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1.
PLoS One ; 18(6): e0285247, 2023.
Article in English | MEDLINE | ID: covidwho-20238784

ABSTRACT

The advanced manufacturing industry is located at the top of the manufacturing value chain. Its development is restricted by supply chain collaboration (SCC), the level of which is affected by many factors. Few studies comprehensively summarize what influences SCC and distinguish the impact level of each factor. Practitioners have difficulty isolating the primary factors that affect SCC and managing them effectively. Therefore, based on synergetics and the theory of comparative advantage, this study analyzes what influences SCC in the advanced manufacturing industry and how these influencing factors work, using data from 94 manufacturing enterprises and the Haken model to identify the influencing factors. The results show that China's advanced manufacturing supply chain underwent a phase change and entered a new stage during 2017-2018. In the new stage, the competitive advantages of enterprises are one order parameter (slow variable) and are primary factors affecting SCC. The interest demands of enterprises are a fast variable and are secondary factors affecting SCC. The competitive advantages of enterprises dominate the interests of enterprises in affecting the collaboration level of China's advanced manufacturing supply chain. In addition, in the process of influencing SCC, there is a positive correlation between the competitive advantages of enterprises and the interest demands of enterprises, and the two factors have a positive feedback mechanism. Finally, when the enterprises in the supply chain cooperate based on their differential advantages, the collaboration capability of the supply chain is at the highest level, and the overall operation of the supply chain is orderly. In terms of theoretical contribution, this study is the first to propose a collaborative motivation framework that conforms to the characteristics of sequential parameters, which provides a theoretical reference for subsequent studies on SCC. In addition, the theory of comparative advantage and synergetics are linked for the first time in this study, and both of them are enriched and developed. Equally importantly, this study compares the bidirectional influence between firms' competitive advantages and firms' interest demands and the ability of both to influence SCC, enriching previous validation studies of unidirectional influence. In terms of practical implications, this study guides top managers to focus on the management practice of collaborative innovation in the supply chain and advises purchasing managers and sales managers on selecting supply chain partnerships.


Subject(s)
Commerce , Manufacturing Industry , Motivation , Records , China
2.
BMC Med Educ ; 23(1): 366, 2023 May 23.
Article in English | MEDLINE | ID: covidwho-20244818

ABSTRACT

The global COVID-19 pandemic has shown the need for internationalization of medical education, in order to facilitate global collaborative problem solving in healthcare. In 2023, it is time to reshape IoME within the context of our time, and share new visions, ideas, and formats. This collection of articles reports on theories and actions in IoME.


Subject(s)
COVID-19 , Education, Medical , Humans , Pandemics , Problem Solving , Records
3.
Sci Rep ; 13(1): 8591, 2023 05 26.
Article in English | MEDLINE | ID: covidwho-20241826

ABSTRACT

The ability to extract critical information about an infectious disease in a timely manner is critical for population health research. The lack of procedures for mining large amounts of health data is a major impediment. The goal of this research is to use natural language processing (NLP) to extract key information (clinical factors, social determinants of health) from free text. The proposed framework describes database construction, NLP modules for locating clinical and non-clinical (social determinants) information, and a detailed evaluation protocol for evaluating results and demonstrating the effectiveness of the proposed framework. The use of COVID-19 case reports is demonstrated for data construction and pandemic surveillance. The proposed approach outperforms benchmark methods in F1-score by about 1-3%. A thorough examination reveals the disease's presence as well as the frequency of symptoms in patients. The findings suggest that prior knowledge gained through transfer learning can be useful when researching infectious diseases with similar presentations in order to accurately predict patient outcomes.


Subject(s)
COVID-19 , Natural Language Processing , Humans , COVID-19/epidemiology , Electronic Health Records , Records , Pandemics
4.
Stud Health Technol Inform ; 301: 162-167, 2023 May 02.
Article in English | MEDLINE | ID: covidwho-2317652

ABSTRACT

BACKGROUND: Dashboards provide a good retrospective view of the development of the disease. Yet, current COVID-related dashboards typically lack the capability to predict future trends. However, this is important for health policy makers and health care providers in order to adopt meaningful containment strategies. OBJECTIVES: The aim of this paper is to present the Surviral dashboard, which allows the effective monitoring of infectious disease dynamics. METHODS: The presented dashboard comprises a wide range of information, including retrospective and prognostic data based on an agent-based simulation framework. It served as the basis for informed decision-making and planning of disease control strategies within the federal state of Tyrol. RESULTS: By visualizing the information in an understandable format, the dashboard provided a comprehensive overview of the COVID-19 situation in Tyrol and allowed for the identification of trends and patterns. CONCLUSION: The presented dashboard is a valuable tool for managing pandemics such as COVID-19. It provides a convenient and efficient way to monitor the spread of a disease and identify potential areas for intervention.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Retrospective Studies , Health Policy , Records , Health Personnel
5.
Epidemiol Serv Saude ; 32(1): e2022183, 2023.
Article in English, Portuguese | MEDLINE | ID: covidwho-2273010

ABSTRACT

OBJECTIVE: to analyze the difference in the number of primary teeth dental procedures performed within the Brazilian National Health System (SUS) in the state of Rio Grande do Sul, before and during the COVID-19 pandemic. METHODS: this was a descriptive ecological study, using secondary data from the SUS Outpatient Information System (SIA-SUS), from 2018 to 2021, in the state and in its seven health macro-regions; we calculated the relative and absolute frequencies and the percentage difference of the dental procedures performed. RESULTS: 94,443 and 36,151 dental procedures were recorded before and during the pandemic, respectively, corresponding to a 61.7% reduction; relevant percentage reductions were found in restorative procedures, which reached 20% in the southern region of the state; an increase in the percentage of exodontic and endodontic procedures was found. CONCLUSION: the results suggest that the COVID-19 pandemic had negative repercussions on the performance of primary teeth dental procedures in Ro Grande do Sul.


Subject(s)
COVID-19 , Pandemics , Child , Humans , Brazil/epidemiology , Pediatric Dentistry , COVID-19/epidemiology , Records
6.
PLoS One ; 18(3): e0283092, 2023.
Article in English | MEDLINE | ID: covidwho-2279100

ABSTRACT

The constant increase in survey nonresponse and fieldwork costs are the reality of survey research. Together with other unpredictable events occurring in the world today, this increase poses a challenge: the necessity to accelerate a switch from face-to-face data collection to different modes, that have usually been considered to result in lower response rates. However, recent research has established that the simple response rate is a feeble measure of study quality. Therefore, this article aims to analyze the effect of survey characteristics, especially the survey mode, on the nonresponse bias. The bias measure used is the internal criteria first proposed by Sodeur and first applied by Kohler. The analysis is based on the survey documentation and results from the International Social Survey Programme waves 1996-2018 and the European Social Survey rounds 1 to 9. Random-effects three-level meta-regression models, based on data from countries from each inhabited continent, were created in order to estimate the impact of the survey mode or modes, sampling design, fieldwork experience, year of data collection, and response rate on the nonresponse bias indicator. Several ways of nesting observations within clusters were also proposed. The results suggest that using mail and some types of mixed-mode surveys were connected to lower nonresponse bias than using face-to-face mode surveys.


Subject(s)
Records , Surveys and Questionnaires , Data Collection/methods , Bias , Costs and Cost Analysis
7.
PLoS One ; 18(3): e0277166, 2023.
Article in English | MEDLINE | ID: covidwho-2267653

ABSTRACT

The article focuses on measuring the fluctuations in countries' development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Public Health , Pandemics , Economic Development , Records
8.
J Biomed Inform ; 139: 104306, 2023 03.
Article in English | MEDLINE | ID: covidwho-2220929

ABSTRACT

BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.


Subject(s)
COVID-19 , Electronic Health Records , Humans , Data Collection , Records , Cluster Analysis
9.
Vaccine ; 41(7): 1390-1397, 2023 02 10.
Article in English | MEDLINE | ID: covidwho-2165934

ABSTRACT

Recent evidence suggests that COVID-19 vaccine hesitancy is not static. In order to develop effective vaccine uptake interventions, we need to understand the extent to which vaccine hesitancy fluctuates and identify factors associated with both between- and within-person differences in vaccine hesitancy. The goals of the current study were to assess the extent to which COVID-19 vaccine hesitancy varied at an individual level across time and to determine whether disgust sensitivity and germ aversion were associated with between- and within-person differences in COVID-19 vaccine hesitancy. A national sample of U.S. adults (N = 1025; 516 woman; Mage = 46.34 years, SDage = 16.56, range: 18 to 85 years; 72.6 % White) completed six weekly online surveys (March 20 - May 3, 2020). Between-person mean COVID-19 vaccine hesitancy rates were relatively stable across the six-week period (range: 38-42 %). However, there was considerable within-person variability in COVID-19 vaccine hesitancy. Approximately, 40 % of the sample changed their vaccine hesitancy at least once during the six weeks. There was a significant between-person effect for disgust sensitivity, such that greater disgust sensitivity was associated with a lower likelihood of COVID-19 vaccine hesitance. There was also a significant within-person effect for germ aversion. Participants who experienced greater germ aversion for a given week relative to their own six week average were less likely to be COVID-19 vaccine hesitant that week relative to their own six-week average. This study provides important information on rapidly changing individual variability in COVID-19 vaccine hesitancy on a weekly basis, which should be taken into consideration with any efforts to decrease vaccine hesitancy and increase vaccine uptake. Further, these findings identify-two psychological factors (disgust sensitivity and germ aversion) with malleable components that could be leveraged in developing vaccine uptake interventions.


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , Female , Humans , United States , Middle Aged , Adolescent , COVID-19/prevention & control , Individuality , Probability , Records , Vaccination
10.
Int J Environ Res Public Health ; 19(24)2022 12 10.
Article in English | MEDLINE | ID: covidwho-2155107

ABSTRACT

During the initial phase of the coronavirus disease 2019 (COVID-19) pandemic, there was a critical need to create a valid and reliable screening and surveillance for university staff and students. Consequently, 11 medical experts participated in this cross-sectional study to judge three risk categories of either low, medium, or high, for all 1536 possible combinations of 11 key COVID-19 predictors. The independent experts' judgement on each combination was recorded via a novel dashboard-based rating method which presented combinations of these predictors in a dynamic display within Microsoft Excel. The validated instrument also incorporated an innovative algorithm-derived deduction for efficient rating tasks. The results of the study revealed an ordinal-weighted agreement coefficient of 0.81 (0.79 to 0.82, p-value < 0.001) that reached a substantial class of inferential benchmarking. Meanwhile, on average, the novel algorithm eliminated 76.0% of rating tasks by deducing risk categories based on experts' ratings for prior combinations. As a result, this study reported a valid, complete, practical, and efficient method for COVID-19 health screening via a reliable combinatorial-based experts' judgement. The new method to risk assessment may also prove applicable for wider fields of practice whenever a high-stakes decision-making relies on experts' agreement on combinations of important criteria.


Subject(s)
COVID-19 , Public Health , Humans , Cross-Sectional Studies , COVID-19/epidemiology , Risk Assessment , Records
11.
BMJ ; 379: o2941, 2022 12 05.
Article in English | MEDLINE | ID: covidwho-2152974
12.
PLoS One ; 17(11): e0277924, 2022.
Article in English | MEDLINE | ID: covidwho-2140674

ABSTRACT

Interactions between stock and cryptocurrency markets have experienced shifts and changes in their dynamics. In this paper, we study the connection between S&P500 and Bitcoin in higher-order moments, specifically up to the fourth conditional moment, utilizing the time-scale perspective of the wavelet coherence analysis. Using data from 19 August 2011 to 14 January 2022, the results show that the co-movement between Bitcoin and S&P500 is moment-dependent and varies across time and frequency. There is very weak or even non-existent connection between the two markets before 2018. Starting 2018, but mostly 2019 onwards, the interconnections emerge. The co-movements between the volatility of Bitcoin and S&P500 intensified around the COVID-19 outbreak, especially at mid-term scales. For skewness and kurtosis, the co-movement is stronger and more significant at mid- and long-term scales. A partial-wavelet coherence analysis underlines the intermediating role of economic policy uncertainty (EPU) in provoking the Bitcoin-S&P500 nexus. These results reflect the co-movement between US stock and Bitcoin markets beyond the second moment of return distribution and across time scales, suggesting the relevance and importance of considering fat tails and return asymmetry when jointly considering US equity-Bitcoin trading or investments and the policy formulation for the sake of US market stability.


Subject(s)
COVID-19 , Models, Economic , Humans , Commerce , COVID-19/epidemiology , Investments , Records
13.
PLoS One ; 17(11): e0277756, 2022.
Article in English | MEDLINE | ID: covidwho-2140661

ABSTRACT

In a financial system, entities (e.g., companies or markets) face systemic risk that could lead to financial instability. To prevent this impact, we require quantitative systemic risk management we can carry out using conditional value-at-risk (CoVaR) and a network model. The former measures any targeted entity's tail risk conditional on another entity being financially distressed; the latter represents the financial system through a set of nodes and a set of edges. In this study, we modify CoVaR along with its multivariate extension (MCoVaR) considering the joint conditioning events of multiple entities. We accomplish this by first employing a multivariate Johnson's SU risk model to capture the asymmetry and leptokurticity of the entities' asset returns. We then adopt the Cornish-Fisher expansion to account for the analytic higher-order conditional moments in modifying (M)CoVaR. In addition, we attempt to construct a conditional tail risk network. We identify its edges using a corresponding Delta (M)CoVaR reflecting the systemic risk contribution and further compute the strength and clustering coefficient of its nodes. When applying the financial system to global foreign exchange (forex) markets before and during COVID-19, we revealed that the resulting expanded (M)CoVaR forecast exhibited a better conditional coverage performance than its unexpanded version. Its superior performance appeared to be more evident over the COVID-19 period. Furthermore, our network analysis shows that advanced and emerging forex markets generally play roles as net transmitters and net receivers of systemic risk, respectively. The former (respectively, the latter) also possessed a high tendency to cluster with their neighbors in the network during (respectively, before) COVID-19. Overall, the interconnectedness and clustering tendency of the examined global forex markets substantially increased as the pandemic progressed.


Subject(s)
COVID-19 , Mustelidae , Animals , COVID-19/epidemiology , Internationality , Records , Pandemics , Administration, Cutaneous
14.
Int J Environ Res Public Health ; 19(5)2022 Mar 05.
Article in English | MEDLINE | ID: covidwho-1732030

ABSTRACT

BACKGROUND: Best practices for management of COVID-19 patients with acute respiratory failure continue to evolve. Initial debate existed over whether patients should be intubated in the emergency department or trialed on noninvasive methods prior to intubation outside the emergency department. OBJECTIVES: To determine whether emergency department intubations in COVID-19 affect mortality. METHODS: We conducted a retrospective observational chart review of patients who had a confirmed positive COVID-19 test and required endotracheal intubation during their hospital course between 1 March 2020 and 1 June 2020. Patients were divided into two groups based on location of intubation: early intubation in the emergency department or late intubation performed outside the emergency department. Clinical and demographic information was collected including comorbid medical conditions, qSOFA score, and patient mortality. RESULTS: Of the 131 COVID-19-positive patients requiring intubation, 30 (22.9%) patients were intubated in the emergency department. No statistically significant difference existed in age, gender, ethnicity, or smoking status between the two groups at baseline. Patients in the early intubation cohort had a greater number of existing comorbidities (2.5, p = 0.06) and a higher median qSOFA score (3, p ≤ 0.001). Patients managed with early intubation had a statistically significant higher mortality rate (19/30, 63.3%) compared to the late intubation group (42/101, 41.6%). CONCLUSION: COVID-19 patients intubated in the emergency department had a higher qSOFA score and a greater number of pre-existing comorbidities. All-cause mortality in COVID-19 was greater in patients intubated in the emergency department compared to patients intubated outside the emergency department.


Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Intubation, Intratracheal , Records , Retrospective Studies , SARS-CoV-2
15.
Annu Int Conf IEEE Eng Med Biol Soc ; 2021: 2252-2257, 2021 11.
Article in English | MEDLINE | ID: covidwho-1566196

ABSTRACT

Cough is one of the most common symptoms of COVID-19. It is easily recorded using a smartphone for further analysis. This makes it a great way to track and possibly identify patients with COVID. In this paper, we present a deep learning-based algorithm to identify whether a patient's audio recording contains a cough for subsequent COVID screening. More generally, cough identification is valuable for the remote monitoring and tracking of infections and chronic conditions. Our algorithm is validated on our novel dataset in which COVID-19 patients were instructed to volunteer natural coughs. The validation dataset consists of real patient cough and no cough audio. It was supplemented by files without cough from publicly available datasets that had cough-like sounds including: throat clearing, snoring, etc. Our algorithm had an area under receiver operating characteristic curve statistic of 0.977 on a validation set when making a cough/no cough determination. The specificity and sensitivity of the model on a reserved test set, at a threshold set by the validation set, was 0.845 and 0.976. This algorithm serves as a fundamental step in a larger cascading process to monitor, extract, and analyze COVID-19 patient coughs to detect the patient's health status, symptoms, and potential for deterioration.


Subject(s)
COVID-19 , Cough , Algorithms , Cough/diagnosis , Humans , Records , SARS-CoV-2
16.
Science ; 374(6569): 879-882, 2021 Nov 12.
Article in English | MEDLINE | ID: covidwho-1455668

ABSTRACT

The stalling of COVID-19 vaccination rates threatens public health. To increase vaccination rates, governments across the world are considering the use of monetary incentives. Here we present evidence about the effect of guaranteed payments on COVID-19 vaccination uptake. We ran a large preregistered randomized controlled trial (with 8286 participants) in Sweden and linked the data to population-wide administrative vaccination records. We found that modest monetary payments of 24 US dollars (200 Swedish kronor) increased vaccination rates by 4.2 percentage points (P = 0.005), from a baseline rate of 71.6%. By contrast, behavioral nudges increased stated intentions to become vaccinated but had only small and not statistically significant impacts on vaccination rates. The results highlight the potential of modest monetary incentives to raise vaccination rates.


Subject(s)
COVID-19 Vaccines , COVID-19/prevention & control , Intention , Reimbursement, Incentive , Vaccination/economics , Vaccination/methods , Adolescent , Adult , Female , Humans , Male , Middle Aged , Records , Sweden , Vaccination/statistics & numerical data , Young Adult
18.
Int J Environ Res Public Health ; 17(1)2020 01 01.
Article in English | MEDLINE | ID: covidwho-829330

ABSTRACT

This study examined the effect of disclosing a list of hospitals with Middle East respiratory syndrome coronavirus (MERS-CoV) patients on the number of laboratory-confirmed MERS-CoV cases in South Korea. MERS-CoV data from 20 May 2015 to 5 July 2015 were from the Korean Ministry of Health & Welfare website and analyzed using segmented linear autoregressive error models for interrupted time series. This study showed that the number of laboratory-confirmed cases was increased by 9.632 on 5 June (p < 0.001). However, this number was significantly decreased following disclosure of a list of hospitals with MERS-CoV cases (Estimate = -0.699; p < 0.001). Disclosing the list of hospitals exposed to MERS-CoV was critical to the prevention of further infection. It reduced the number of confirmed MERS-CoV cases. Thus, providing accurate and timely information is a key to critical care response.


Subject(s)
Coronavirus Infections , Disclosure , Disease Outbreaks , Adult , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Disclosure/statistics & numerical data , Disease Outbreaks/prevention & control , Female , Humans , Interrupted Time Series Analysis , Laboratories , Male , Middle East Respiratory Syndrome Coronavirus/physiology , Policy , Records , Republic of Korea/epidemiology
20.
Infect Control Hosp Epidemiol ; 41(12): 1449-1451, 2020 12.
Article in English | MEDLINE | ID: covidwho-733557

ABSTRACT

The early phase of the coronavirus disease 2019 (COVID-19) pandemic and ongoing efforts for mitigation underscore the importance of universal travel and symptom screening. We analyzed adherence to documentation of travel and symptom screening through a travel navigator tool with clinical decision support to identify patients at risk for Middle East Respiratory Syndrome.


Subject(s)
COVID-19 , Communicable Disease Control , Communicable Diseases, Emerging , Coronavirus Infections , Mass Screening/methods , Travel Medicine , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Diseases, Emerging/epidemiology , Communicable Diseases, Emerging/prevention & control , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Decision Support Techniques , Guideline Adherence/statistics & numerical data , Humans , Massachusetts/epidemiology , Records , Risk Assessment/methods , SARS-CoV-2 , Travel/trends , Travel Medicine/methods , Travel Medicine/trends , Travel-Related Illness
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