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1.
Eur J Med Res ; 26(1): 152, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1582002

ABSTRACT

BACKGROUND: COVID-19 and its related anti-inflammatory treatment (steroids, immunomodulators) may induce the reactivation of latent bacterial, parasitic, and viral infections. According to our knowledge, no case of disseminated HHV-8-related Kaposi sarcoma (KS) after COVID-19 and its treatment has been described so far. Only one case of cutaneous KS concurrently with COVID-19 has been previously reported. CASE PRESENTATION: We describe a case of disseminated KS in a 61-year-old immunocompetent Albanian man after hospitalization for COVID-19. METHODS FOR LITERATURE RESEARCH: We used PubMed as biomedical database for the literature research. We selected keyword combinations including "Kaposi sarcoma," "HHV-8," "immunocompetent," "COVID-19," "SARS-CoV-2," and "steroids." No time or language limitation was set. Titles and abstracts of selected articles were systematically screened. Articles were included in the examination if they were published under free access through the digital library of the University of Brescia (Italy), and provided full text. Articles were excluded if the topic was beyond the aim of our study. Finally, we selected 15 articles. RESULTS: We describe a case of KS in COVID-19 patient and postulate that Interleukin-6 (IL-6) activity and steroid-induced immunodeficiency may play a major role in KS emergence. No published case of disseminated KS following COVID-19 in otherwise healthy individuals was found through the systematic literature review, despite the high incidence of COVID-19 in areas with medium-high prevalence of HHV-8 infection. This observation might be explained by the role of individual genetic susceptibility factors. CONCLUSIONS: SARS-CoV-2 infection and its treatment may lead to reactivation of several latent infections, including HHV-8 and its related clinical syndrome, Kaposi sarcoma.


Subject(s)
COVID-19/genetics , SARS-CoV-2/genetics , Sarcoma, Kaposi/drug therapy , COVID-19/diagnosis , COVID-19/drug therapy , Databases, Chemical , Humans , Interleukin-6/metabolism , Language , Male , Middle Aged , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , Sarcoma, Kaposi/complications , Sarcoma, Kaposi/genetics
2.
Comput Math Methods Med ; 2021: 4321131, 2021.
Article in English | MEDLINE | ID: covidwho-1553710

ABSTRACT

The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations against coronavirus, people's feelings have become more diverse and complex. Our aim is to understand and unravel their sentiments in this research using deep learning techniques. Social media is currently the best way to express feelings and emotions, and with the help of Twitter, one can have a better idea of what is trending and going on in people's minds. Our motivation for this research was to understand the diverse sentiments of people regarding the vaccination process. In this research, the timeline of the collected tweets was from December 21 to July21. The tweets contained information about the most common vaccines available recently from across the world. The sentiments of people regarding vaccines of all sorts were assessed using the natural language processing (NLP) tool, Valence Aware Dictionary for sEntiment Reasoner (VADER). Initializing the polarities of the obtained sentiments into three groups (positive, negative, and neutral) helped us visualize the overall scenario; our findings included 33.96% positive, 17.55% negative, and 48.49% neutral responses. In addition, we included our analysis of the timeline of the tweets in this research, as sentiments fluctuated over time. A recurrent neural network- (RNN-) oriented architecture, including long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM), was used to assess the performance of the predictive models, with LSTM achieving an accuracy of 90.59% and Bi-LSTM achieving 90.83%. Other performance metrics such as precision,, F1-score, and a confusion matrix were also used to validate our models and findings more effectively. This study improves understanding of the public's opinion on COVID-19 vaccines and supports the aim of eradicating coronavirus from the world.


Subject(s)
COVID-19 Vaccines , COVID-19/prevention & control , Deep Learning , Social Media , Attitude , Attitude to Health , Databases, Factual , Humans , Language , Models, Statistical , Neural Networks, Computer , Public Opinion , Reproducibility of Results , Vaccination
3.
BMC Public Health ; 21(1): 2121, 2021 11 18.
Article in English | MEDLINE | ID: covidwho-1526619

ABSTRACT

BACKGROUND: The COVID-19 pandemic has further exposed inequities in our society, demonstrated by disproportionate COVID-19 infection rate and mortality in communities of color and low-income communities. One key area of inequity that has yet to be explored is disparities based on preferred language. METHODS: We conducted a retrospective cohort study of 164,368 adults tested for COVID-19 in a large healthcare system across Washington, Oregon, and California from March - July 2020. Using electronic health records, we constructed multi-level models that estimated the odds of testing positive for COVID-19 by preferred language, adjusting for age, race/ethnicity, and social factors. We further investigated interaction between preferred language and both race/ethnicity and state. Analysis was performed from October-December 2020. RESULTS: Those whose preferred language was not English had higher odds of having a COVID-19 positive test (OR 3.07, p < 0.001); this association remained significant after adjusting for age, race/ethnicity, and social factors. We found significant interaction between language and race/ethnicity and language and state, but the odds of COVID-19 test positivity remained greater for those whose preferred language was not English compared to those whose preferred language was English within each race/ethnicity and state. CONCLUSIONS: People whose preferred language is not English are at greater risk of testing positive for COVID-19 regardless of age, race/ethnicity, geography, or social factors - demonstrating a significant inequity. Research demonstrates that our public health and healthcare systems are centered on English speakers, creating structural and systemic barriers to health. Addressing these barriers are long overdue and urgent for COVID-19 prevention.


Subject(s)
COVID-19 , Adult , Humans , Language , Pandemics , Retrospective Studies , SARS-CoV-2 , Social Factors , United States/epidemiology
4.
Clin Orthop Relat Res ; 479(7): 1417-1425, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1511052

ABSTRACT

BACKGROUND: Healthcare disparities are well documented across multiple subspecialties in orthopaedics. The widespread implementation of telemedicine risks worsening these disparities if not carefully executed, despite original assumptions that telemedicine improves overall access to care. Telemedicine also poses unique challenges such as potential language or technological barriers that may alter previously described patterns in orthopaedic disparities. QUESTIONS/PURPOSES: Are the proportions of patients who use telemedicine across orthopaedic services different among (1) racial and ethnic minorities, (2) non-English speakers, and (3) patients insured through Medicaid during a 10-week period after the implementation of telemedicine in our healthcare system compared with in-person visits during a similar time period in 2019? METHODS: This was a retrospective comparative study using electronic medical record data to compare new patients establishing orthopaedic care via outpatient telemedicine at two academic urban medical centers between March 2020 and May 2020 with new orthopaedic patients during the same 10-week period in 2019. A total of 11,056 patients were included for analysis, with 1760 in the virtual group and 9296 in the control group. Unadjusted analyses demonstrated patients in the virtual group were younger (median age 57 years versus 59 years; p < 0.001), but there were no differences with regard to gender (56% female versus 56% female; p = 0.66). We used self-reported race or ethnicity as our primary independent variable, with primary language and insurance status considered secondarily. Unadjusted and multivariable adjusted analyses were performed for our primary and secondary predictors using logistic regression. We also assessed interactions between race or ethnicity, primary language, and insurance type. RESULTS: After adjusting for age, gender, subspecialty, insurance, and median household income, we found that patients who were Hispanic (odds ratio 0.59 [95% confidence interval 0.39 to 0.91]; p = 0.02) or Asian were less likely (OR 0.73 [95% CI 0.53 to 0.99]; p = 0.04) to be seen through telemedicine than were patients who were white. After controlling for confounding variables, we also found that speakers of languages other than English or Spanish were less likely to have a telemedicine visit than were people whose primary language was English (OR 0.34 [95% CI 0.18 to 0.65]; p = 0.001), and that patients insured through Medicaid were less likely to be seen via telemedicine than were patients who were privately insured (OR 0.83 [95% CI 0.69 to 0.98]; p = 0.03). CONCLUSION: Despite initial promises that telemedicine would help to bridge gaps in healthcare, our results demonstrate disparities in orthopaedic telemedicine use based on race or ethnicity, language, and insurance type. The telemedicine group was slightly younger, which we do not believe undermines the findings. As healthcare moves toward increased telemedicine use, we suggest several approaches to ensure that patients of certain racial, ethnic, or language groups do not experience disparate barriers to care. These might include individual patient- or provider-level approaches like expanded telemedicine schedules to accommodate weekends and evenings, institutional investment in culturally conscious outreach materials such as advertisements on community transport systems, or government-level provisions such as reimbursement for telephone-only encounters. LEVEL OF EVIDENCE: Level III, therapeutic study.


Subject(s)
Health Services Accessibility , Healthcare Disparities/statistics & numerical data , Minority Groups/statistics & numerical data , Orthopedic Procedures/statistics & numerical data , Telemedicine/statistics & numerical data , Adult , Female , Health Plan Implementation , Healthcare Disparities/ethnology , Humans , Insurance Coverage/statistics & numerical data , Language , Male , Medicaid , Middle Aged , Odds Ratio , Retrospective Studies , Telemedicine/methods , United States
5.
PLoS One ; 16(11): e0259594, 2021.
Article in English | MEDLINE | ID: covidwho-1504862

ABSTRACT

BACKGROUND: The emergence of the COVID-19 pandemic has affected the lives of many people, including medical students. The present study explored internet addiction and changes in sleep patterns among medical students during the pandemic and assessed the relationship between them. METHODS: A cross-sectional study was carried out in seven countries, the Dominican Republic, Egypt, Guyana, India, Mexico, Pakistan, and Sudan, using a convenience sampling technique, an online survey comprising demographic details, information regarding COVID-19, the Pittsburgh Sleep Quality Index (PSQI), and the Internet Addiction Test (IAT). RESULTS: In total, 2749 participants completed the questionnaire. Of the total, 67.6% scored above 30 in the IAT, suggesting the presence of an Internet addiction, and 73.5% scored equal and above 5 in the PSQI, suggesting poor sleep quality. Internet addiction was found to be significant predictors of poor sleep quality, causing 13.2% of the variance in poor sleep quality. Participants who reported COVID-19 related symptoms had disturbed sleep and higher internet addiction levels when compared with those who did not. Participants who reported a diagnosis of COVID-19 reported poor sleep quality. Those living with a COVID-19 diagnosed patient reported higher internet addiction and worse sleep quality compared with those who did not have any COVID-19 patients in their surroundings. CONCLUSION: The results of this study suggest that internet addiction and poor sleep quality are two issues that require addressing amongst medical students. Medical training institutions should do their best to minimize their negative impact, particularly during the current COVID-19 pandemic.


Subject(s)
Internet Addiction Disorder/complications , Internet Addiction Disorder/epidemiology , Sleep Wake Disorders/complications , Sleep Wake Disorders/epidemiology , Sleep , Students, Medical , Adolescent , Adult , COVID-19/epidemiology , Cross-Sectional Studies , Female , Humans , Internationality , Language , Male , Pandemics , Research Design , Surveys and Questionnaires , Young Adult
6.
Curr Med Res Opin ; 37(11): 2017-2018, 2021 11.
Article in English | MEDLINE | ID: covidwho-1500876

Subject(s)
Language , Publishing , Humans
7.
Sci Rep ; 11(1): 21505, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1500509

ABSTRACT

Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions. When the COVID-19 pandemic broke out and mobility restrictions ensued across the globe, it was unclear whether contributions to Wikipedia would decrease in the face of the pandemic, or whether volunteers would withstand the added stress and increase their contributions to accommodate the growing readership uncovered in recent studies. We analyze [Formula: see text] million edits contributed from 2018 to 2020 across twelve Wikipedia language editions and find that Wikipedia's global volunteer community responded resiliently to the pandemic, substantially increasing both productivity and the number of newcomers who joined the community. For example, contributions to the English Wikipedia increased by over [Formula: see text] compared to the expectation derived from pre-pandemic data. Our work sheds light on the response of a global volunteer population to the COVID-19 crisis, providing valuable insights into the behavior of critical online communities under stress.


Subject(s)
COVID-19/epidemiology , Volunteers/statistics & numerical data , COVID-19/pathology , COVID-19/virology , Databases, Factual , Encyclopedias as Topic , Humans , Language , Pandemics , Quarantine , SARS-CoV-2/isolation & purification
8.
PLoS One ; 16(10): e0259062, 2021.
Article in English | MEDLINE | ID: covidwho-1496527

ABSTRACT

This study aimed to generate a linguistic equivalent of the COVID Stress Scales (CSS) in the Serbian language and examine its psychometric characteristics. Data were collected from September to December 2020 among the general population of three cities in Republic of Serbia and Republic of Srpska, countries where the Serbian language is spoken. Participants completed a socio-demographic questionnaire, followed by the CSS and Perceived Stress Scale (PSS). The CSS was validated using the standard methodology (i.e., forward and backward translations, pilot testing). The reliability of the Serbian CSS was assessed using Cronbach's alpha and McDonald's omega coefficients and convergent validity was evaluated by correlating the CSS with PSS. Confirmatory factor analysis was performed to examine the construct validity of the Serbian CSS. This study included 961 persons (52.8% males and 47.2% females). The Cronbach's alpha coefficient of the Serbian CSS was 0.964 and McDonald's omega was 0.964. The Serbian CSS with 36 items and a six-factorial structure showed a measurement model with a satisfactory fit for our population (CMIN/DF = 4.391; GFI = 0.991; RMSEA = 0.025). The CSS total and all domain scores significantly positively correlated with PSS total score. The Serbian version of the CSS is a valid and reliable questionnaire that can be used in assessing COVID-19-related distress experienced by Serbian speaking people during the COVID-19 pandemic as well as future epidemics and pandemics.


Subject(s)
COVID-19 , Language , Pandemics , Adult , Female , Humans , Male , Middle Aged , Psychometrics , Reproducibility of Results , Serbia
9.
Comput Intell Neurosci ; 2021: 2158184, 2021.
Article in English | MEDLINE | ID: covidwho-1495704

ABSTRACT

COVID-19 has claimed several human lives to this date. People are dying not only because of physical infection of the virus but also because of mental illness, which is linked to people's sentiments and psychologies. People's written texts/posts scattered on the web could help understand their psychology and the state they are in during this pandemic. In this paper, we analyze people's sentiment based on the classification of tweets collected from the social media platform, Twitter, in Nepal. For this, we, first, propose to use three different feature extraction methods-fastText-based (ft), domain-specific (ds), and domain-agnostic (da)-for the representation of tweets. Among these three methods, two methods ("ds" and "da") are the novel methods used in this study. Second, we propose three different convolution neural networks (CNNs) to implement the proposed features. Last, we ensemble such three CNNs models using ensemble CNN, which works in an end-to-end manner, to achieve the end results. For the evaluation of the proposed feature extraction methods and CNN models, we prepare a Nepali Twitter sentiment dataset, called NepCOV19Tweets, with 3 classes (positive, neutral, and negative). The experimental results on such dataset show that our proposed feature extraction methods possess the discriminating characteristics for the sentiment classification. Moreover, the proposed CNN models impart robust and stable performance on the proposed features. Also, our dataset can be used as a benchmark to study the COVID-19-related sentiment analysis in the Nepali language.


Subject(s)
COVID-19 , Deep Learning , Humans , Language , Pandemics , SARS-CoV-2
10.
Proc Natl Acad Sci U S A ; 118(43)2021 10 26.
Article in English | MEDLINE | ID: covidwho-1483204

ABSTRACT

Contact tracing is a pillar of COVID-19 response, but language access and equity have posed major obstacles. COVID-19 has disproportionately affected minority communities with many non-English-speaking members. Language discordance can increase processing times and hamper the trust building necessary for effective contact tracing. We demonstrate how matching predicted patient language with contact tracer language can enhance contact tracing. First, we show how to use machine learning to combine information from sparse laboratory reports with richer census data to predict the language of an incoming case. Second, we embed this method in the highly demanding environment of actual contact tracing with high volumes of cases in Santa Clara County, CA. Third, we evaluate this language-matching intervention in a randomized controlled trial. We show that this low-touch intervention results in 1) significant time savings, shortening the time from opening of cases to completion of the initial interview by nearly 14 h and increasing same-day completion by 12%, and 2) improved engagement, reducing the refusal to interview by 4%. These findings have important implications for reducing social disparities in COVID-19; improving equity in healthcare access; and, more broadly, leveling language differences in public services.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Contact Tracing/methods , Language , SARS-CoV-2 , Algorithms , COVID-19/epidemiology , California/epidemiology , Communication Barriers , Contact Tracing/statistics & numerical data , Female , Humans , Machine Learning , Male , Pandemics/prevention & control , Surveys and Questionnaires , Trust
11.
Int J Environ Res Public Health ; 18(19)2021 09 30.
Article in English | MEDLINE | ID: covidwho-1458302

ABSTRACT

Short and effective tools for measuring depression, anxiety and their resulting impairments are lacking in the Czech language. The abbreviated versions of the Overall Anxiety Severity and Impairment Scale (OASIS) and the Overall Depression Severity and Impairment Scale (ODSIS) show very good psychometric properties in English and other languages, and can be used in different settings for research or clinical purposes. The aim of this study was the psychometric evaluation and validation of the Czech versions of the abbreviated forms of both tools in the general population. A nationally representative sample of 2912 participants (age = 48.88, SD = 15.56; 55% female) was used. The non-parametric testing of the differences between sociodemographic groups revealed a higher level of anxiety and depression in students, females and religious respondents. Confirmatory Factor Analysis suggested a good fit for the unidimensional model of the OASIS: x2(4) = 38.28; p < 0.001; TLI = 0.999; CFI = 0.997; RMSEA = 0.078; SRMR = 0.027 and the ODSIS: x2(4) = 36.54; p < 0.001; TLI = 0.999; CFI = 0.999; RMSEA = 0.076; SRMR = 0.021 with the data. Both scales had an excellent internal consistency (OASIS: Cronbach's alpha = 0.95, McDonald's omega = 0.95 and ODSIS: Cronbach's alpha = 0.95, McDonald's omega = 0.95). A clinical cut-off of 15 was identified for the OASIS and a cut-off of 12 for the ODSIS. The study showed good validity for both scales. The Czech versions of the abbreviated OASIS and ODSIS were short and valid instruments for measuring anxiety and depression.


Subject(s)
Depression , Language , Anxiety/diagnosis , Anxiety/epidemiology , Czech Republic/epidemiology , Depression/diagnosis , Depression/epidemiology , Factor Analysis, Statistical , Female , Humans , Male , Middle Aged , Psychometrics , Reproducibility of Results , Surveys and Questionnaires
12.
Psychooncology ; 30(8): 1262-1277, 2021 08.
Article in English | MEDLINE | ID: covidwho-1453646

ABSTRACT

OBJECTIVE: Breast cancer treatments bring adverse consequences that interfere with everyday functioning. Importantly, some of these treatments are associated with cognitive and language changes. Tamoxifen is a selective estrogen receptor modulator and is a common endocrine therapy treatment for breast cancer. The current review examines the specific domains of cognition and language affected by the use of tamoxifen in women with breast cancer. METHODS: We conducted a systematic search that examined cognitive and/or language functions in chemotherapy-naïve women with breast cancer taking tamoxifen. PubMed, Cochrane CENTRAL, CINAHL Complete, PsycINFO, Scopus, EMBASE, and the Grey Literature Report (greylit.org) were searched. Covidence Systematic Review software (covidence.org) was used to manage the screening process of study titles and abstracts as well as full texts. A total of 17 studies were included in the review. RESULTS: A range of cognitive and language domains were reported. These were grouped into seven broad domains: attention, memory, speed, executive functioning, verbal abilities, visual abilities, and language abilities. Results showed that there is compelling evidence that specific domains of memory and speed are negatively affected by the use of tamoxifen. In addition, there was a pattern of change in domains of executive functions and verbal abilities. CONCLUSIONS: Tamoxifen affects specific cognitive and language domains. Language domains beyond semantics have not been studied and thus conclusions related to these domains, and language in general, could not be made. Studies exploring the effects of tamoxifen on the different domains of language are recommended.


Subject(s)
Breast Neoplasms , Tamoxifen , Breast Neoplasms/drug therapy , Cognition , Executive Function , Female , Humans , Language , Tamoxifen/adverse effects
13.
S Afr J Commun Disord ; 68(1): e1-e9, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1449017

ABSTRACT

BACKGROUND: The need for communication-related services in sub-Saharan Africa to support individuals experiencing communication disability is a longstanding and well-documented situation. We posit the inequities highlighted by coronavirus disease 2019 (COVID-19) make this a relevant time for speech language therapists and the professional bodies that govern us to broadly consider our roles and practices in education, health and disability in local, national and global contexts. OBJECTIVE: To illustrate what services developed with local knowledge can look like in Kenya in order to promote dialogue around alternative speech language therapy models, particularly in contexts where there are insufficient services, few trained speech language therapists and limited structures to support the emerging profession. METHOD: This article examines three clinical case studies from Western Kenya, using a conceptual framework for responsive global engagement. RESULTS: Service needs in Western Kenya well exceed a direct one-on-one model of care that is common in the minority world. The service delivery models described here emphasise training, skills sharing and engaging the myriad of communication partners available to individuals with communication disabilities. CONCLUSION: We offer up these case studies of collaborative practice as contextual realities that may be present in any speech language therapy programming in under-resourced communities. We dispel the idea that success in this work has been linear, progressed on planned time frames or come to fruition with targeted goal attainment. The fact that our relationships have endured in these communities since 2007 is our primary success.


Subject(s)
COVID-19 , Language Therapy , Humans , Kenya , Language , SARS-CoV-2 , Speech , Speech Therapy
14.
PLoS One ; 16(10): e0258137, 2021.
Article in English | MEDLINE | ID: covidwho-1448582

ABSTRACT

Online education, including college English education, has been developing rapidly in the recent decade in China. Such aspects as e-readiness, benefits and challenges of online education were well-researched under normal situations, but fully online language teaching on a large-scale in emergencies may tell a different story. A survey of 2310 non-English-major college students and 149 English teachers from three types of twelve higher education institutions in Wuhan was conducted to evaluate their readiness for online English education during the COVID-19 pandemic, to figure out challenges encountered by them and to draw implications for future online college English education. Quantitative statistics gathered using two readiness scales adapted from previous studies showed that both cohorts were slightly below the ready level for the unexpected online transition of college English education. The overall level of readiness for students was 3.68 out of a score of 5, and that for teachers was 3.70. Individual differences were explored and reported. An analysis of qualitative results summarized six categories of challenges encountered by the students, i.e. technical challenges, challenges concerning learning process, learning environment, self-control, efficiency and effectiveness, and health concern. Though the students reported the highest level of readiness in technology access, they were most troubled by technical problems during online study. For teachers, among three types of challenges, they were most frustrated by pedagogical ones, especially students' disengagement in online class. The survey brought insights for online college English education development. Institutions should take the initiative and continue promoting the development of online college English education, because a majority of the respondents reported their willingness and intention to continue learning/teaching English in online or blended courses in the post-pandemic period. They are supposed to remove technical barriers for teachers and students, and assess the readiness levels of both cohorts before launching English courses online. Institutions should also arrange proper training for instructors involved, especially about pedagogical issues. Language teachers are suggested to pay special attention to students' engagement and communication in online courses.


Subject(s)
COVID-19/epidemiology , Education, Distance , Educational Personnel/psychology , Students/psychology , Academic Performance , Adult , COVID-19/pathology , COVID-19/virology , China/epidemiology , Female , Humans , Language , Learning , Male , SARS-CoV-2/isolation & purification , Surveys and Questionnaires , Young Adult
15.
Clin Microbiol Infect ; 28(1): 107-113, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1446536

ABSTRACT

OBJECTIVES: Motivated by reports of increased risk of coronavirus disease 2019 (COVID-19) in ethnic minorities of high-income countries, we explored whether patients with a foreign first language are at an increased risk of COVID-19 infections, more serious presentations, or worse outcomes. METHODS: In a retrospective observational population-based quality registry study covering a population of 1.7 million, we studied the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), admissions to specialist healthcare and the intensive care unit (ICU), and all-cause case fatality in different language groups between 27th February and 3rd August 2020 in Southern Finland. A first language other than Finnish, Swedish or Sámi served as a surrogate marker for a foreign ethnic background. RESULTS: In total, 124 240 individuals were tested, and among the 118 300 (95%) whose first language could be determined, 4005 (3.4%) were COVID-19-positive, 623 (0.5%) were admitted to specialized hospitals, and 147 (0.1%) were admitted to the ICU; 254 (0.2%) died. Those with a foreign first language had lower testing rates (348, 95%CI 340-355 versus 758, 95%CI 753-762 per 10 000, p < 0.0001), higher incidence (36, 95%CI 33-38 versus 22, 95%CI 21-23 per 10 000, p < 0.0001), and higher positivity rates (103, 95%CI 96-109 versus 29, 95%CI 28-30 per 1000, p < 0.0001). There was no significant difference in ICU admissions, disease severity at ICU admission, or ICU outcomes. Case fatality by 90 days was 7.7% in domestic cases and 1.2% in those with a foreign first language, explained by demographics (age- and sex-adjusted HR 0.49, 95%CI 0.21-1.15). CONCLUSIONS: The population with a foreign first language was at an increased risk for testing positive for SARS-CoV-2, but when hospitalized they had outcomes similar to those in the native, domestic language population. This suggests that special attention should be paid to the prevention and control of infectious diseases among language minorities.


Subject(s)
COVID-19 , /statistics & numerical data , COVID-19/epidemiology , COVID-19/ethnology , Cohort Studies , Critical Care , Finland/epidemiology , Hospitalization , Humans , Intensive Care Units , Language , Retrospective Studies
16.
Int J Environ Res Public Health ; 18(18)2021 09 18.
Article in English | MEDLINE | ID: covidwho-1430866

ABSTRACT

The sudden appearance of a new epidemic disease in China created the need for names identifying that disease. Between December 2019 and January 2020, a variety of severe pneumonia-related disease names suddenly appeared, and more name varieties kept coming up afterwards. To better understand the introduction and spread of these names, 16 different COVID-19-related name varieties were selected covering the period from the end of December 2019, when the epidemic started, to mid-March 2020, a moment at which the term competition had stabilized. By way of big data analysis, the initiation and distribution of the 16 names across the media landscape was traced with regard to the impact of different media platforms, while the distribution frequency of each of the selected terms was mapped, resulting in a distinction of three groups of disease names, each with a different media and time profile. The results were discussed based on the hypotheses of disease confusion by name variety and management failures in absence of clear language governance at the national and global levels. The analysis of the data led to a refutation of both hypotheses. Based on this discussion, the study offers empirically based suggestions for the WHO in their naming practices and further research.


Subject(s)
COVID-19 , Social Media , China , Humans , Language , SARS-CoV-2
17.
Int J Environ Res Public Health ; 18(18)2021 Sep 13.
Article in English | MEDLINE | ID: covidwho-1409542

ABSTRACT

While the literature on infectious disease outbreaks has examined the extent to which communication inequalities during public health emergencies exacerbate negative outcomes among disadvantaged individuals, the implications of ethnic media consumption among minority groups during these crises are underexplored. Making use of the first nationally representative survey of US Latinos (N = 1200) on the impact and reactions to COVID-19, this study examines the implications of Spanish-language news media consumption on source credibility and attitude formation during the COVID-19 pandemic among Latinos and immigrants from Latin America. Through a series of statistical analyses, this study finds that ethnic news consumption is strongly associated with trust in Spanish-language journalists, whereas mainstream media consumption is not associated with trust in English-language journalists. More importantly, this study finds that source credibility, particularly in Spanish-language journalists, matters for Latinos as it is associated with more positive assessments of state and local officials providing adequate information about COVID-19. This study illuminates the importance of non-traditional media among racial minorities, who account for almost 40% of the US population, and highlights the importance of shared backgrounds in source credibility among linguistically diverse groups in the United States during a public health crisis.


Subject(s)
COVID-19 , Pandemics , Humans , Language , SARS-CoV-2 , United States/epidemiology
18.
PLoS Med ; 18(9): e1003758, 2021 09.
Article in English | MEDLINE | ID: covidwho-1406746

ABSTRACT

BACKGROUND: A number of prior studies have demonstrated that research participants with limited English proficiency in the United States are routinely excluded from clinical trial participation. Systematic exclusion through study eligibility criteria that require trial participants to be able to speak, read, and/or understand English affects access to clinical trials and scientific generalizability. We sought to establish the frequency with which English language proficiency is required and, conversely, when non-English languages are affirmatively accommodated in US interventional clinical trials for adult populations. METHODS AND FINDINGS: We used the advanced search function on ClinicalTrials.gov specifying interventional studies for adults with at least 1 site in the US. In addition, we used these search criteria to find studies with an available posted protocol. A computer program was written to search for evidence of English or Spanish language requirements, or the posted protocol, when available, was manually read for these language requirements. Of the 14,367 clinical trials registered on ClinicalTrials.gov between 1 January 2019 and 1 December 2020 that met baseline search criteria, 18.98% (95% CI 18.34%-19.62%; n = 2,727) required the ability to read, speak, and/or understand English, and 2.71% (95% CI 2.45%-2.98%; n = 390) specifically mentioned accommodation of translation to another language. The remaining trials in this analysis and the following sub-analyses did not mention English language requirements or accommodation of languages other than English. Of 2,585 federally funded clinical trials, 28.86% (95% CI 27.11%-30.61%; n = 746) required English language proficiency and 4.68% (95% CI 3.87%-5.50%; n = 121) specified accommodation of other languages; of the 5,286 industry-funded trials, 5.30% (95% CI 4.69%-5.90%; n = 280) required English and 0.49% (95% CI 0.30%-0.69%; n = 26) accommodated other languages. Trials related to infectious disease were less likely to specify an English requirement than all registered trials (10.07% versus 18.98%; relative risk [RR] = 0.53; 95% CI 0.44-0.64; p < 0.001). Trials related to COVID-19 were also less likely to specify an English requirement than all registered trials (8.18% versus 18.98%; RR = 0.43; 95% CI 0.33-0.56; p < 0.001). Trials with a posted protocol (n = 366) were more likely than all registered clinical trials to specify an English requirement (36.89% versus 18.98%; RR = 1.94, 95% CI 1.69-2.23; p < 0.001). A separate analysis of studies with posted protocols in 4 therapeutic areas (depression, diabetes, breast cancer, and prostate cancer) demonstrated that clinical trials related to depression were the most likely to require English (52.24%; 95% CI 40.28%-64.20%). One limitation of this study is that the computer program only searched for the terms "English" and "Spanish" and may have missed evidence of other language accommodations. Another limitation is that we did not differentiate between requirements to read English, speak English, understand English, and be a native English speaker; we grouped these requirements together in the category of English language requirements. CONCLUSIONS: A meaningful percentage of US interventional clinical trials for adults exclude individuals who cannot read, speak, and/or understand English, or are not native English speakers. To advance more inclusive and generalizable research, funders, sponsors, institutions, investigators, institutional review boards, and others should prioritize translating study materials and eliminate language requirements unless justified either scientifically or ethically.


Subject(s)
Clinical Trials as Topic , Language , Patient Selection , COVID-19 , Depression , Humans , United States
19.
PLoS One ; 16(9): e0256874, 2021.
Article in English | MEDLINE | ID: covidwho-1398937

ABSTRACT

The Coronavirus (COVID-19) pandemic has led to a rapidly growing 'infodemic' of health information online. This has motivated the need for accurate semantic search and retrieval of reliable COVID-19 information across millions of documents, in multiple languages. To address this challenge, this paper proposes a novel high precision and high recall neural Multistage BiCross encoder approach. It is a sequential three-stage ranking pipeline which uses the Okapi BM25 retrieval algorithm and transformer-based bi-encoder and cross-encoder to effectively rank the documents with respect to the given query. We present experimental results from our participation in the Multilingual Information Access (MLIA) shared task on COVID-19 multilingual semantic search. The independently evaluated MLIA results validate our approach and demonstrate that it outperforms other state-of-the-art approaches according to nearly all evaluation metrics in cases of both monolingual and bilingual runs.


Subject(s)
COVID-19/epidemiology , Information Storage and Retrieval/methods , Algorithms , Humans , Language , Multilingualism , Semantics
20.
Int J Environ Res Public Health ; 18(17)2021 09 05.
Article in English | MEDLINE | ID: covidwho-1390648

ABSTRACT

Healthcare workers (HCW) are among those most directly affected by the COVID-19 pandemic. Most research with this group has used ad hoc measures, which limits comparability across samples. The Stress and Anxiety to Viral Epidemics-9 scale (SAVE-9) is a nine-item scale first developed in Korea, and has since been translated into several languages. We report on data collected from 484 German HCW between November 2020 and March 2021, during the "second wave" of coronavirus infections. We conducted item analysis, confirmatory factor analysis on the previously found factor solutions of the SAVE-9, examined correlations with established measures of depression, generalized anxiety, and insomnia, and compared scores between different groups of HCW. The psychometric properties of the German SAVE-9 were satisfactory and comparable to previous findings from Korea and Russia. Correlations with mental health measures were positive, as expected. We found some significant differences between groups of HCW on the SAVE-9 which were consistent with the literature but did not appear on the other mental health measures. This suggests that the SAVE-9 taps into specifically work-related stress, which may make it a helpful instrument in this research area.


Subject(s)
COVID-19 , Pandemics , Anxiety/epidemiology , Cross-Sectional Studies , Depression , Health Personnel , Humans , Language , SARS-CoV-2
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