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1.
Medicina (Kaunas) ; 57(12)2021 Nov 30.
Article in English | MEDLINE | ID: covidwho-1598246

ABSTRACT

Background and Objectives: This study aimed to assess the effect of neck stabilization exercise on respiratory function in stroke patients through longitudinal observation and determine whether there is a difference in its effect based on the side of paralysis in the patients. It is difficult to observe the amount of change observed in individuals and groups as most intergroup comparison studies only use mean values. To address these shortcomings, this study adopted a hierarchical linear model (HLM) in our trajectory analysis. Materials and Methods: We conducted neck stabilization training three times a week for four weeks in a single group of 21 stroke patients. To evaluate respiratory function, their forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), forced expiration ratio (FEV1/FVC), and peak cough flow (PCF) were measured. Data analysis was performed using HLM 8.0. Results: A significant increase was found in the respiratory function after neck stabilization training (p < 0.05). While neck stabilization training overall was longitudinally effective, the growth rate of respiratory function in left-sided paralytic patients was less than the whole group value. Conversely, the growth rate of respiratory function in right-sided paralytic patients was greater than the whole group value. Conclusions: This study demonstrated that neck stabilization training is longitudinally effective in improving respiratory function in stroke patients. Additionally, the growth rate of respiratory function was greater in patients with right side paralysis than in patients with left side paralysis.


Subject(s)
Respiratory Muscles , Stroke , Exercise Therapy , Humans , Linear Models , Respiration , Stroke/complications
2.
Int J Environ Res Public Health ; 18(24)2021 12 07.
Article in English | MEDLINE | ID: covidwho-1593858

ABSTRACT

The aim was to examine the association between oral health-related quality of life and loneliness and perceived as well as objective social isolation. Data were used from a nationally representative survey with n = 3075 (late Summer 2021). The established Oral Health Impact Profile (OHIP-G5) was used to quantify oral health-related quality of life. Moreover, established tools were used to quantify the outcome measures (De Jong Gierveld loneliness scale, Bude/Lantermann scale and Lubben Social Network Scale). It was adjusted for several covariates in regression analysis. Linear regressions showed that low oral health-related quality of life is associated with higher loneliness (B = 0.03, p < 0.001), higher perceived social isolation (B = 0.06, p < 0.001) and higher objective social isolation (B = 0.07, p < 0.05). Further regressions were performed (e.g., stratified by denture usage). Our study stressed the importance of low oral health-related quality of life for loneliness and social isolation (both perceived and objective). This knowledge is important to address individuals at risk. Future studies should clarify the underlying mechanisms.


Subject(s)
Loneliness , Quality of Life , Humans , Linear Models , Social Isolation , Surveys and Questionnaires
3.
Rural Remote Health ; 21(3): 6596, 2021 07.
Article in English | MEDLINE | ID: covidwho-1579427

ABSTRACT

INTRODUCTION: Face masks are widely recommended as a COVID-19 prevention strategy. State mask mandates have generally reduced the spread of the disease, but decisions to wear a mask depend on many factors. Recent increases in case rates in rural areas following initial outbreaks in more densely populated areas highlight the need to focus on prevention and education. Messaging about disease risk has faced challenges in rural areas in the past. While surges in cases within some communities are likely an impetus for behavior change, rising case rates likely explain only part of mask-wearing decisions. The current study examined the relationship between county-level indicators of rurality and mask wearing in the USA. METHODS: National data from the New York Times' COVID-19 cross-sectional mask survey was used to identify the percentage of a county's residents who reported always/frequently wearing a mask (2-14 July 2020). The New York Times' COVID-19 data repository was used to calculate county-level daily case rates for the 2 weeks preceding the mask survey (15 June - 1 July 2020), and defined county rurality using the Index of Relative Rurality (n=3103 counties). Multivariate linear regression was used to predict mask wearing across levels of rurality. The model was adjusted for daily case rates and other relevant county-level confounders, including county-level indicators of age, race/ethnicity, gender, political partisanship, income inequality, and whether each county was subject to a statewide mask mandate. RESULTS: Large clusters of counties with high rurality and low mask wearing were observed in the Midwest, upper Midwest, and mountainous West. Holding daily case rates and other county characteristics constant, the predicted probability of wearing a mask decreased significantly as counties became more rural (β=-0.560; p<0.0001). CONCLUSION: Upticks in COVID-19 cases and deaths in rural areas are expected to continue, and localized outbreaks will likely occur indefinitely. The present findings highlight the need to better understand the mechanisms underlying perceptions of COVID-19 risk in rural areas. Dissemination of scientifically correct and consistent information is critical during national emergencies.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Health Status Disparities , Masks/trends , Rural Population/trends , Cross-Sectional Studies , Female , Humans , Linear Models , Male , Severity of Illness Index , Socioeconomic Factors
4.
Sci Rep ; 11(1): 24449, 2021 12 27.
Article in English | MEDLINE | ID: covidwho-1585776

ABSTRACT

Syndromic surveillance systems monitor disease indicators to detect emergence of diseases and track their progression. Here, we report on a rapidly deployed active syndromic surveillance system for tracking COVID-19 in Israel. The system was a novel combination of active and passive components: Ads were shown to people searching for COVID-19 symptoms on the Google search engine. Those who clicked on the ads were referred to a chat bot which helped them decide whether they needed urgent medical care. Through its conversion optimization mechanism, the ad system was guided to focus on those people who required such care. Over 6 months, the ads were shown approximately 214,000 times and clicked on 12,000 times, and 722 people were informed they needed urgent care. Click rates on ads and the fraction of people deemed to require urgent care were correlated with the hospitalization rate ([Formula: see text] and [Formula: see text], respectively) with a lead time of 9 days. Males and younger people were more likely to use the system, and younger people were more likely to be determined to require urgent care (slope: [Formula: see text], [Formula: see text]). Thus, the system can assist in predicting case numbers and hospital load at a significant lead time and, simultaneously, help people determine if they need medical care.


Subject(s)
COVID-19/epidemiology , Sentinel Surveillance , Ambulatory Care/statistics & numerical data , COVID-19/pathology , COVID-19/virology , Hospitalization/statistics & numerical data , Humans , Israel/epidemiology , Linear Models , SARS-CoV-2/isolation & purification , Search Engine
5.
Int J Mol Sci ; 23(1)2021 Dec 22.
Article in English | MEDLINE | ID: covidwho-1580701

ABSTRACT

Using drugs to treat COVID-19 symptoms may induce adverse effects and modify patient outcomes. These adverse events may be further aggravated in obese patients, who often present different illnesses such as metabolic-associated fatty liver disease. In Rennes University Hospital, several drug such as hydroxychloroquine (HCQ) have been used in the clinical trial HARMONICOV to treat COVID-19 patients, including obese patients. The aim of this study is to determine whether HCQ metabolism and hepatotoxicity are worsened in obese patients using an in vivo/in vitro approach. Liquid chromatography high resolution mass spectrometry in combination with untargeted screening and molecular networking were employed to study drug metabolism in vivo (patient's plasma) and in vitro (HepaRG cells and RPTEC cells). In addition, HepaRG cells model were used to reproduce pathophysiological features of obese patient metabolism, i.e., in the condition of hepatic steatosis. The metabolic signature of HCQ was modified in HepaRG cells cultured under a steatosis condition and a new metabolite was detected (carboxychloroquine). The RPTEC model was found to produce only one metabolite. A higher cytotoxicity of HCQ was observed in HepaRG cells exposed to exogenous fatty acids, while neutral lipid accumulation (steatosis) was further enhanced in these cells. These in vitro data were compared with the biological parameters of 17 COVID-19 patients treated with HCQ included in the HARMONICOV cohort. Overall, our data suggest that steatosis may be a risk factor for altered drug metabolism and possibly toxicity of HCQ.


Subject(s)
Antiviral Agents/adverse effects , Antiviral Agents/metabolism , COVID-19/drug therapy , Hydroxychloroquine/adverse effects , Hydroxychloroquine/metabolism , Aged , Antiviral Agents/therapeutic use , COVID-19/complications , COVID-19/metabolism , Cell Line , Cell Survival/drug effects , Chemical and Drug Induced Liver Injury/metabolism , Correlation of Data , Drug-Related Side Effects and Adverse Reactions , Fatty Acids/pharmacology , Fatty Liver/complications , Fatty Liver/metabolism , Female , Humans , Hydroxychloroquine/therapeutic use , Linear Models , Male , Metabolic Networks and Pathways , Middle Aged , Obesity/complications , Obesity/metabolism , Risk Factors
6.
Ann Med ; 53(1): 181-188, 2021 12.
Article in English | MEDLINE | ID: covidwho-1575964

ABSTRACT

OBJECTIVE: To illustrate the effect of corticosteroids and heparin, respectively, on coronavirus disease 2019 (COVID-19) patients' CD8+ T cells and D-dimer. METHODS: In this retrospective cohort study involving 866 participants diagnosed with COVID-19, patients were grouped by severity. Generalized additive models were established to explore the time-course association of representative parameters of coagulation, inflammation and immunity. Segmented regression was performed to examine the influence of corticosteroids and heparin upon CD8+ T cell and D-dimer, respectively. RESULTS: There were 541 moderate, 169 severe and 156 critically ill patients involved in the study. Synchronous changes of levels of NLR, D-dimer and CD8+ T cell in critically ill patients were observed. Administration of methylprednisolone before 14 DFS compared with those after 14 DFS (ß = 0.154%, 95% CI=(0, 0.302), p=.048) or a dose lower than 40 mg per day compared with those equals to 40 mg per day (ß = 0.163%, 95% CI=(0.027, 0.295), p=.020) significantly increased the rising rate of CD8+ T cell in 14-56 DFS. CONCLUSIONS: The parameters of coagulation, inflammation and immunity were longitudinally correlated, and an early low-dose corticosteroid treatment accelerated the regaining of CD8+ T cell to help battle against SARS-Cov-2 in critical cases of COVID-19.


Subject(s)
CD8-Positive T-Lymphocytes/drug effects , COVID-19/drug therapy , Glucocorticoids/administration & dosage , Inflammation/drug therapy , Adult , Aged , Aged, 80 and over , Blood Coagulation/drug effects , Blood Coagulation/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19/blood , COVID-19/diagnosis , COVID-19/immunology , Dose-Response Relationship, Drug , Female , Fibrin Fibrinogen Degradation Products/analysis , Fibrin Fibrinogen Degradation Products/immunology , Heparin/administration & dosage , Humans , Inflammation/blood , Inflammation/diagnosis , Inflammation/immunology , Linear Models , Longitudinal Studies , Lymphocyte Count , Male , Methylprednisolone/administration & dosage , Middle Aged , Models, Biological , Retrospective Studies , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Severity of Illness Index , Time Factors , Time-to-Treatment , Young Adult
7.
Gac Med Mex ; 157(3): 271-276, 2021.
Article in English | MEDLINE | ID: covidwho-1535084

ABSTRACT

INTRODUCTION: In December 2019, a new coronavirus emerged in Wuhan, China, which has become a global health problem. OBJECTIVEs: To estimate how many daily COVID-19 deaths per 100,000 population could have been avoided if each one of five restrictive measures had been implemented at the time the first case was diagnosed, and to estimate a multiple linear regression model predictive of the number of deaths per 100,000 population. METHODS: A simple linear regression was performed between the days elapsed since the first COVID-19 diagnosed case, implementation of each one of the five restrictive measures carried out by the 39 European studied countries, the number of hospital beds per 1,000 population (independent variables) and the number of COVID-19 deaths per 100,000 population. RESULTS: For each day elapsed from the first COVID-19 reported case to the adoption of restrictive measures, between 0.611 (p = 0.004) and 1.863 (p = 0.000) patients died per 100,000 population, depending on the implemented measure. CONCLUSIONS: Restrictive measures and social distancing, as well as promptness of their implementation, are necessary for achieving a decrease in COVID-19 infections and mortality.


Subject(s)
COVID-19/prevention & control , Physical Distancing , COVID-19/epidemiology , COVID-19/mortality , Europe/epidemiology , Humans , Linear Models , Time Factors
8.
Gac Med Mex ; 157(3): 231-236, 2021.
Article in English | MEDLINE | ID: covidwho-1535078

ABSTRACT

INTRODUCTION: The scarcity of person-centered applications aimed at developing awareness on the risk posed by the COVID-19 pandemic, stimulates the exploration and creation of preventive tools that are accessible to the population. OBJECTIVE: To develop a predictive model that allows evaluating the risk of mortality in the event of SARS-CoV-2 virus infection. METHODS: Exploration of public data from 16,000 COVID-19-positive patients to generate an efficient discriminant model, evaluated with a score function and expressed by a self-rated preventive interest questionnaire. RESULTS: A useful linear function was obtained with a discriminant capacity of 0.845; internal validation with bootstrap and external validation, with 25 % of tested patients showing marginal differences. CONCLUSION: The predictive model with statistical support, based on 15 accessible questions, can become a structured prevention tool.


Subject(s)
COVID-19/prevention & control , Models, Statistical , Adolescent , Adult , Aged , COVID-19/mortality , Child , Child, Preschool , Discriminant Analysis , Female , Humans , Infant , Linear Models , Male , Middle Aged , Risk , Young Adult
10.
Sci Rep ; 10(1): 16598, 2020 10 06.
Article in English | MEDLINE | ID: covidwho-1493167

ABSTRACT

We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic models characterizing the basic reproduction number [Formula: see text] for each social media platform. Moreover, we identify information spreading from questionable sources, finding different volumes of misinformation in each platform. However, information from both reliable and questionable sources do not present different spreading patterns. Finally, we provide platform-dependent numerical estimates of rumors' amplification.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Social Media , Basic Reproduction Number , COVID-19 , Coronavirus Infections/virology , Data Analysis , Humans , Information Dissemination , Linear Models , Neural Networks, Computer , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2 , Social Behavior
11.
Sci Rep ; 11(1): 21248, 2021 10 28.
Article in English | MEDLINE | ID: covidwho-1493206

ABSTRACT

The COVID-19 pandemic was an inevitable outcome of a globalized world in which a highly infective disease is able to reach every country in a matter of weeks. While lockdowns and strong mobility restrictions have proven to be efficient to contain the exponential transmission of the virus, its pervasiveness has made it impossible for economies to maintain this kind of measures in time. Understanding precisely how the spread of the virus occurs from a territorial perspective is crucial not only to prevent further infections but also to help with policy design regarding human mobility. From the large spatial differences in the behavior of the virus spread we can unveil which areas have been more vulnerable to it and why, and with this information try to assess the risk that each community has to suffer a future outbreak of infection. In this work we have analyzed the geographical distribution of the cumulative incidence during the first wave of the pandemic in the region of Galicia (north western part of Spain), and developed a mathematical approach that assigns a risk factor for each of the different municipalities that compose the region. This risk factor is independent of the actual evolution of the pandemic and incorporates geographic and demographic information. The comparison with empirical information from the first pandemic wave demonstrates the validity of the method. Our results can potentially be used to design appropriate preventive policies that help to contain the virus.


Subject(s)
COVID-19/epidemiology , Pandemics , SARS-CoV-2 , COVID-19/transmission , Computer Simulation , Demography , Humans , Incidence , Linear Models , Models, Statistical , Pandemics/statistics & numerical data , Risk Factors , Spain/epidemiology
12.
Front Immunol ; 12: 760288, 2021.
Article in English | MEDLINE | ID: covidwho-1488433

ABSTRACT

Both age and obesity are leading risk factors for severe coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Specifically, although most infections occur in individuals under the age of 55 years, 95% of hospitalizations, admissions to the intensive care unit, and deaths occur in those over the age of 55 years. Moreover, hospitalized COVID-19 patients have a higher prevalence of obesity. It is generally believed that chronic low-grade inflammation and dysregulated innate and adaptive immune responses that are associated with aging and obesity are responsible for this elevated risk of severe disease. However, the impact of advanced age and obesity on the host response to SARS-CoV-2 infection remains poorly defined. In this study, we assessed changes in the concentration of soluble immune mediators, IgG antibody titers, frequency of circulating immune cells, and cytokine responses to mitogen stimulation as a function of BMI and age. We detected significant negative correlations between BMI and myeloid immune cell subsets that were more pronounced in aged patients. Similarly, inflammatory cytokine production by monocytes was also negatively correlated with BMI in aged patients. These data suggest that the BMI-dependent impact on host response to SARS-CoV-2 is more pronounced on innate responses of aged patients.


Subject(s)
Aging/immunology , Body Mass Index , COVID-19/pathology , Obesity/pathology , SARS-CoV-2/immunology , Adaptive Immunity , Adult , Aged , Aged, 80 and over , Antibodies, Viral/immunology , Cytokines/immunology , Female , Hospitalization , Humans , Immunity, Innate , Linear Models , Male , Middle Aged , Monocytes/immunology , Young Adult
13.
Sci Rep ; 11(1): 20654, 2021 10 21.
Article in English | MEDLINE | ID: covidwho-1479818

ABSTRACT

During the coronavirus disease 2019 (COVID-19) pandemic, gun violence (GV) in the United States (U.S.) was postulated to increase strain on already taxed healthcare resources, such as blood products, intensive care beds, personal protective equipment, and even hospital staff. This report aims to estimate the relative risk of GV in the U.S. during the pandemic compared to before the pandemic. Daily police reports corresponding to gun-related injuries and deaths in the 50 states and the District of Columbia from February 1st, 2019, to March 31st, 2021 were obtained from the GV Archive. Generalized linear mixed-effects models in the form of Poisson regression analysis were utilized to estimate the state-specific rates of GV. Nationally, GV rates were 30% higher between March 01, 2020, and March 31, 2021 (during the pandemic), compared to the same period in 2019 (before the pandemic) [intensity ratio (IR) = 1.30; 95% CI 1.29, 1.32; p < 0.0001]. The risk of GV was significantly higher in 28 states and significantly lower in only one state. National and state-specific rates of GV were higher during the COVID-19 pandemic compared to the same timeframe 1 year prior. State-specific steps to mitigate violence, or at a minimum adequately prepare for its toll during the COVID-19 pandemic, should be taken.


Subject(s)
COVID-19/epidemiology , Gun Violence , Crime , Databases, Factual , Firearms , Humans , Incidence , Linear Models , Normal Distribution , Pandemics , Poisson Distribution , United States
14.
Cell ; 184(23): 5699-5714.e11, 2021 11 11.
Article in English | MEDLINE | ID: covidwho-1466093

ABSTRACT

Extension of the interval between vaccine doses for the BNT162b2 mRNA vaccine was introduced in the United Kingdom to accelerate population coverage with a single dose. At this time, trial data were lacking, and we addressed this in a study of United Kingdom healthcare workers. The first vaccine dose induced protection from infection from the circulating alpha (B.1.1.7) variant over several weeks. In a substudy of 589 individuals, we show that this single dose induces severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibody (NAb) responses and a sustained B and T cell response to the spike protein. NAb levels were higher after the extended dosing interval (6-14 weeks) compared with the conventional 3- to 4-week regimen, accompanied by enrichment of CD4+ T cells expressing interleukin-2 (IL-2). Prior SARS-CoV-2 infection amplified and accelerated the response. These data on dynamic cellular and humoral responses indicate that extension of the dosing interval is an effective immunogenic protocol.


Subject(s)
COVID-19 Vaccines/immunology , Vaccines, Synthetic/immunology , Adult , Aged , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , COVID-19/blood , COVID-19/immunology , COVID-19/virology , Cross-Priming/immunology , Dose-Response Relationship, Immunologic , Female , Humans , Immunity , Immunoglobulin G/immunology , Linear Models , Male , Middle Aged , Reference Standards , SARS-CoV-2/immunology , T-Lymphocytes/immunology , Treatment Outcome , Young Adult
15.
PLoS One ; 16(10): e0258379, 2021.
Article in English | MEDLINE | ID: covidwho-1463316

ABSTRACT

During the outbreak of the COVID-19 pandemic, Non-Pharmaceutical and Pharmaceutical treatments were alternative strategies for governments to intervene. Though many of these intervention methods proved to be effective to stop the spread of COVID-19, i.e., lockdown and curfew, they also posed risk to the economy; in such a scenario, an analysis on how to strike a balance becomes urgent. Our research leverages the mobility big data from the University of Maryland COVID-19 Impact Analysis Platform and employs the Generalized Additive Model (GAM), to understand how the social demographic variables, NPTs (Non-Pharmaceutical Treatments) and PTs (Pharmaceutical Treatments) affect the New Death Rate (NDR) at county-level. We also portray the mutual and interactive effects of NPTs and PTs on NDR. Our results show that there exists a specific usage rate of PTs where its marginal effect starts to suppress the NDR growth, and this specific rate can be reduced through implementing the NPTs.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/methods , Models, Statistical , Pandemics/prevention & control , SARS-CoV-2 , Age Factors , Aged , Aged, 80 and over , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Female , Humans , Linear Models , Male , Middle Aged , Pandemics/economics , Treatment Outcome , United States/epidemiology
17.
PLoS One ; 16(10): e0258042, 2021.
Article in English | MEDLINE | ID: covidwho-1448577

ABSTRACT

OBJECTIVE: To investigate the perceived-stigma level of COVID-19 patients in the early stage of the epidemic and analysed related factors and correlations that affected the stigma levels. METHODS: The COVID-19 patients were selected using the convenience sampling method. Perceived-stigma level was evaluated using the Social Impact Scale (SIS). Frequency was used to describe the general information and disease investigation status of COVID-19 patients; mean and standard deviation were used for describing stigma levels, Wilcoxon signed-ranks test (nonparametric test) was applied for pairwise comparison. Kruskal-Wallis non-parametric test for grade data, and Dwass-Steel-Critchlow-Fligner test for multiple comparative analysis. Multiple linear regression analysis was performed, and statistically significant indicators in single-factor analysis were included to investigate the independent factors of stigma. The p<0.05 was considered statistically significant. RESULTS: SIS score of the 122 COVID-19 patients averaged 57.37±9.99 points. There were statistically significant differences in perceived-stigma levels among patients of different ages (p = 0.008), occupation (p <0.001), marital status (p = 0.009), and disease severity (p = 0.020). Multivariate logistic regression analysis revealed that age was the main influencing factor of stigma (p<0.05). CONCLUSIONS: The overall perceived-stigma level of COVID-19 patients in the early stage of the epidemic was moderate. Younger, unmarried, and severely ill patients had a higher level of perceived-stigma, with age being the main factor. More attention should be given to the young COVID-19 patients.


Subject(s)
COVID-19/pathology , Social Stigma , Adult , Age Factors , COVID-19/epidemiology , COVID-19/virology , China/epidemiology , Cross-Sectional Studies , Humans , Linear Models , Male , Marriage , Middle Aged , SARS-CoV-2/isolation & purification , Severity of Illness Index , Surveys and Questionnaires
18.
Stat Med ; 40(29): 6707-6722, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1432476

ABSTRACT

Mean residual life (MRL) function defines the remaining life expectancy of a subject who has survived to a time point and is an important alternative to the hazard function for characterizing the distribution of a time-to-event variable. Existing MRL models primarily focus on studying the association between risk factors and disease risks using linear model specifications in multiplicative or additive scale. When risk factors have complex correlation structures, nonlinear effects, or interactions, the prefixed linearity assumption may be insufficient to capture the relationship. Single-index modeling framework offers flexibility in reducing dimensionality and modeling nonlinear effects. In this article, we propose a class of partially linear single-index generalized MRL models, the regression component of which consists of both a semiparametric single-index part and a linear regression part. Regression spline technique is employed to approximate the nonparametric single-index function, and parameters are estimated using an iterative algorithm. Double-robust estimators are also proposed to protect against the misspecification of censoring distribution or MRL models. A further contribution of this article is a nonparametric test proposed to formally evaluate the linearity of the single-index function. Asymptotic properties of the estimators are established, and the finite-sample performance is evaluated through extensive numerical simulations. The proposed models and inference approaches are demonstrated by a New York University Langone Health (NYULH) COVID-19 dataset.


Subject(s)
COVID-19 , Algorithms , Humans , Linear Models , Regression Analysis , SARS-CoV-2
19.
PLoS One ; 16(9): e0257668, 2021.
Article in English | MEDLINE | ID: covidwho-1430549

ABSTRACT

BACKGROUND: Adverse reactions are more common after the second injection of messenger RNA vaccines such as Pfizer/BioNTech's BNT162b2. We hypothesized that the degree and severity of reactogenicity after the second injection reflects the magnitude of antibody production against the SARS CoV-2 virus spike protein (spike IgG). METHODS AND RESULTS: Blood samples were obtained from 67 Japanese healthcare workers three weeks after the first injection and two weeks after the second injection of the BNT162b2 vaccine to measure spike IgG levels. Using questionnaires, we calculated an adverse event (AE) score (0-11) for each participant. The geometric mean of spike IgG titers increased from 1,047 antibody units (AU/mL) (95% confidence interval (95% CI): 855-1282 AU/mL) after the first injection to 17,378 AU/mL (95% CI: 14,622-20,663 AU/mL) after the second injection. The median AE score increased from 2 to 5. Spike IgG levels after the second injection were negatively correlated with age and positively correlated with spike IgG after the first injection. AE scores after the second injection were not significantly associated with log-transformed spike IgG after the second injection, when adjusted for age, sex, AE score after the first injection, and log-transformed spike IgG after the first injection. CONCLUSIONS: Although the sample size was relatively small, reactogenicity after the second injection may not accurately reflect antibody production.


Subject(s)
COVID-19 Vaccines/immunology , Immunoglobulin G/blood , Injections , Spike Glycoprotein, Coronavirus/immunology , Adult , COVID-19/blood , COVID-19/immunology , COVID-19/virology , COVID-19 Vaccines/adverse effects , Female , Humans , Linear Models , Male , Middle Aged , Multivariate Analysis , SARS-CoV-2/physiology
20.
PLoS One ; 16(9): e0257552, 2021.
Article in English | MEDLINE | ID: covidwho-1430539

ABSTRACT

Countermeasures against the spread of COVID-19 have become an urgent issue in educational settings, where many group activities are necessary. Educators are key to preventing the spread of COVID-19 in educational settings. Infection prevention behavior requires comprehensive and complex measures such as self-restraint. disinfection care, hand washing, wearing masks and recommendation and implementation of vaccination. Improvement in the knowledge, skills, and preventive actions of educators vis-à-vis COVID-19 could allow for the continued provision of educational services while ensuring safety in educational settings. Therefore, the objective of this study was to explore the knowledge and preventive actions of educators regarding COVID-19 and vaccination awareness to provide appropriate support for educators. The study used data collected from 1,000 Japanese educators in January 2021 when the third wave of viral infections spread. Online surveys and multivariate linear regression analysis were used to determine age and whether respondents were being cared for by a doctor. We investigated the effects of factors on educators' willingness to be vaccinated and changes in their behavior. This study found that factors such as age, gender, whether a respondent was under a physician's care, and health literacy, affected the willingness of educators to receive vaccinations and engage in preventive actions. The study also suggests that the reliability of national government public relations efforts is lower than the reliability of local government public relations and that of information from family physicians, pharmacies, and mass media. It is therefore necessary to reexamine how information is disseminated by the national government and to increase the degree of trust in that information among the public. The findings of the study also revealed the importance of improving the provision of appropriate information and health literacy for the behavior of educators, not only during the initial outbreak, but also during the subsequent period of pandemic life.


Subject(s)
COVID-19/prevention & control , Health Education , Health Knowledge, Attitudes, Practice , Health Literacy , Internet , Surveys and Questionnaires , Vaccination , Adult , COVID-19/epidemiology , COVID-19/virology , Female , Humans , Japan , Linear Models , Male , Middle Aged , Multivariate Analysis , Pandemics/prevention & control , Reproducibility of Results , SARS-CoV-2/physiology , Young Adult
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