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The coronavirus disease of 2019 (COVID-19) pandemic has forced most academics to work from home. This sudden venue change can affect academics' productivity and exacerbate the challenges that confront universities as they face an uncertain future. In this paper, we identify factors that influence academics' productivity while working from home during the mandate to self-isolate. From analyzing results from a global survey we conducted, we found that both personal and technology-related factors affect an individual's attitude toward working from home and productivity. Our results should prove valuable to university administrators to better address the work-life challenges that academics face.
The hospitality industry worldwide is among the hardest-hit industries from the COVID-19 lockdowns. Initial theoretical and practical observations in the hospitality industry indicate that business model innovation (BMI) might be a solution to recover from and successfully cope with the COVID-19 crisis. Interestingly, some firms in the hospitality industry already started to successfully adapt their business models. This study explores the why and how of these successful recovery attempts through BMI by conducting a multiple case study of six hospitality firms in Austria. We rely on interview data from managers together with one of their main stammgasts for each case, which we triangulate with secondary data for the analysis. Findings show that BMI is applied during and after the crisis to create new revenue streams and secure a higher level of liquidity, with an important role of stammgasts.
Background:
Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associatedwith worse outcomes. However, AKI among hospitalized patients with COVID19 in the United States is not well described.
Methods:
This retrospective, observational study involved a review of data from electronic health records of patients aged >= 18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality.
Results:
Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patientswith AKI required dialysis. The proportionswith stages 1, 2, or 3 AKIwere 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up.
Conclusions:
AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics
(2021)
Newly emerging pandemics like COVID-19 call for predictive models to implement precisely tuned responses to limit their deep impact on society. Standard epidemic models provide a theoretically well-founded dynamical description of disease incidence. For COVID-19 with infectiousness peaking before and at symptom onset, the SEIR model explains the hidden build-up of exposed individuals which creates challenges for containment strategies. However, spatial heterogeneity raises questions about the adequacy of modeling epidemic outbreaks on the level of a whole country. Here, we show that by applying sequential data assimilation to the stochastic SEIR epidemic model, we can capture the dynamic behavior of outbreaks on a regional level. Regional modeling, with relatively low numbers of infected and demographic noise, accounts for both spatial heterogeneity and stochasticity. Based on adapted models, short-term predictions can be achieved. Thus, with the help of these sequential data assimilation methods, more realistic epidemic models are within reach.
Reacting, fast and slow
(2021)
The COVID-19 pandemic created extraordinary challenges for governments to safeguard the well-being of their people. To what extent has leaders' reliance on scientific advice shaped government responses to the COVID-19 outbreak? We argue that leaders who tend to orient themselves on expert advice realized the extent of the crisis earlier. Consequently, these governments would adopt containment measures relatively quickly, despite the high uncertainty they faced. Over time, differences in government responses based on the use of science would dissipate due to herding effects. We test our argument on data combining 163 government responses to the pandemic with national- and individual-level characteristics. Consistent with our argument, we find that countries governed by politicians with a stronger technocratic mentality, approximated by holding a PhD, adopted restrictive containment measures faster in the early, but not in the later, stages of the crisis. This importance of expert-based leadership plausibly extends to other large-scale societal crises.
COVID-19
(2021)
We investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed — particularly women — in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are about one-third more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
Background:
Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial.
Objective:
This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others.
Methods:
A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables.
Results:
Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one's own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that "too much" concern leads to defensive reactions and reduces app uptake.
Conclusions:
As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.
Despite new challenges like climate change and digitalization, global and regional organizations recently went through turbulent times due to a lack of support from several of their member states. Next to this crisis of multilateralism, the COVID-19 pandemic now seems to question the added value of international organizations for addressing global governance issues more specifically. This article analyses this double challenge that several organizations are facing and compares their ways of managing the crisis by looking at their institutional and political context, their governance structure, and their behaviour during the pandemic until June 2020. More specifically, it will explain the different and fragmented responses of the World Health Organization, the European Union and the International Monetary Fund/World Bank. With the aim of understanding the old and new problems that these international organizations are trying to solve, this article argues that the level of autonomy vis-a-vis the member states is crucial for understanding the politics of crisis management. <br /> Points for practitioners <br /> As intergovernmental bodies, international organizations require authorization by their member states. Since they also need funding for their operations, different degrees of autonomy also matter for reacting to emerging challenges, such as the COVID-19 pandemic. The potential for international organizations is limited, though through proactive and bold initiatives, they can seize the opportunity of the crisis and partly overcome institutional and political constraints.
During COVID-19, various public institutions tried to shape citizens’ behaviour to slow the spread of the pandemic. How did their authority affect citizens’ support of public measures taken to combat the spread of COVID-19? The article makes two contributions. First, it presents a novel conceptualisation of authority as a source heuristic. Second, it analyses the authority of four types of public institutions (health ministries, universities, public health agencies, the WHO) in two countries (Germany and the UK), drawing on novel data from a survey experiment conducted in May 2020. On average, institutional endorsements seem to have mattered little. However, there is an observable polarisation effect where citizens who ascribe much expertise to public institutions support COVID-19 measures more than the control group. Furthermore, those who ascribe little expertise support them less than the control group. Finally, neither perception of biases nor exposure to institutions in public debates seems consistently to affect their authority.