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1.
Frontiers in medicine ; 9, 2022.
Article in English | EuropePMC | ID: covidwho-1871809

ABSTRACT

Objective The long-term impact of COVID-19 on patient health has been a recent focus. This study aims to determine the persistent symptoms and psychological conditions of patients hospitalized with COVID-19 15 months after onset, that patients first developed symptoms. The potential risk factors were also explored. Methods A cohort of COVID-19 patients discharged from February 20, 2020 to March 31, 2020 was recruited. Follow-ups were conducted using validated questionnaires and psychological screening scales at 15 months after onset to evaluate the patients' health status. The risk factors for long-term health impacts and their associations with disease severity was analyzed. Findings 534 COVID-19 patients were enrolled. The median age of the patients was 62.0 years old (IQR 52.0–70.0) and 295 were female (55.2%). The median time from onset to follow-up was 460.0 (451.0–467.0) days. Sleep disturbance (18.5%, 99/534) and fatigue (17.2%, 92/534) were the most common persistent symptoms. 6.4% (34/534) of the patients had depression, 9.2% (49/534) were anxious, 13.0% (70/534) had insomnia and 4.7% (25/534) suffered from post-traumatic stress disorder (PTSD). Multivariate adjusted logistic regression analysis showed that glucocorticoid use during hospitalization (OR 3.58, 95% CI 1.12–11.44) was significantly associated with an increased risk of fatigue. The OR values for anxiety and sleep disorders were 2.36 (95% CI 1.07–5.20) and 2.16 (95% CI 1.13–4.14) in females to males. The OR value of PTSD was 25.6 (95% CI 3.3–198.4) in patients with persistent symptoms to those without persistent symptoms. No significant associations were observed between fatigue syndrome or adverse mental outcomes and disease severity. Conclusions 15-month follow-up in this study demonstrated the need of extended rehabilitation intervention for complete recovery in COVID-19 patients.

2.
Sustainable cities and society ; 2022.
Article in English | EuropePMC | ID: covidwho-1843022

ABSTRACT

In this paper, objective physical tests and subjective questionnaire surveys were used to study an office building in Beijing during the operation of the fresh air system in the summer before the coronavirus disease 2019 (COVID-19). This paper conducted long-term tests on indoor environmental parameters: air temperature, relative air humidity, air velocity, CO2 concentration, PM2.5 concentration, fresh air volume, and conducted a questionnaire survey on the satisfaction of indoor office workers with the indoor environment. The results showed that the indoor environmental parameters conformed to the design values specified in the relevant design standards, but the satisfaction of the indoor personnel with the indoor environmental parameters was generally low. The risk probability of infection of indoor personnel with the COVID-19 under two existing fresh air system operation modes was calculated and compared, and the results showed that the probability of infection was less than 5%. Gray correlation analysis of the measured data with the questionnaire results identified indoor air temperature and indoor air quality as the main factors affecting the subjective satisfaction of indoor personnel, which was consistent with the results of the questionnaire analysis. A new operation and maintenance method of the fresh air system was proposed for the regular epidemic prevention and control to ensure the normal operation of the office building and the health of the indoor personnel.

3.
SN Comput Sci ; 3(4): 269, 2022.
Article in English | MEDLINE | ID: covidwho-1821085

ABSTRACT

The coronavirus (COVID-19) pandemic has caused disastrous results in most countries of the world. It has rapidly spread across the globe with over 156 million cumulative confirmed cases and 3.264 million deaths to date, according to World Health Organization (WHO) Coronavirus Disease (COVID-19) Dashboard. With these huge amounts of causalities in the world, Geographic Information Systems (GIS) as a computer-based analyzer could help governments, experts, medical staff, and citizens to prevent and respond to the incidence. On the other hand, the COVID-19 pandemic involves many unknown parameters where most of them have a spatial dimension. Thus, spatial analysis and GIS could provide appropriate decision-making tools, predictive models, statistical methods, and new technologies for COVID-19 outbreak control, also help the people for avoiding direct contact and preserving social distance. This article aims to review the most promising categories of GIS-based solutions in this domain. We divided the solutions into ten classes including spatio-temporal analysis, SDSS approaches, geo-business, context-aware recommendation systems, participatory GIS and volunteered geographic information (VGI), internet of things (IoT), location-based service (LBS), web mapping, satellite imagery-based analysis, and waste management. The main contribution of this paper is proposing different geospatial guidelines that could provide reliable and useful protocols for COVID-19 outbreak control to minimize causalities, restrict incidence, establish effective urban communication, provide new approaches for business in lockdown situations, telehealth treatment, patient monitoring, adaptive decision making, and visualize trend analysis.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325284

ABSTRACT

Background: The phenomenon of COVID-19 patients tested positive for SARS-CoV-2 after discharge (redetectable as positive, RP) emerged globally. The data of incidence rate and risk factors for RP event and the clinical features of RP patients may provide recommendations for virus containment and discharge assessment for COVID-19. Methods: The baseline included 285 adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Guangzhou Eighth People's Hospital. We started the Observation on Jan 20, 2020, and acquired all their definite clinical outcome (becoming RP or keeping normal during post-discharge surveillance) by Mar 10, 2020. The dynamic clinical data of patients during observation were prospectively collected and analyzed. Univariate and multivariate-adjusted logistic regression were used to explore the risk factors related to RP events in COVID-19 patients. Results: By March 10, 27 (9.5%) discharged patients had tested positive for SARS-CoV-2 in their nasopharyngeal swab after a median duration of 7·0 days (IQR 5·0-8·0). Age, sex, epidemiological history, clinical symptoms and underlying diseases were similar between RP and non-RP patients (p>0.05). Compared to first admission, RP patients generally had milder clinical symptoms, lower viral load, shorter length of stay and improved pulmonary conditions at readmission (p<0.05). Elder RP patients (≥ 60 years old) were more likely to be symptomatic compared to younger patients (7/8, 87.5% vs. 3/19, 18.8%, p=0.001) at readmission. A prolonged duration of viral shedding (>10 days) during the first hospitalization [adjusted odds ratio [aOR]: 5.82, 95% confidence interval [CI]: 2.50-13.57 for N gene;aOR: 9.64, 95% CI: 3.91-23.73 for ORF gene] and higher Ct value (ORF) in the third week of the first hospitalization (aOR: 0.69;95% CI: 0.50-0.95) were associated with RP events. Conclusions: RP events occurred in nearly 10% of COVID-19 patients which deserves globally attention. During hospitalization, patients’ low efficiency of viral clearance was a risk factor for RP event. Elderly RP patients were more likely to develop clinical symptoms. To reduce the possibility of reinfection and readmission during the management of COVID-19, more rigorously monitoring on patients’ viral load should be carried out especially in elder patients and later stage of hospitalization.

6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-316041

ABSTRACT

The COVID-19, which belongs to the family of Coronaviridae and is large-scale outbreak in the whole world, is a public health emergency for human beings and brings some very harmful consequences in social and economic fields. In order to modelling the COVID-19 and develop the efficient control method corresponding to the contacting distance, this paper proposes an SEIR-type epidemic model with the contacting distance between the healthy individuals and the asymptomatic or symptomatic infected individuals, and the immigration rate of the healthy individuals, since the contacting distance and the immigration rate are two critical factors which determine the transmission of the COVID-19. Firstly, the threshold contacting distance and the threshold immigration rate are obtained by analyze the dynamical behaviors of the proposed SEIR-type epidemic model in order to control the COVID-19. The effect of the contacting distance and the immigration rate on the control of the COVID-19 are revealed based on ecological and epidemiological issues. The results show that the COVID-19 will be controlled while the contacting distance between the healthy individuals and the symptomatic infected individuals is larger than the threshold value A~ and the immigration rate is smaller than the threshold value ~ d. Secondly, the sensitivity analysis is conducted and the results show that the contacting distance and the immigration rate play an important role in controlling the COVID-19. Finally, the numerical test for Wuhan city are conducted and the conclusions show that the extinct lag decreases as the the contacting distance increase or the immigration rate decrease. Our study could give some reasonable suggestions for the health officials and the public.

7.
Arthritis Res Ther ; 24(1): 6, 2022 01 03.
Article in English | MEDLINE | ID: covidwho-1590005

ABSTRACT

BACKGROUND: Hydroxychloroquine (HCQ) has been recommended as a basic treatment for lupus nephritis (LN) during this decade based on its ability to improve LN-related renal immune-mediated inflammatory lesions. As a classical lysosomal inhibitor, HCQ may inhibit lysosomal degradation and disrupt protective autophagy in proximal tubular epithelial cells (PTECs). Therefore, the final renal effects of HCQ on LN need to be clarified. METHOD: HCQ was administered on spontaneous female MRL/lpr LN mice with severe proteinuria daily for 4 weeks. Moreover, the MRL/lpr mice with proteinuric LN were subjected to cisplatin-induced or unilateral ischemia/reperfusion (I/R)-induced acute kidney injury (AKI) after 2 weeks of HCQ preadministration. RESULTS: As expected, HCQ treatment increased the survival ratio and downregulated the levels of serum creatinine in the mice with LN, ameliorated renal lesions, and inhibited renal interstitial inflammation. Unexpectedly, HCQ preadministration significantly increased susceptibility to and delayed the recovery of AKI complicated by LN, as demonstrated by an increase in PTEC apoptosis and expression of the tubular injury marker KIM-1 as well as the retardation of PTEC replenishment. HCQ preadministration suppressed the proliferation of PTECs by arresting cells in G1/S phase and upregulated the expression of cell cycle inhibitors. Furthermore, HCQ preadministration disrupted the PTEC autophagy-lysosomal pathway and accelerated PTEC senescence. CONCLUSION: HCQ treatment may increase susceptibility and delay the recovery of AKI complicated by LN despite its ability to improve LN-related renal immune-mediated inflammatory lesions. The probable mechanism involves accelerated apoptosis and inhibited proliferation of PTECs via autophagy-lysosomal pathway disruption and senescence promotion.


Subject(s)
Acute Kidney Injury , Lupus Nephritis , Acute Kidney Injury/chemically induced , Animals , Female , Hydroxychloroquine/pharmacology , Kidney/pathology , Mice , Mice, Inbred MRL lpr
8.
Nat Med ; 26(6): 845-848, 2020 06.
Article in English | MEDLINE | ID: covidwho-1641979

ABSTRACT

We report acute antibody responses to SARS-CoV-2 in 285 patients with COVID-19. Within 19 days after symptom onset, 100% of patients tested positive for antiviral immunoglobulin-G (IgG). Seroconversion for IgG and IgM occurred simultaneously or sequentially. Both IgG and IgM titers plateaued within 6 days after seroconversion. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.


Subject(s)
Antibodies, Viral/blood , Antibody Formation/drug effects , Betacoronavirus/pathogenicity , Coronavirus Infections/drug therapy , Pneumonia, Viral/drug therapy , Adult , Aged , Antibody Formation/immunology , Antiviral Agents/therapeutic use , Betacoronavirus/genetics , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , SARS-CoV-2
9.
Nonlinear Dyn ; 107(3): 3065-3084, 2022.
Article in English | MEDLINE | ID: covidwho-1634949

ABSTRACT

COVID-19 is a public health emergency for human beings and brings some very harmful consequences in social and economic fields. In order to model COVID-19 and develop the effective control measures, this paper proposes an SEIR-type epidemic model with the contacting distance between the healthy individuals and the asymptomatic or symptomatic infected individuals, and the immigration rate of the healthy individuals since the contacting distance and the immigration rate are two critical factors which determine the transmission of COVID-19. Firstly, the threshold values of the contacting distance and the immigration rate are obtained to analyze the presented model. Secondly, based on the data from January 10, 2020, to March 18, 2020, for Wuhan city, all parameters are estimated. Finally, based on the estimated parameters, the sensitivity analysis and the numerical study are conducted. The results show that the contacting distance and the immigration rate play an important role in controlling COVID-19. Meanwhile, the extinct lag decreases as the contacting distance increases and/or the immigration rate decreases. Our study could give some reasonable suggestions for the health officials and the public and provide a theoretical issue for globally controlling the COVID-19 pandemic.

10.
Front Cell Dev Biol ; 9: 766142, 2021.
Article in English | MEDLINE | ID: covidwho-1497022

ABSTRACT

As an evolutionarily conserved cellular process, autophagy plays an essential role in the cellular metabolism of eukaryotes as well as in viral infection and pathogenesis. Under physiological conditions, autophagy is able to meet cellular energy needs and maintain cellular homeostasis through degrading long-lived cellular proteins and recycling damaged organelles. Upon viral infection, host autophagy could degrade invading viruses and initial innate immune response and facilitate viral antigen presentation, all of which contribute to preventing viral infection and pathogenesis. However, viruses have evolved a variety of strategies during a long evolutionary process, by which they can hijack and subvert host autophagy for their own benefits. In this review, we highlight the function of host autophagy in the key regulatory steps during viral infections and pathogenesis and discuss how the viruses hijack the host autophagy for their life cycle and pathogenesis. Further understanding the function of host autophagy in viral infection and pathogenesis contributes to the development of more specific therapeutic strategies to fight various infectious diseases, such as the coronavirus disease 2019 epidemic.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-291513

ABSTRACT

Background: The long-term impact of COVID-19 on patient health has been a recent focus. This study aims to determine the persistent symptoms and psychological conditions of patients hospitalized with COVID-19 15 months after onset. The potential risk factors were also explored.Methods: A cohort of COVID-19 patients discharged from February 20, 2020 to March 31, 2020 was recruited. Follow-ups were conducted using validated questionnaires and psychological screening scales at 15 months after onset to evaluate the patients’ health status. The risk factors for long-term health impacts and their associations with disease severity was analyzed.Findings: 534 COVID-19 patients were enrolled. The median age of the patients was 62.0 years old (IQR 52.0-70.0) and 295 were female (55.2%). The median time from onset to follow-up was 460.0 (451.0-467.0) days. Sleep disturbance (18.5%, 99/534) and fatigue (17.2%, 92/534) were the most common persistent symptoms. 6.4% (34/534) of the patients had depression, 9.2% (49/534) were anxious, 13.0% (70/534) had insomnia and 4.7% (25/534) suffered from posttraumatic stress disorder (PTSD). Multivariate adjusted logistic regression analysis showed that glucocorticoid use during hospitalization (OR 3.58, 95% CI 1.12-11.44) was significantly associated with an increased risk of fatigue. The OR values for anxiety and sleep disorders were 2.36 (95% CI 1.07-5.20) and 2.16 (95% CI 1.13-4.14) in females compared with males. The OR value of PTSD was 25.6 (95% CI 3.3-198.4) in patients with persistent symptoms to those without persistent symptoms. No significant associations were observed between fatigue syndrome or adverse mental outcomes and disease severity.Interpretation: 15-month follow-up in this study aroused the need of extended rehabilitation intervention for complete recovery in COVID-19 patients. Funding: None to declare. Declaration of Interest: All the authors declare no competing interests.Ethical Approval: The Research Ethics Committee of Shanghai Changzheng Hospital approved this study (2020SL007).

12.
Front Endocrinol (Lausanne) ; 12: 727419, 2021.
Article in English | MEDLINE | ID: covidwho-1444039

ABSTRACT

Background: Blood parameters, such as neutrophil-to-lymphocyte ratio, have been identified as reliable inflammatory markers with diagnostic and predictive value for the coronavirus disease 2019 (COVID-19). However, novel hematological parameters derived from high-density lipoprotein-cholesterol (HDL-C) have rarely been studied as indicators for the risk of poor outcomes in patients with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection. Here, we aimed to assess the prognostic value of these novel biomarkers in COVID-19 patients and the diabetes subgroup. Methods: We conducted a multicenter retrospective cohort study involving all hospitalized patients with COVID-19 from January to March 2020 in five hospitals in Wuhan, China. Demographics, clinical and laboratory findings, and outcomes were recorded. Neutrophil to HDL-C ratio (NHR), monocyte to HDL-C ratio (MHR), lymphocyte to HDL-C ratio (LHR), and platelet to HDL-C ratio (PHR) were investigated and compared in both the overall population and the subgroup with diabetes. The associations between blood parameters at admission with primary composite end-point events (including mechanical ventilation, admission to the intensive care unit, or death) were analyzed using Cox proportional hazards regression models. Receiver operating characteristic curves were used to compare the utility of different blood parameters. Results: Of 440 patients with COVID-19, 67 (15.2%) were critically ill. On admission, HDL-C concentration was decreased while NHR was high in patients with critical compared with non-critical COVID-19, and were independently associated with poor outcome as continuous variables in the overall population (HR: 0.213, 95% CI 0.090-0.507; HR: 1.066, 95% CI 1.030-1.103, respectively) after adjusting for confounding factors. Additionally, when HDL-C and NHR were examined as categorical variables, the HRs and 95% CIs for tertile 3 vs. tertile 1 were 0.280 (0.128-0.612) and 4.458 (1.817-10.938), respectively. Similar results were observed in the diabetes subgroup. ROC curves showed that the NHR had good performance in predicting worse outcomes. The cutoff point of the NHR was 5.50. However, the data in our present study could not confirm the possible predictive effect of LHR, MHR, and PHR on COVID-19 severity. Conclusion: Lower HDL-C concentrations and higher NHR at admission were observed in patients with critical COVID-19 than in those with noncritical COVID-19, and were significantly associated with a poor prognosis in COVID-19 patients as well as in the diabetes subgroup.


Subject(s)
COVID-19/blood , Cholesterol, HDL/blood , Diabetes Mellitus/blood , Aged , Biomarkers/blood , COVID-19/diagnosis , COVID-19/mortality , China , Diabetes Mellitus/diagnosis , Diabetes Mellitus/mortality , Female , Humans , Kaplan-Meier Estimate , Leukocytes/cytology , Male , Middle Aged , Prognosis , ROC Curve , Retrospective Studies , Severity of Illness Index
13.
J Med Internet Res ; 23(9): e31627, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1443997

ABSTRACT

BACKGROUND: eHealth literacy (EHL) refers to a variety of capabilities that enable individuals to obtain health information from electronic resources and apply it to solve health problems. With the digitization of health care and the wide availability of health apps, a more diverse range of eHealth skills is required to properly use such health facilities. Existing EHL measurements focus mainly on the skill of obtaining health information (Web 1.0), whereas skills for web-based interactions (Web 2.0) and self-managing health data and applying information (Web 3.0) have not been well measured. OBJECTIVE: This study aims to develop an EHL scale (eHLS) termed eHLS-Web3.0 comprising a comprehensive spectrum of Web 1.0, 2.0, and 3.0 skills to measure EHL, and evaluate its validity and reliability along with the measurement invariance among college students. METHODS: In study 1, 421 Chinese college students (mean age 20.5, SD 1.4 years; 51.8% female) and 8 health experts (mean age 38.3, SD 5.9 years; 87.5% female) were involved to develop the eHLS-Web3.0. The scale development included three steps: item pool generation, content validation, and exploratory factor analysis. In study 2, 741 college students (mean age 21.3, SD 1.4 years; 52.2% female) were recruited from 4 Chinese cities to validate the newly developed eHLS-Web3.0. The construct validity, convergent validity, concurrent validity, internal consistency reliability, test-retest reliability, and measurement invariance across genders, majors, and regions were examined by a series of statistical analyses, including confirmatory factor analysis (CFA) and multigroup CFAs using SPSS and Mplus software packages. RESULTS: Based on the item pool of 374 statements collected during the conceptual development, 24 items (4-10 items per subscale) were generated and adjusted after cognitive testing and content validity examination. Through exploratory factor analysis, a 3-factor eHLS-Web3.0 was finally developed, and it included acquisition (8 items), verification (6 items), and application (10 items). In study 2, CFAs supported the construct validity of the 24-item 3D eHLS-Web3.0 (χ2244=903.076, χ2244=3.701, comparative fit index=0.924, Tucker-Lewis index=0.914, root mean square error of approximation [RMSEA]=0.06, and standardized root mean residual [SRMR]=0.051). The average variance extracted (AVE) value of 0.58 and high correlation between eHLS-Web3.0 subscales and the eHealth Literacy Scale (r=0.725-0.880, P<.001) indicated the convergent validity and concurrent validity of the eHLS-Web3.0. The results also indicated satisfactory internal consistency reliability (α=.976, ρ=0.934-0.956) and test-retest reliability (r=0.858, P<.001) of the scale. Multigroup CFA demonstrated the 24-item eHLS-Web3.0 to be invariant at all configural, metric, strength, and structural levels across genders (female and male), majors (sport-related, medical, and general), and regions (Yinchuan, Kunming, Xiamen, and Beijing). CONCLUSIONS: The 24-item 3D eHLS-Web3.0 proved to be a reliable and valid measurement tool for EHL in the Web 3.0 context among Chinese college students.


Subject(s)
Health Literacy , Telemedicine , Adult , Factor Analysis, Statistical , Female , Humans , Male , Psychometrics , Reproducibility of Results , Surveys and Questionnaires , Young Adult
14.
International Journal of Operations & Production Management ; 41(8):1350-1378, 2021.
Article in English | ProQuest Central | ID: covidwho-1406530

ABSTRACT

PurposeDrawing on the transactional cost economics (TCE) perspective, we aim to investigate the effects of the balance and imbalance between contractual and relational governance on a firm's bridging responses to supply chain disruptions. By adopting the institutionally contingent perspective, we further examine the moderating effect of cultural distance on the relationship between governance mechanisms and bridging responses.Design/methodology/approachBased on data collected from 183 firms in China, we use polynomial regression and response surface analyses to test our research model.FindingsThe bridging responses increase along with an increasing balance level between contractual and relational governance and decrease along with an increasing imbalance level between contractual and relational governance. Moreover, the positive effect of balance between contractual and relational governance is strengthened by a large cultural distance. We also find that a large cultural distance amplifies the negative effect of the combination of high relational governance and low contractual governance yet weakens that of the combination of high contractual governance and low relational governance.Originality/valueOur study provides nuanced insights into the effects of the balance and imbalance between contractual and relational governance on bridging responses and into the cultural boundary conditions under which these effects vary.

15.
Ann Palliat Med ; 10(7): 8094-8102, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1344624

ABSTRACT

BACKGROUND: There have been few reports on cancer patients with COVID-19 since its outbreak. Our study aimed to understand the clinical features of cancer patients with COVID-19 and determine the impact of surgery and chemotherapy on the patients' conditions. METHODS: Seventy COVID-19 patients from Renmin Hospital of Wuhan University, including 18 cancer patients, were enrolled in this study. Patients were classified into moderate or severe cases of COVID-19 and as well as non-cancer or cancer patients. Cancer patients were further grouped into Group A (prevalent cases with cancer history) and Group B (incident cases who underwent cancer treatment recently). Laboratory results were analyzed to determine whether cancer-related surgery and chemotherapy worsened the condition of cancer patients. The patients presented with clinical symptoms of COVID-19, including fever, dry cough, and polypnea; blood tests also revealed decreased lymphocyte counts and cellular immune function, and examination of CT scans revealed patchy ground-glass opacity of lungs. RESULTS: The results showed a significant difference (P<0.05) in levels of CD3 CD4 T lymphocytes and D-dimer between non-cancer and cancer patients with moderate COVID-19; there was also a significant difference (P<0.05) in levels of D-dimer between non-cancer and cancer patients with severe COVID-19. Except for liver function, there was no significant difference (P>0.05) between cancer patients in Group A and B with moderate COVID-19. A significant difference (P<0.05) in neutrophil-to-lymphocyte ratio (NLR) and CD4 T lymphocytes was observed between cancer patients with moderate COVID-19 and those with severe COVID-19. CONCLUSIONS: The results indicated that chemotherapy and surgery might not worsen the conditions of COVID-19 patients. NLR and CD4 T lymphocyte might be used as effective indicators for the conditions of cancer patients with COVID-19.


Subject(s)
COVID-19 , Neoplasms , Humans , Lymphocytes , Neutrophils , Retrospective Studies , SARS-CoV-2
16.
Journal of the American Statistical Association ; : 1-32, 2021.
Article in English | Academic Search Complete | ID: covidwho-1243358

ABSTRACT

Motivated by recent work studying massive functional data, such as the COVID-19 data, we propose a new dynamic interaction semiparametric function-on-scalar (DISeF) model. The proposed model is useful to explore the dynamic interaction among a set of covariates and their effects on the functional response. The proposed model includes many important models investigated recently as special cases. By tensor product B-spline approximating the unknown bivariate coefficient functions, a three-step efficient estimation procedure is developed to iteratively estimate bivariate varying-coefficient functions, the vector of index parameters, and the covariance functions of random effects. We also establish the asymptotic properties of the estimators including the convergence rate and their asymptotic distributions. In addition, we develop a test statistic to check whether the dynamic interaction varies with time/spatial locations, and we prove the asymptotic normality of the test statistic. The finite sample performance of our proposed method and of the test statistic are investigated with several simulation studies. Our proposed DISeF model is also used to analyze the COVID-19 data and the ADNI data. In both applications, hypothesis testing shows that the bivariate varying-coefficient functions significantly vary with the index and the time/spatial locations. For instance, we find that the interaction effect of the population ageing and the socio-economic covariates, such as the number of hospital beds, physicians, nurses per 1,000 people and GDP per capita, on the COVID-19 mortality rate varies in different periods of the COVID-19 pandemic. The healthcare infrastructure index related to the COVID-19 mortality rate is also obtained for 141 countries estimated based on the proposed DISeF model. [ABSTRACT FROM AUTHOR] Copyright of Journal of the American Statistical Association is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

17.
Transbound Emerg Dis ; 69(2): 549-558, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1096940

ABSTRACT

Epicentres are the focus of COVID-19 research, whereas emerging regions with mainly imported cases due to population movement are often neglected. Classical compartmental models are useful, however, likely oversimplify the complexity when studying epidemics. This study aimed to develop a multi-regional, hierarchical-tier mathematical model for better understanding the complexity and heterogeneity of COVID-19 spread and control. By incorporating the epidemiological and population flow data, we have successfully constructed a multi-regional, hierarchical-tier SLIHR model. With this model, we revealed insight into how COVID-19 was spread from the epicentre Wuhan to other regions in Mainland China based on the large population flow network data. By comprehensive analysis of the effects of different control measures, we identified that Level 1 emergency response, community prevention and application of big data tools significantly correlate with the effectiveness of local epidemic containment across different provinces of China outside the epicentre. In conclusion, our multi-regional, hierarchical-tier SLIHR model revealed insight into how COVID-19 spread from the epicentre Wuhan to other regions of China, and the subsequent control of local epidemics. These findings bear important implications for many other countries and regions to better understand and respond to their local epidemics associated with the ongoing COVID-19 pandemic.


Subject(s)
COVID-19 , Epidemics , Animals , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/veterinary , China/epidemiology , Cities , Epidemics/prevention & control , Models, Theoretical , Pandemics/prevention & control
18.
J Infect Public Health ; 14(2): 201-205, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1042961

ABSTRACT

IMPORTANCE: The infection of medical personnel with COVID-19 was a disaster for both patients and doctors. However, some effective measures can prevent medical staff from becoming infected. This article introduces those measures and thus provides a reference for other hospitals. OBJECTIVE: In order to reduce the risk of occupational exposure and of the infection of medical staff, this article analyzed the factors, causes and experience of medical personnel on their occupational exposure to COVID-19. Some effective and targeted intervention measures can be implemented in order to avoid the occupational exposure of medical staff to COVID-19. EVIDENCE REVIEW: In this single-center case series involving 196 medical personnel, occupational exposure to COVID-19 was present. Nursing staff accounted for 67.35% of those cases. The relationships with an exposure source were found to be as follows: doctors and patients (87.24%), colleagues (10.20%), and roommates (2.55%). Occupational exposure was found to be present in the clinical department, radiology department, central sterile supply department, as well as in the outpatient clinics and operating rooms. The non-surgical departments accounted for 72.96% and direct contact accounted for 84.69% while failure to wear surgical masks (84.18%) and operating on the patient without wearing goggles/face shield (8.16%) were the main causes of occupational exposure. The occurrence of occupational exposure to COVID-19 declined to 0.19% after an extensive and comprehensive intervention program. CONCLUSIONS AND RELEVANCE: Some effective measures such as hand hygiene, wearing surgical masks in and around the hospital, reasonable use of goggles/face screens, raising awareness of protective measures, minimizing the number of elective operations, strengthening training as well as many other control measures were instrumental in reducing occupational exposure. For any medical institution there is room for improvement in terms of personal protection to reduce occupational exposure.


Subject(s)
COVID-19/prevention & control , Hand Hygiene , Health Personnel , Masks , Occupational Exposure/prevention & control , Hospitals , Humans , Infection Control/methods , Infectious Disease Transmission, Patient-to-Professional/prevention & control
19.
Int J Hyg Environ Health ; 231: 113638, 2021 01.
Article in English | MEDLINE | ID: covidwho-865729

ABSTRACT

Evidence concerning short-term acute association between air pollutants and hospital admissions for respiratory diseases among children in a multi-city setting was quite limited. We conducted a time-series analysis to evaluate the association of six common air pollutants with hospital admissions for respiratory diseases among children aged 0-14 years in 4 cities (Guangzhou, Shanghai, Wuhan and Xining), China during 2013-2018. We used generalized additive models incorporating penalized smoothing splines and random-effect meta-analysis to calculate city-specific and pooled estimates, respectively. The exposure-response relationship curves were fitted using the cubic spline regression. Subgroup analyses by gender, age, season and disease subtype were also performed. A total of 183,036 respiratory diseases hospitalizations were recorded during the study period, and 94.1% of the cases were acute respiratory infections. Overall, we observed that increased levels of air pollutants except O3, were significantly associated with increased hospital admissions for respiratory disease. Each 10 µg/m3 increase in PM2.5, SO2 and NO2 at lag 07, PM10 at lag 03 and per 1 mg/m3 increase in CO at lag 01 corresponded to increments of 1.19%, 3.58%, 2.23%, 0.51% and 6.10% in total hospitalizations, respectively. Generally, exposure-response relationships of PM2.5 and SO2 in Guangzhou, SO2, NO2 and CO in Wuhan, as well as SO2 and NO2 in Xining with respiratory disease hospitalizations were also found. Moreover, the adverse effects of these pollutants apart from PM2.5 in certain cities remained significant even at exposure levels below the current Chinese Ambient Air Quality Standards (CAAQS) Grade II. Children aged 4-14 years appeared to be more vulnerable to the adverse effects of PM2.5, SO2 and NO2. Furthermore, with the exception of O3, the associations were stronger in cold season than in warm season. Short-term exposure to PM2.5, SO2, NO2 and CO were associated, in dose-responsive manners, with increased risks of hospitalizations for childhood respiratory diseases, and adverse effects of air pollutants except PM2.5 held even at exposure levels below the current CAAQS Grade II in certain cities.


Subject(s)
Air Pollutants , Air Pollution , Respiratory Tract Infections , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Child , China/epidemiology , Cities , Hospitalization , Hospitals , Humans , Particulate Matter/adverse effects , Particulate Matter/analysis , Respiratory Tract Infections/epidemiology
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