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