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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
25 Research products, page 1 of 3

  • COVID-19
  • Publications
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  • University of Southern Denmark Research Output

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  • Closed Access English
    Authors: 
    Glintborg, B.; Jensen, D. V.; Engel, S.; Terslev, L.; Jensen, M. Pfeiffer; Hendricks, O.; Ostergaard, M.; Rasmussen, S. H.; Adelsten, T.; Danebod, K.; +11 more
    Country: Denmark
  • Closed Access English
    Authors: 
    Emma Heeno; Irmelin Biesenbach; Charlotte Englund; Martin Lund; Anja Toft; Lars Lund;
    Country: Denmark

    Objective: In March-April 2020, during the coronavirus disease 2019 (COVID-19) pandemic lockdown in Denmark, the Danish Health Authorities recommended that, where possible, face-to-face patient-physician consultations be replaced by telephone consultations. The aim of this study was to obtain patients’ evaluation of their telemedicine experience. Methods: Patients who were candidates for telemedicine consultations were recruited based on their urological ailment, necessity for follow-up and comorbidity. New referrals including patients with suspicion of cancer were not candidates for telemedicine. In total, 548 patients had their appointment altered during the period from 13 March to 30 April 2020. Postal questionnaires were sent to 548 patients and 300 (54.7%) replied. Results: In total, 280 patient answered, 224 (80%) men and 56 (20%) women, mean age 69 years (range 18–91) of whom 180 (64.3%) had a benign and 100 (35.7%) a malignant diagnosis. Twenty (6.7%) respondents did not remember their telephone consultation and were therefore excluded. Telephone consultation satisfaction was reported by 230 (85.0%) patients, but they would not prefer video consultations over telephone consultations, and only 102 (36.4%) would prefer telephone consultations in the future. Patients’ age, sex and distance to the hospital did not seem to be associated with telephone consultation satisfaction (age p = 0.17; sex p = 0.99; distance p = 0.27, respectively). In total, 226 (80.7%) were medically assessed as being at risk for COVID, but 74 (26.4%) subjectively evaluated themselves as being at risk. Conclusions: In general (85.0%), urological patients were satisfied with telephone consultations.

  • Publication . Part of book or chapter of book . 2022
    Closed Access English
    Authors: 
    O'Hagan, John; Borowiecki, Karol J;
    Publisher: Routledge
    Country: Denmark

    The approach of this chapter is polemical in nature, reflecting the very fluid situation that lies ahead for orchestras post COVID-19. The chapter has three main academic research objectives. First, to put the current debate in context, it looks at the key challenges that orchestras have faced since the turn of the last century and in what way COVID-19 posed new problems that impacted orchestral music. The second objective is to outline some special short-term measures introduced to mitigate the impact of COVID-19, namely: (i) the income-support measures needed to sustain orchestras; and (ii) the extent to which orchestras could come together and practice, and in fact perform, even if only in front of no or very limited live audiences. The third objective is to discuss what possibly lies ahead for live orchestral music, post-COVID-19, and in a rapidly changing world regarding technological advances in the production and consumption of orchestral music. To inform this discussion, some broad trends in the ‘consumption’ of orchestral music over time, particularly in terms of numbers attending live concerts and revenues from streamed concerts, are examined.

  • Closed Access English
    Authors: 
    Shulzhenko, Elena; Secchi, Davide; Senderovitz, Martin; Hansen, Kristian Rune; van Bakel, Marian;
    Country: Denmark
  • Closed Access English
    Authors: 
    Olesen, T. W.; Tyler, P. D.; Lassen, A. T.; Shapiro I, N.; Burke, R. C.; Wolfe, R. E.;
    Country: Denmark
  • Publication . Part of book or chapter of book . 2020
    Closed Access English
    Authors: 
    Shuquan He; Maria Elo; Xiaotian Zhang; Julia Zhang;
    Publisher: Routledge
    Country: Denmark

    This chapter argues that China has been triple hit by the COVID-19 pandemic as it has caused a major trade shock, an investment shock and a business environment shock. To date, the globalized economies are interconnected by international trade, which makes trade an important vehicle for international contagion. Globalization and economic shocks are underpinned by a variety of forces affecting economic and societal changes creating a domino effect in global production networks. The impact of the COVID-19 pandemic on China’s overseas investment is manifold. Chinese businesses are exposed to the changing international business environment as perceptions on China’s roles are shifting. The COVID-19 pandemic is changing the way business is conducted worldwide. As a result, Chinese companies are now confronted with a new international business environment that is moving away from globalization that had been creating opportunities for firms from emerging economies to grow their presence in global markets.

  • Closed Access English
    Authors: 
    Irena Koprinska; Michael Kamp; Annalisa Appice; Corrado Loglisci; Luiza Antonie; Albrecht Zimmermann; Riccardo Guidotti; Özlem Özgöbek; Rita P. Ribeiro; Ricard Gavaldà; +20 more
    Publisher: HAL CCSD
    Countries: France, Denmark

    This volume constitutes the refereed proceedings of the workshops which complemented the 20th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2020. Due to the COVID-19 pandemic the conference and workshops were held online. The 43 papers presented in volume were carefully reviewed and selected from numerous submissions. The volume presents the papers that have been accepted for the following workshops: 5th Workshop on Data Science for Social Good, SoGood 2020; Workshop on Parallel, Distributed and Federated Learning, PDFL 2020; Second Workshop on Machine Learning for Cybersecurity, MLCS 2020, 9th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2020, Workshop on Data Integration and Applications, DINA 2020, Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning, EDML 2020, Second International Workshop on eXplainable Knowledge Discovery in Data Mining, XKDD 2020; 8th International Workshop on News Recommendation and Analytics, INRA 2020.

  • Closed Access English
    Authors: 
    Signe Skovgaard Hviid; Veronica Pisinger; Sofie Have Hoffman; Johanne Aviaja Rosing; Janne Shurmann Tolstrup;
    Country: Denmark

    Objective: As alcohol is often consumed for social purposes, we aimed to explore how restrictions during the first Danish COVID-19 lockdown affected the alcohol use among adolescents aged 15–20. Method: In May 2020, 11,596 15- to 20-year-olds from two subpopulations answered a survey regarding their alcohol use and social life, as well as changes to these, during the Danish lockdown. Using survey data from all participants, we performed a multinomial logistic regression to assess the association between determinants of alcohol use and perceived change in alcohol use during the Danish lockdown. We used longitudinal data from one subpopulation ( n=1869) to perform negative binomial regressions exploring changes in frequency of alcohol use from 2019 to 2020. Results: Of all participants, 59% drank less, 75% had fewer in-person social interactions and 56% met more frequently online during lockdown. Girls were more likely than boys to have a perceived decrease in alcohol use during lockdown (odds ratio (OR)=1.41; 95% confidence interval (CI) 1.27–1.56). A perceived decrease in in-person social interaction during lockdown was associated with less drinking (OR=2.27; 95% CI 1.98–2.61), while a perceived increase in in-person social interaction during lockdown was associated with more drinking (OR=1.42; 95% CI 1.11–1.82) compared to unchanged drinking behaviour and social interaction. Conclusions: Adolescents in Denmark drank less during the Danish lockdown than before. Findings indicate that there is a close relationship between in-person social interactions and frequency of drinking. Drinking episodes when meeting online were rare and were not unambiguously associated with changes in drinking during lockdown.

  • Closed Access English
    Authors: 
    Skaarup, Kristoffer Grundtvig; Lassen, Mats Christian Højbjerg; Lind, Jannie Nørgaard; Alhakak, Alia Saed; Sengeløv, Morten; Nielsen, Anne Bjerg; Espersen, Caroline; Hauser, Raphael; Schöps, Liv Borum; Holt, Eva; +32 more
    Country: Denmark
  • Closed Access English
    Authors: 
    Amin Naemi; Mostafa Naemi; Romina Zarrabi Ekbatani; Thomas Schmidt; Ali Ebrahimi; Marjan Mansourvar; Uffe Kock Wiil;
    Publisher: Springer
    Country: Denmark

    This paper analyzes single and two-wave COVID-19 outbreaks using two novel hybrid models, which combine machine learning and statistical methods with Richards growth models, to simulate and forecast the spread of the infection. For this purpose, historical cumulative numbers of confirmed cases for three countries, including Iran, Italy, and Mexico, are used. The analysis of the Richards models shows that its single-stage form can model the cumulative number of infections in countries with a single wave of outbreak (Italy and Mexico) accurately while its performance deteriorates for countries with two-wave outbreaks (Iran), which clarifies the requirement of multi-stage Richards models. The results of multi-stage Richards models reveal that the prevention of the second wave could reduce the outbreak size in Iran by approximately 400,000 cases, and the pandemic could be controlled almost 7 months earlier. Although the cumulative size of outbreak is estimated accurately using multi-stage Richards models, the results show that these models cannot forecast the daily number of cases, which are important for health systems’ planning. Therefore, two novel hybrid models, including autoregressive integrated moving average (ARIMA)-Richards and nonlinear autoregressive neural network (NAR)-Richards, are proposed. The accuracy of these models in forecasting the number of daily cases for 14 days ahead is calculated using the test data set shows that forecast error ranges from 8 to 25%. A comparison between these hybrid models also shows that the machine learning-based models have superior performance compared with statistical-based ones and on average are 20% more accurate.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
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Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
25 Research products, page 1 of 3
  • Closed Access English
    Authors: 
    Glintborg, B.; Jensen, D. V.; Engel, S.; Terslev, L.; Jensen, M. Pfeiffer; Hendricks, O.; Ostergaard, M.; Rasmussen, S. H.; Adelsten, T.; Danebod, K.; +11 more
    Country: Denmark
  • Closed Access English
    Authors: 
    Emma Heeno; Irmelin Biesenbach; Charlotte Englund; Martin Lund; Anja Toft; Lars Lund;
    Country: Denmark

    Objective: In March-April 2020, during the coronavirus disease 2019 (COVID-19) pandemic lockdown in Denmark, the Danish Health Authorities recommended that, where possible, face-to-face patient-physician consultations be replaced by telephone consultations. The aim of this study was to obtain patients’ evaluation of their telemedicine experience. Methods: Patients who were candidates for telemedicine consultations were recruited based on their urological ailment, necessity for follow-up and comorbidity. New referrals including patients with suspicion of cancer were not candidates for telemedicine. In total, 548 patients had their appointment altered during the period from 13 March to 30 April 2020. Postal questionnaires were sent to 548 patients and 300 (54.7%) replied. Results: In total, 280 patient answered, 224 (80%) men and 56 (20%) women, mean age 69 years (range 18–91) of whom 180 (64.3%) had a benign and 100 (35.7%) a malignant diagnosis. Twenty (6.7%) respondents did not remember their telephone consultation and were therefore excluded. Telephone consultation satisfaction was reported by 230 (85.0%) patients, but they would not prefer video consultations over telephone consultations, and only 102 (36.4%) would prefer telephone consultations in the future. Patients’ age, sex and distance to the hospital did not seem to be associated with telephone consultation satisfaction (age p = 0.17; sex p = 0.99; distance p = 0.27, respectively). In total, 226 (80.7%) were medically assessed as being at risk for COVID, but 74 (26.4%) subjectively evaluated themselves as being at risk. Conclusions: In general (85.0%), urological patients were satisfied with telephone consultations.

  • Publication . Part of book or chapter of book . 2022
    Closed Access English
    Authors: 
    O'Hagan, John; Borowiecki, Karol J;
    Publisher: Routledge
    Country: Denmark

    The approach of this chapter is polemical in nature, reflecting the very fluid situation that lies ahead for orchestras post COVID-19. The chapter has three main academic research objectives. First, to put the current debate in context, it looks at the key challenges that orchestras have faced since the turn of the last century and in what way COVID-19 posed new problems that impacted orchestral music. The second objective is to outline some special short-term measures introduced to mitigate the impact of COVID-19, namely: (i) the income-support measures needed to sustain orchestras; and (ii) the extent to which orchestras could come together and practice, and in fact perform, even if only in front of no or very limited live audiences. The third objective is to discuss what possibly lies ahead for live orchestral music, post-COVID-19, and in a rapidly changing world regarding technological advances in the production and consumption of orchestral music. To inform this discussion, some broad trends in the ‘consumption’ of orchestral music over time, particularly in terms of numbers attending live concerts and revenues from streamed concerts, are examined.

  • Closed Access English
    Authors: 
    Shulzhenko, Elena; Secchi, Davide; Senderovitz, Martin; Hansen, Kristian Rune; van Bakel, Marian;
    Country: Denmark
  • Closed Access English
    Authors: 
    Olesen, T. W.; Tyler, P. D.; Lassen, A. T.; Shapiro I, N.; Burke, R. C.; Wolfe, R. E.;
    Country: Denmark
  • Publication . Part of book or chapter of book . 2020
    Closed Access English
    Authors: 
    Shuquan He; Maria Elo; Xiaotian Zhang; Julia Zhang;
    Publisher: Routledge
    Country: Denmark

    This chapter argues that China has been triple hit by the COVID-19 pandemic as it has caused a major trade shock, an investment shock and a business environment shock. To date, the globalized economies are interconnected by international trade, which makes trade an important vehicle for international contagion. Globalization and economic shocks are underpinned by a variety of forces affecting economic and societal changes creating a domino effect in global production networks. The impact of the COVID-19 pandemic on China’s overseas investment is manifold. Chinese businesses are exposed to the changing international business environment as perceptions on China’s roles are shifting. The COVID-19 pandemic is changing the way business is conducted worldwide. As a result, Chinese companies are now confronted with a new international business environment that is moving away from globalization that had been creating opportunities for firms from emerging economies to grow their presence in global markets.

  • Closed Access English
    Authors: 
    Irena Koprinska; Michael Kamp; Annalisa Appice; Corrado Loglisci; Luiza Antonie; Albrecht Zimmermann; Riccardo Guidotti; Özlem Özgöbek; Rita P. Ribeiro; Ricard Gavaldà; +20 more
    Publisher: HAL CCSD
    Countries: France, Denmark

    This volume constitutes the refereed proceedings of the workshops which complemented the 20th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2020. Due to the COVID-19 pandemic the conference and workshops were held online. The 43 papers presented in volume were carefully reviewed and selected from numerous submissions. The volume presents the papers that have been accepted for the following workshops: 5th Workshop on Data Science for Social Good, SoGood 2020; Workshop on Parallel, Distributed and Federated Learning, PDFL 2020; Second Workshop on Machine Learning for Cybersecurity, MLCS 2020, 9th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2020, Workshop on Data Integration and Applications, DINA 2020, Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning, EDML 2020, Second International Workshop on eXplainable Knowledge Discovery in Data Mining, XKDD 2020; 8th International Workshop on News Recommendation and Analytics, INRA 2020.

  • Closed Access English
    Authors: 
    Signe Skovgaard Hviid; Veronica Pisinger; Sofie Have Hoffman; Johanne Aviaja Rosing; Janne Shurmann Tolstrup;
    Country: Denmark

    Objective: As alcohol is often consumed for social purposes, we aimed to explore how restrictions during the first Danish COVID-19 lockdown affected the alcohol use among adolescents aged 15–20. Method: In May 2020, 11,596 15- to 20-year-olds from two subpopulations answered a survey regarding their alcohol use and social life, as well as changes to these, during the Danish lockdown. Using survey data from all participants, we performed a multinomial logistic regression to assess the association between determinants of alcohol use and perceived change in alcohol use during the Danish lockdown. We used longitudinal data from one subpopulation ( n=1869) to perform negative binomial regressions exploring changes in frequency of alcohol use from 2019 to 2020. Results: Of all participants, 59% drank less, 75% had fewer in-person social interactions and 56% met more frequently online during lockdown. Girls were more likely than boys to have a perceived decrease in alcohol use during lockdown (odds ratio (OR)=1.41; 95% confidence interval (CI) 1.27–1.56). A perceived decrease in in-person social interaction during lockdown was associated with less drinking (OR=2.27; 95% CI 1.98–2.61), while a perceived increase in in-person social interaction during lockdown was associated with more drinking (OR=1.42; 95% CI 1.11–1.82) compared to unchanged drinking behaviour and social interaction. Conclusions: Adolescents in Denmark drank less during the Danish lockdown than before. Findings indicate that there is a close relationship between in-person social interactions and frequency of drinking. Drinking episodes when meeting online were rare and were not unambiguously associated with changes in drinking during lockdown.

  • Closed Access English
    Authors: 
    Skaarup, Kristoffer Grundtvig; Lassen, Mats Christian Højbjerg; Lind, Jannie Nørgaard; Alhakak, Alia Saed; Sengeløv, Morten; Nielsen, Anne Bjerg; Espersen, Caroline; Hauser, Raphael; Schöps, Liv Borum; Holt, Eva; +32 more
    Country: Denmark
  • Closed Access English
    Authors: 
    Amin Naemi; Mostafa Naemi; Romina Zarrabi Ekbatani; Thomas Schmidt; Ali Ebrahimi; Marjan Mansourvar; Uffe Kock Wiil;
    Publisher: Springer
    Country: Denmark

    This paper analyzes single and two-wave COVID-19 outbreaks using two novel hybrid models, which combine machine learning and statistical methods with Richards growth models, to simulate and forecast the spread of the infection. For this purpose, historical cumulative numbers of confirmed cases for three countries, including Iran, Italy, and Mexico, are used. The analysis of the Richards models shows that its single-stage form can model the cumulative number of infections in countries with a single wave of outbreak (Italy and Mexico) accurately while its performance deteriorates for countries with two-wave outbreaks (Iran), which clarifies the requirement of multi-stage Richards models. The results of multi-stage Richards models reveal that the prevention of the second wave could reduce the outbreak size in Iran by approximately 400,000 cases, and the pandemic could be controlled almost 7 months earlier. Although the cumulative size of outbreak is estimated accurately using multi-stage Richards models, the results show that these models cannot forecast the daily number of cases, which are important for health systems’ planning. Therefore, two novel hybrid models, including autoregressive integrated moving average (ARIMA)-Richards and nonlinear autoregressive neural network (NAR)-Richards, are proposed. The accuracy of these models in forecasting the number of daily cases for 14 days ahead is calculated using the test data set shows that forecast error ranges from 8 to 25%. A comparison between these hybrid models also shows that the machine learning-based models have superior performance compared with statistical-based ones and on average are 20% more accurate.