@article{MunschGruarinNateqietal.,
  author    = {Munsch, Nicolas and Gruarin, Stefanie and Nateqi, Jama and Lutz, Thomas and Binder, Michael and Aberle, Judith H. and Martin, Alistair and Knapp, Bernhard},
  title     = {Symptoms associated with a COVID-19 infection among a non-hospitalized cohort in Vienna},
  series = {Wiener Klinische Wochenschrift / The Central European Journal of Medicine},
  volume    = {2022},
  journal   = {Wiener Klinische Wochenschrift / The Central European Journal of Medicine},
  number    = {134 (9-10)},
  publisher = {Springer},
  pages     = {344 -- 350},
  abstract  = {Background: Most clinical studies report the symptoms experienced by those infected with coronavirus disease 2019 (COVID-19) via patients already hospitalized. Here we analyzed the symptoms experienced outside of a hospital setting. Methods: The Vienna Social Fund (FSW; Vienna, Austria), the Public Health Services of the City of Vienna (MA15) and the private company Symptoma collaborated to implement Vienna's official online COVID-19 symptom checker. Users answered 12 yes/no questions about symptoms to assess their risk for COVID-19. They could also specify their age and sex, and whether they had contact with someone who tested positive for COVID-19. Depending on the assessed risk of COVID-19 positivity, a SARS-CoV‑2 nucleic acid amplification test (NAAT) was performed. In this publication, we analyzed which factors (symptoms, sex or age) are associated with COVID-19 positivity. We also trained a classifier to correctly predict COVID-19 positivity from the collected data. Results: Between 2 November 2020 and 18 November 2021, 9133 people experiencing COVID-19-like symptoms were assessed as high risk by the chatbot and were subsequently tested by a NAAT. Symptoms significantly associated with a positive COVID-19 test were malaise, fatigue, headache, cough, fever, dysgeusia and hyposmia. Our classifier could successfully predict COVID-19 positivity with an area under the curve (AUC) of 0.74. Conclusion: This study provides reliable COVID-19 symptom statistics based on the general population verified by NAATs. Keywords: Chatbot; Machine learning; Self-reported; Symptom assessment; Symptom checker.},
  subject      = {COVID-19},
  language  = {en}
}
@article{SimboeckMarksteinerMachaceketal.,
  author    = {Simb{\"o}ck, Elisabeth and Marksteiner, Jessica and Machacek, Thomas and Wiessner, Katharina and Gepp, Barbara and Jesenberger, Veronika and Weihs, Anna and Leitner, Rita},
  title     = {The Power of Problem Based Learning beyond its Didactic Attributes},
  series = {Journal of Problem Based Learning in Higher Education (JPBLHE)},
  volume    = {9},
  journal   = {Journal of Problem Based Learning in Higher Education (JPBLHE)},
  number    = {1},
  pages     = {109 -- 130},
  abstract  = {Hybrid courses with a focus on practice-orientated education and self-guided learning phases are on the rise on the higher education sector. Disciplines in Life Sciences implicate a high degree of practical laboratory expertise. The University of Applied Sciences (UAS) in Vienna, Austria, has thus been endeavoured offering students a high qualitative education integrating hybrid courses based on PBL principles, which consist of on-site (including the transmission of necessary background and practical laboratory training) and off-site (including self-study phases) sessions. As practical laboratory units are central in those courses, the restrictive measures, including the transition to a complete online teaching format due to the first Covid-19-pandemic lock-down, had severe effects on the implementation and the quality of the curriculum. According to surveys made specifically to address this problematic situation, it can be concluded that on-site practical units are fundamental for certain disciplines such as Life Sciences.},
  subject      = {Problem-based Learning},
  language  = {en}
}
@article{MunschMartinGruarinetal.,
  author    = {Munsch, Nicolas and Martin, Alistair and Gruarin, Stefanie and Nateqi, Jama and Abdarahmane, Isselmou and Weingartner-Ortner, Rafael and Knapp, Bernhard},
  title     = {Authors' Reply to: Screening Tools: Their Intended Audiences and Purposes. Comment on "Diagnostic Accuracy of Web-Based COVID-19 Symptom Checkers: Comparison Study"},
  series = {Journal of Medical Internet Research},
  journal   = {Journal of Medical Internet Research},
  number    = {Vol 23, No 5 (2021)},
  subject      = {COVID-19},
  language  = {en}
}