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This paper aims to visualise three financial distress outlooks using computer simulations. The financial distress exposure for airport operations in Malaysia between 1991 and 2021 is given by Altman Z”-score and modelled by the multivariate generalized linear model (MGLM). Seven determinants contributing to the financial distress from literature are examined. The determinant series are fitted individually by using linear model with time series components and autoregressive integrated moving average models to forecast values for the next 10 financial years. Future short- to long-term memory effects following COVID-19 are apparent in time series plots. In the simulations, the MGLM procedure utilised Gaussian, gamma, and Cauchy probability distributions associated with expectations and challenges of doing business as well as uncertainties in the economy. The underlying trends of realistic, optimistic, and pessimistic financial distress outlooks insinuate that the increasing risk of financial distress of airport operations in Malaysia is expected to continue for the next decade.
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Am J Manag Care. 2023;29(6):In Press _____ Takeaway Points The value of direct-to-consumer (DTC) telemedicine services offered by academic health systems is understudied. * DTC telemedicine services for low-acuity or minor illnesses are increasingly offered as an employee benefit, but any per-episode unit cost advantage may be offset by overuse of care. * DTC telemedicine staffed by an academic health system and offered to its employees resulted in lower per-episode unit costs for care within 7 days and only marginally increased the use of services. * DTC telemedicine staffed by an academic health system and offered directly to employees was cost-saving. _____ Employers in the United States have increasingly been offering a direct-to-consumer (DTC) telemedicine benefit for low-acuity or minor illnesses to their employees.1-3 By 2021, more than 95% of employers with 50 or more employees provided some coverage for DTC telemedicine in their largest health plan;more than 75% felt that offering telemedicine was important and nearly 20% either limited or eliminated cost sharing for telemedicine.4 Despite these trends among general employers, few health systems have directly provided DTC telemedicine to their own employees. [...]because these services are easy to access (often available immediately, around the clock, and without travel), they may induce overuse of care, especially for self-limited conditions such as viral upper respiratory infections for which the alternative to in-person care is no care at all, thus increasing the overall cost of care.5-11 Telemedicine will save money relative to in-person care if any unit price advantages are not overwhelmed by the increased use of care overall, induced by its convenience. Employers provide health insurance coverage for 158 million Americans or nearly 50% of the population. Since the COVID-19 pandemic began, telemedicine has represented a significantly larger portion of all medical claims—consistently more than 5% of all medical claims by mid-202112-15—and the estimated value of the global telemedicine industry is projected to reach a quarter of a trillion dollars by 2024.13 Yet, the future of telemedicine remains undetermined with reimbursement rates in debate,16-18 driven in large part because its economic value is understudied and uncertain. Penn Medicine is self-insured and more than 95% of employees use its only employer-sponsored plan—a preferred provider organization (PPO) plan—rather than insurance obtained individually or through a family member. Since 2017, these PPO-insured employees have been offered Penn Medicine OnDemand,19 a 24/7 DTC telemedicine benefit to employees and their adult (≥ 18 years) dependents.
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BackgroundPatients with rheumatic diseases may present more severe SARS-CoV-2 infection compared to the general population. However, in some studies, hospitalization and mortality due COVID-19 were lower in patients with axial spondyloarthritis (axSpA) compared to other rheumatic diseases.ObjectivesTo assess the severity of SARS-CoV-2 infection in patients with axSpA from the SAR-COVID registry, comparing them with patients with rheumatoid arthritis (RA), and to determine the factors associated with poor outcomes and death.MethodsPatients ≥18 years old from the SAR-COVID national registry with diagnosis of AxSpA (ASAS criteria 2009) and RA (ACR/EULAR criteria 2010) who had confirmed SARS-CoV-2 infection (RT-PCR or positive serology), recruited from August 2020 to June 2022 were included. Sociodemographic and clinical data, comorbidities, treatments and outcomes of the infection were collected. Infection severity was assessed using the WHO-ordinal scale (WHO-OS)[1]: ambulatory [1], mild hospitalizations (2.3 y 4), severe hospitalizations (5.6 y 7) and death [8].Statistical analysisDescriptive statistics. Chi[2] or Fischer test and Student T or Mann-Whitney as appropriate. Poisson generalized linear model.ResultsA total of 1226 patients were included, 59 (4.8%) with axSpA and 1167 (95.2%) with RA. RA patients were significantly older, more frequently female, and had a longer disease duration. More than a third of the patients were in remission. 43.9 % presented comorbidities, arterial hypertension being the most frequent. At the time of SARS-Cov-2 diagnosis, patients with RA used glucocorticoids and conventional DMARDs more frequently than those with axSpA, while 74.6% of the latter were under treatment with biological DMARDs being anti-TNF the most used (61%).94.9 % of the patients in both groups reported symptoms related to SARS-CoV-2 infection. Although the differences were not significant, patients with RA presented more frequently cough, dyspnea, and gastrointestinal symptoms, while those with axSpA reported more frequently odynophagia, anosmia, and dysgeusia. During the SARS-CoV-2 infection, 6.8% and 23.5% of the patients with axSpA and RA were hospitalized, respectively. All of the patients with axSpA were admitted to the general ward, while 26.6% of those with RA to intensive care units. No patient with axSpA had complications or severe COVID-19 (WHO-OS>=5) or died as a result of the infection while mortality in the RA group was 3.3% (Figure 1).In the multivariate analysis adjusted to poor prognosis factors, no association was found between the diagnosis of axSpA and severity of SARS-CoV-2 infection assessed with the WHO-OS (OR -0.18, IC 95%(-0.38, 0.01, p=0.074).ConclusionPatients with EspAax did not present complications from SARS-CoV-2 infections and none of them died due COVID-19.Reference[1]World Health Organization coronavirus disease (COVID-19) Therapeutic Trial Synopsis Draft 2020.Figure 1.Outcomes and severity of SARS-CoV-2 infection in patients with axSpA and RA.[Figure omitted. See PDF]Acknowledgements:NIL.Disclosure of InterestsAndrea Bravo Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Tatiana Barbich Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Carolina Isnardi Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretati n, or writing the report. They do not have access to the information collected in the database., Gustavo Citera Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Emilce Edith Schneeberger Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Rosana Quintana Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Cecilia Pisoni Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Mariana Pera Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Edson Velozo Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Dora Aida Pereira Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Paula Alba Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Juan A Albiero Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Jaime Villafañe Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Hernan Maldonado Ficco Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Veronica Sa io Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Santiago Eduardo Aguero Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Romina Rojas Tessel Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Maria Isabel Quaglia Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., María Soledad Gálvez Elkin Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access tothe information collected in the database., Gisela Paola Pendon Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Carolina Aeschlimann Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Gustavo Fabian Rodriguez Gil Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Malena Viola Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Cecilia Romeo Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Carla Maldini Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Silvana Mariela Conti Grant/research support from: SAR-COVID is a multi-sponsor re istry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Rosana Gallo Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Leticia Ibañez Zurlo Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Maria Natalia Tamborenea Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Susana Isabel Pineda Vidal Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Debora Guaglianone Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Jonatan Marcos Mareco Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Cecilia Goizueta Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Elisa Novatti Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Fernanda Guzzanti Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Gimena Gómez Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Karen Roberts Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of t em participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database., Guillermo Pons-Estel Grant/research support from: SAR-COVID is a multi-sponsor registry, where Pfizer, Abbvie, and Elea Phoenix provided unrestricted grants. None of them participated or influenced the development of the project, data collection, analysis, interpretation, or writing the report. They do not have access to the information collected in the database.
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Introduction: The coronavirus disease (COVID-19) has spread among the population of Costa Rica and has had a great global impact. However, there are important geographic differences in mortality from COVID-19 among world regions and within Costa Rica.Objective: To explore the effect of some sociodemographic factors on COVID-19 mortality in the small geo-graphic divisions or cantons of Costa Rica.Methods: We used official records and applied a classical epidemiological Poisson regression model and a geographically weighted regression model.Results: We obtained a lower Akaike Information Criterion with the weighted regression (927.1 in Poisson regression versus 358.4 in weighted regression). The cantons with higher risk of mortality from COVID-19 had a denser population;higher material well-being;less population by health service units and are located near the Pacific coast.Conclusions: A specific COVID-19 intervention strategy should concentrate on Pacific coast areas with denser population, higher material well-being and less population by health service units.
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The tourism industry is a major branch of the service sector that contributes to national wealth creation. It is one of the main drivers of employment and foreign exchange drainage in the economies. However, some tragic events affect and slow down its development. The epidemiological context of the coronavirus has deeply affected the sector, implying a total halt to all tourist activities at national and international levels. In this sense, Dauphiné and Provitolo (2007) [16] state that "it is then possible to adopt another strategy based on the concept of resilience. This strategy aims, not to oppose the hazard, but to reduce its impacts as much as possible. From this reflection, we have attempted in this essay to clarify and analyze the determinants of resilience summarised in the characteristics linked to the environment, the strategies implemented, the personal traits of the manager, and the characteristics specific to tourism organizations contributing to helping these Moroccan economic units, specifically in the Rabat-Salé-Kénitra region, to overcome the setbacks caused by the covid-19 health crisis. © 2023 Little Lion Scientific.
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Insomnia is a major health issue associated with great psychological burden. Research of insomnia during a pandemic crisis is limited. The aim of the present study was to explore sleep difficulties during the COVID-19 pandemic in a Greek population. The three-day online survey included questions about sociodemographic characteristics, contact with COVID-19 and COVID-19-related negative attitudes, as well as the Athens Insomnia Scale (AIS), the Intolerance to Uncertainty scale (IUS), the De Jong Gierveld Loneliness scale (JGLS) and the Patient Health Questionnaire-2 (PHQ-2) Depression Scale. Altogether, 2,427 individuals participated in the study (with 2,363 of them providing all basic demographic data). Sleep problems were detected in 37.6% of the participants. Women and people in urban areas were more vulnerable to sleep problems, while younger age showed a non-significant trend. Those uncertain about having themselves, or someone close to them contracted the virus, also demonstrated elevated insomnia scores. Lastly, according to the regression analysis, higher levels of intolerance to uncertainty, COVID-19-related worry, loneliness, as well as more severe depressive symptoms, were all predictive of insomnia. Results may be used for the development of therapeutic strategies and implementation of social policies to support people with sleep difficulties.
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In generalized linear models (GLMs), measures of lack of fit are typically defined as the deviance between two nested models, and a deviance-based R2 is commonly used to evaluate the fit. In this paper, we extend deviance measures to mixtures of GLMs, whose parameters are estimated by maximum likelihood (ML) via the EM algorithm. Such measures are defined both locally, i.e., at cluster-level, and globally, i.e., with reference to the whole sample. At the cluster-level, we propose a normalized two-term decomposition of the local deviance into explained, and unexplained local deviances. At the sample-level, we introduce an additive normalized decomposition of the total deviance into three terms, where each evaluates a different aspect of the fitted model: (1) the cluster separation on the dependent variable, (2) the proportion of the total deviance explained by the fitted model, and (3) the proportion of the total deviance which remains unexplained. We use both local and global decompositions to define, respectively, local and overall deviance R2 measures for mixtures of GLMs, which we illustrate-for Gaussian, Poisson and binomial responses-by means of a simulation study. The proposed fit measures are then used to assess, and interpret clusters of COVID-19 spread in Italy in two time points.
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Background: Social media platforms are frequently used by the general public to access health information, including information relating to complementary and alternative medicine (CAM). The aim of this study was to measure how often naturopathic influencers make evidence-informed recommendations on Instagram, and to examine associations between the level of evidence available or presented, and user engagement. Methods: A retrospective observational study using quantitative content analysis on health-related claims made by naturopathic influencers with 30000 or more followers on Instagram was conducted. Linear regression was used to measure the association between health-related posts and the number of Likes, and Comments. Results: A total of 494 health claims were extracted from eight Instagram accounts, of which 242 (49.0%) were supported by evidence and 34 (6.9%) included a link to evidence supporting the claim. Three naturopathic influencers did not provide any evidence to support the health claims they made on Instagram. Posts with links to evidence had fewer Likes (B=-1343.9, 95% CI=-2424.4 to -263.4, X=-0.1, P=0.02) and fewer Comments (B=-82.0, 95% CI=-145.9 to -18.2, X=-0.2, P=0.01), compared to posts without links to evidence. The most common areas of health were claims relating to 'women's health' (n=94; 19.0%), and 'hair, nail and skin' (n=74; 15.0%). Conclusion: This study is one of the first to look at the evidence available to support health-related claims by naturopathic influencers on Instagram. Our findings indicate that around half of Instagram posts from popular naturopathic influencers with health claims are supported by high-quality evidence.
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Introduction: COVID-19 policies such as quarantining, social isolation, and lockdowns are an essential public health measure to reduce the spread of disease but may lead to reduced physical activity. Little is known if these changes are associated with changes in physical or mental health. Method(s): Between September 2017 and December 2018 (baseline) and March 2020 and February 2021 (follow-up), we obtained self-reported demographic, health, and walking (only at follow-up) data on 2042 adults in primary care with multiple chronic health conditions. We examined whether the perceived amount of time engaged in walking was different compared with prepandemic levels and if this was associated with changes in Patient-Reported Outcomes Measurement Information System-29 mental and physical health summary scores. Multivariable linear regression controlling for demographic, health, and neighborhood information were used to assess this association. Result(s): Of the 2042 participants, 9% reported more walking, 28% reported less, and 52% reported the same amount compared with prepandemic levels. Nearly 1/3 of participants reported less walking during the pandemic. Multivariable models revealed that walking less or not at all was associated with negative changes in mental (s = -1.0;95% CI [-1.6, -0.5];s = -2.2;95% CI [-2.9, -1.4]) and physical (s = -0.9;95% CI [-1.5, -0.3];s = -3.1;95% CI [-4.0, -2.3]) health, respectively. Increasing walking was significantly associated with a positive change in physical health (s = 1.3;95% CI [0.3, 2.2]). Conclusion(s): These findings demonstrate the importance of walking during the COVID-19 pandemic. Promotion of physical activity should be taken into consideration when mandating restrictions to slow the spread of disease. Primary care providers can assess patient's walking patterns and implement brief interventions to help patients improve their physical and mental health through walking. Copyright © 2022 American Board of Family Medicine. All rights reserved.
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Introducción: La atención primaria es el pilar fundamental de un sistema de salud efectivo;el incumplimiento de los atributos esenciales podría contribuir al colapso de los sistemas de salud en eventuales pandemias. Objetivo: Evaluar el cumplimiento de los atributos de la atención primaria y sus factores asociados, según perspectiva del usuario externo en el contexto de la pandemia por COVID-19, en una región del Perú. Método: Estudio transversal, que incluyó 1064 usuarios externos, seleccionados aleatoriamente. Utilizando la Encuesta se recogieron características sociodemográficas y de salud. El cumplimiento de los atributos de la atención primaria fue valorado con la versión modificada del instrumento PCAT-A10. Se realizó un análisis descriptivo y multivariado mediante modelos lineales generalizados de la familia Poisson para evaluar ciertos factores asociados al incumplimiento de los atributos de la atención primaria. Resultados: De los participantes, el 76,6% perciben que los atributos básicos esenciales se incumplen;asimismo, en el primer contacto (74,7%), continuidad (87,8%), coordinación (95,7%), globalidad (88,3%) y competencia cultural (75,9%). La condición de estudiante (p<0,001), autopercepción de salud regular (p=0,010), adulto de 30 a 59 años (p<0,001) y la condición de usuarios del centro de salud Subtanjalla (p=0,001), Parcona (p<0,001) y Guadalupe (p<0,001), se encuentran asociados a mayor percepción de incumplimiento de los atributos de la atención primaria. Conclusiones: Desde la perspectiva de los usuarios externos los atributos esenciales son incumplidos en los centros de atención primaria;existen factores asociados a mayor probabilidad de percibir que estos atribuidos son incumplidos.Alternate :Introduction: Primary care attention is the fundamental pillar of an effective health system;a failure to comply with its essential attributes could contribute to the collapse of the health systems in the event of pandemics. Objective: To evaluate the compliance of the primary attention's attributes and its associated factors, according to the external user's perspective in the context of the COVID-19 pandemic in a Peruvian region. Method: Cross-sectional study, which included 1064 randomly selected external users. Also, the sociodemographic and health characteristics were collected using the survey. And the compliance of the primary care attributes was valued using the modified version of the PCAT-A10 instrument. Finally, a descriptive and multivariate analysis was performed using generalized linear models of the Poisson family to evaluate certain factors associated with noncompliance with the attributes of primary care. Results: 76.6% of the participants perceive that the essential basic attributes are not met;likewise, in the first contact (74.7%), continuity (87.7%), coordination (95.7%), globality (88.3%) and cultural competence (75.9%). The student condition (p<0,001), self-perception of regular health (p=0.010), adult from 30 to 59 years old (p<0.001), and the condition of users of Subtanjalla (p=0.001), Parcona (p<0.001) and Guadalupe (p<0.001) health centers were associated with a greater perception of noncompliance with the attributes of primary health care. Conclusions: From the external user's perspective the essential attributes are met in primary care centers;there are factors associated with a greater probability of perceiving that these attributes are not met.
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Background: Transmission of SARS-CoV-2 in acute-care settings affects patients, healthcare workers, and the already-burdened healthcare system. An analysis of risk factors associated with outbreak severity was conducted to inform prevention strategies. Methods: This study was a cross-sectional analysis of COVID-19 outbreaks at Fraser Health (FH) acute-care sites between March 2020 and March 2021. Outbreak severity measures included COVID-19 attack rate, outbreak duration, and 30-day case mortality. Covariates at patient, outbreak, unit level, and facility level were included (Table 1). Generalized linear models with generalized estimation equations were used for all outcome measures, with outbreak duration and 30-day case mortality using multivariate negative binomial distributions, and attack rate using Gaussian distribution. A P value of .05 indicated statistical significance. Analyseswere performed using SAS version 3.8 software, R version 4.1.0 software, and Stata version 16.0 software. Results: Between March 2020 and March 2021, 54 COVID-19 outbreaks were declared in FH acute-care sites involving 455 SARS-CoV-2–positive patients. The average outbreak duration was 23 days, the average attack rate was 28%, and the average 30-day all-cause mortality per outbreak was 2 deaths. The results of the full models are shown in Table 1. Discussion: We identified an inverse relationship between increased hand hygiene compliance during outbreaks and all 3 severity measures. Paradoxically, hand hygiene rates in the year prior to the pandemic were positively associated with duration and mortality. Increased unit age was also associated with increases in each of the severity measures. Comorbidity total factor was correlated with outbreak attack rate and duration, demonstrating the importance of individual patient characteristics in an outbreak. Conclusions: Our findings highlight the importance of hand hygiene practices during an outbreak. Additionally, it is important to understand the difficulties faced by older facilities, many of which face infrastructural challenges. This study reinforces the need to incorporate infection control standards into healthcare planning and construction.Funding: NoneDisclosures: None
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OBJECTIVES: Although it is widely used as a measure for mortality, the case fatality rate (CFR) ofcoronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons otherthan viral characteristics. To compare the CFRs of different countries in equal measure, weestimated comparable CFRs after adjusting for multiple covariates and examined the mainfactors that contributed to variability in the CFRs among 21 countries. METHODS: For statistical analysis, time-series cross-sectional data were collected from OurWorld in Data, CoVariants.org, and GISAID. Biweekly CFRs of COVID-19 were estimated bypooled generalized linear squares regression models for the panel data. Covariates includedthe predominant virus variant, reproduction rate, vaccination, national economic status,hospital beds, diabetes prevalence, and population share of individuals older than age 65. Intotal, 21 countries were eligible for analysis. RESULTS: Adjustment for covariates reduced variation in the CFRs of COVID-19 across countriesand over time. Regression results showed that the dominant spread of the Omicron variant,reproduction rate, and vaccination were associated with lower country-level CFRs, whereasage, the extreme poverty rate, and diabetes prevalence were associated with higher countrylevel CFRs. CONCLUSION: A direct comparison of crude CFRs among countries may be fallacious, especiallyin a cross-sectional analysis. Our study presents an adjusted comparison of CFRs over timefor a more proper comparison. In addition, our findings suggest that comparing CFRs amongdifferent countries without considering their context, such as the epidemic phase, medicalcapacity, surveillance strategy, and socio-demographic traits, should be avoided.
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Introduction: In response to the requirement of keeping social distance during the COVID-19 outbreak a lot of employees needed to change from a regular office to a home-office at short notice. The aim of the present study is to explore these employees' experiences and evaluate changes in their work situation during the pandemic. Method: A mixed-method design was used with panel data collected twice in an insurance company in Norway. The first dataset was collected in December 2020 (Time 1; N = 558), with a follow up in March 2021 (Time 2; N = 601). Results: Our study indicated that employees' main reasons for working from home were to keep social distance, avoid contagion and protect their loved ones. Flexibility, timesaving and more time with family and friends were also motivators. Most employees reported that they had the necessary technical equipment to work from home and wanted more opportunity to use their home office in the future. General Linear Models (GLM) indicated that work-family balance and workload were the same across age, gender, and worksites. Women and employees working from home reported more fear of being infected by COVID-19 at work. Younger employees reported experiencing less social contact with colleagues than normal during the pandemic, compared to the older employees. Overall, employees working at home were more positive toward digital solutions and digital meetings than those at the office. Repeated measures MANOVA showed that the work motivation and digital competence decreased over time for all worksites. Productivity increased for home-office employees but decreased for the hybrid and work-office employees. Discussion: This paper contributes to knowledge of employees' experiences with different worksite solutions, which will be useful for anticipating employees experience in the future with more hybrid work.
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Objetivo: Este artigo estima o impacto das medidas de distanciamento social sobre a incidência de COVID-19 a partir de uma perspectiva multissetorial. Métodos: O desenho de pesquisa utiliza um modelo de regressão em painel para analisar a relação entre restrições de mobilidade em diferentes setores econômicos e a dinâmica longitudinal da doença nos estados do Brasil. Resultados: Os principais resultados indicam que apenas os coeficientes das variáveis que representam os setores de restaurantes (p-valor < 0,05), compras (p-valor < 0,05) e transporte (p-valor < 0,001) obtiveram significância estatística. Em especial, o transporte (ß= -0,674) é a variável que mais influencia a variação do número de casos de COVID-19. Conclusões: As evidências reportadas nesta pesquisa podem auxiliar o processo de tomada de decisão dos gestores governamentais a respeito da eficácia de intervenções não farmacológicas como instrumento para reduzir a disseminação da COVID-19 (AU)
Objective: This article estimates the impact of social distancing measures on the incidence of COVID-19 from a multisectoral perspective. Methods: The research design uses a panel regression model to analyze the relationship between mobility restrictions in different economic sectors and the longitudinal dynamics of the infection across Brazilian states. Results: The main results indicate that only the coefficients for the restaurant (p-value < 0.05), shopping (p-value < 0.05), and transport sectors (p-value < 0.001) reached statistical significance. In particular, transport (ß = -0.674) is the variable with the strongest impact on the variation in the number of COVID-19 cases. Conclusions: The evidence reported in this research can assist the decision-making process of government managers regarding the effectiveness of non-pharmacological interventions as a tool to reduce the spread of COVID-19
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Humans , Incidence , Surveys and Questionnaires , Commerce , Physical Distancing , COVID-19/prevention & controlABSTRACT
Objetivo: Este artigo estima o impacto das medidas de distanciamento social sobre a incidência de COVID-19 a partir de uma perspectiva multissetorial. Métodos: O desenho de pesquisa utiliza um modelo de regressão em painel para analisar a relação entre restrições de mobilidade em diferentes setores econômicos e a dinâmica longitudinal da doença nos estados do Brasil. Resultados: Os principais resultados indicam que apenas os coeficientes das variáveis que representam os setores de restaurantes (p-valor < 0,05), compras (p-valor < 0,05) e transporte (p-valor < 0,001) obtiveram significância estatística. Em especial, o transporte (ß= -0,674) é a variável que mais influencia a variação do número de casos de COVID-19. Conclusões: As evidências reportadas nesta pesquisa podem auxiliar o processo de tomada de decisão dos gestores governamentais a respeito da eficácia de intervenções não farmacológicas como instrumento para reduzir a disseminação da COVID-19 (AU)
Objective: This article estimates the impact of social distancing measures on the incidence of COVID-19 from a multisectoral perspective. Methods: The research design uses a panel regression model to analyze the relationship between mobility restrictions in different economic sectors and the longitudinal dynamics of the infection across Brazilian states. Results: The main results indicate that only the coefficients for the restaurant (p-value < 0.05), shopping (p-value < 0.05), and transport sectors (p-value < 0.001) reached statistical significance. In particular, transport (ß = -0.674) is the variable with the strongest impact on the variation in the number of COVID-19 cases. Conclusions: The evidence reported in this research can assist the decision-making process of government managers regarding the effectiveness of non-pharmacological interventions as a tool to reduce the spread of COVID-19
Subject(s)
Humans , Incidence , Surveys and Questionnaires , Commerce , Physical Distancing , COVID-19/prevention & controlABSTRACT
The optimization of resources for research in developing countries forces us to consider strategies in the wet lab that allow the reuse of molecular biology reagents to reduce costs. In this study, we used linear regression as a method for predictive modeling of coverage depth given the number of MinION reads sequenced to define the optimum number of reads necessary to obtain >200X coverage depth with a good lineage-clade assignment of SARS-CoV-2 genomes. The research aimed to create and implement a model based on machine learning algorithms to predict different variables (e.g., coverage depth) given the number of MinION reads produced by Nanopore sequencing to maximize the yield of high-quality SARS-CoV-2 genomes, determine the best sequencing runtime, and to be able to reuse the flow cell with the remaining nanopores available for sequencing in a new run. The best accuracy was -0.98 according to the R squared performance metric of the models. A demo version is available at https://genomicdashboard.herokuapp.com/.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Sequence Analysis, DNA/methods , SARS-CoV-2/genetics , High-Throughput Nucleotide Sequencing/methods , GenomeABSTRACT
In the era of big data, standard analysis tools may be inadequate for making inference and there is a growing need for more efficient and innovative ways to collect, process, analyze and interpret the massive and complex data. We provide an overview of challenges in big data problems and describe how innovative analytical methods, machine learning tools and metaheuristics can tackle general healthcare problems with a focus on the current pandemic. In particular, we give applications of modern digital technology, statistical methods,data platforms and data integration systems to improve diagnosis and treatment of diseases in clinical research and novel epidemiologic tools to tackle infection source problems, such as finding Patient Zero in the spread of epidemics. We make the case that analyzing and interpreting big data is a very challenging task that requires a multi-disciplinary effort to continuously create more effective methodologies and powerful tools to transfer data information into knowledge that enables informed decision making.
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PURPOSE: Many patients delayed health care during COVID-19. We assessed the extent to which patients managing multiple chronic conditions (MCC) delayed care in the first months of the pandemic, reasons for delay, and impact of delay on patient-reported physical and behavioral health (BH) outcomes. METHODS: As part of a large clinical trial conducted April 2016-June, 2021, primary care patients managing MCC were surveyed about physical and behavioral symptoms and functioning. Surveys administered between September 3, 2020, and March 16, 2021, included questions about the extent of and reasons for any delayed medical and BH care since COVID-19. Multivariable linear regression was used to assess health outcomes as a function of delay of care status. RESULTS: Among patients who delayed medical care, 58% delayed more than once. Among those who delayed behavioral health care, 63% delayed more than once. Participants who delayed multiple times tended to be younger, female, unmarried, and reported food, financial, and housing insecurities and worse health. The primary reasons for delaying care were lack of availability of in-person visits and perceived lack of urgency. Participants who delayed care multiple times had significantly worse outcomes on nearly every measure of physical and mental health, compared with participants who delayed care once or did not delay. CONCLUSIONS: Delay of care was substantial. Patients who delayed care multiple times were in poorer health and thus in need of more care. Effective strategies for reengaging patients in deferred care should be identified and implemented on multiple levels. TRIAL REGISTRATION: ClinicalTrials.gov NCT02868983. Registered on August 16, 2016.
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Climate variables play a critical role in COVID-19's spread. Therefore, this research aims to analyze the effect of average temperature and relative humidity on the propagation of COVID-19 in Africa's first four affected countries (South Africa, Morocco, Tunisia, and Ethiopia). As a result, policymakers should develop effective COVID-19 spread control strategies. For each country, using daily data of confirmed cases and weather variables from May 1, 2020, to April 30, 2021, generalized linear models (Poisson regression) and general linear models were estimated. According to the findings, the rising average temperature causes COVID-19 daily new cases to increase in South Africa and Ethiopia while decreasing in Morocco and Tunisia. However, in Tunisia, the relative humidity and daily new cases of COVID-19 are positively correlated, while in the other three countries, they are negatively associated.