The recent rise of populism has generated a resurgence of interest in critical theory, in the wider public debate and in academia—with critical theory being variously accused of paving the way for ...post-truth politics, hailed as explaining the rise of populism, or criticized for failing to achieve its emancipatory political goals. Failure of the latter kind, many International Relations scholars argue, calls for a fundamental reform of critical theory if it is to address current political developments. Investigating this claim, this article makes three contributions: First, an empirical account shows that, far from failing, critical theory has been politically highly successful. Second, a theoretical reconstruction of critical theory shows that it is precisely this success that leads to the alienation of critical theorists from their own approach. In light of this analysis, third, the article concludes that the task of critical theory in times of Brexit and Trump does not lie in abandoning its core principles but in systematically applying them to a new historical conjuncture.
Despite repeated announcements of the end of ideology and the demise of religion during the twentieth century, both play a crucial role in world politics today. This disjuncture between theoretical ...expectations and historical developments has its roots in conventional conceptions of ideology. While the latter grasp the representative nature of ideology as an expression of historical forces and political interests, they miss its constitutive role for modern politics. Based on an analysis of its historical origins and political implications, this article develops a new conception of ideology which accounts for the resilience and historical dynamics of ideological struggle. Like the sorcerer’s apprentice, I show, liberalism has called ideology into being but lost control of its own creation.
Coronavirus disease 2019 (COVID-19) is caused by the novel betacoronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Most people infected with SARS-CoV-2 have mild disease with ...unspecific symptoms, but about 5% become critically ill with respiratory failure, septic shock and multiple organ failure. An unknown proportion of infected individuals never experience COVID-19 symptoms although they are infectious, that is, they remain asymptomatic. Those who develop the disease, go through a presymptomatic period during which they are infectious. Universal screening for SARS-CoV-2 infections to detect individuals who are infected before they present clinically, could therefore be an important measure to contain the spread of the disease.
We conducted a rapid review to assess (1) the effectiveness of universal screening for SARS-CoV-2 infection compared with no screening and (2) the accuracy of universal screening in people who have not presented to clinical care for symptoms of COVID-19.
An information specialist searched Ovid MEDLINE and the Centers for Disease Control (CDC) COVID-19 Research Articles Downloadable Database up to 26 May 2020. We searched Embase.com, the CENTRAL, and the Cochrane Covid-19 Study Register on 14 April 2020. We searched LitCovid to 4 April 2020. The World Health Organization (WHO) provided records from daily searches in Chinese databases and in PubMed up to 15 April 2020. We also searched three model repositories (Covid-Analytics, Models of Infectious Disease Agent Study MIDAS, and Society for Medical Decision Making) on 8 April 2020.
Trials, observational studies, or mathematical modelling studies assessing screening effectiveness or screening accuracy among general populations in which the prevalence of SARS-CoV2 is unknown.
After pilot testing review forms, one review author screened titles and abstracts. Two review authors independently screened the full text of studies and resolved any disagreements by discussion with a third review author. Abstracts excluded by a first review author were dually reviewed by a second review author prior to exclusion. One review author independently extracted data, which was checked by a second review author for completeness and accuracy. Two review authors independently rated the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies and a modified form designed originally for economic evaluations for modelling studies. We resolved differences by consensus. We synthesized the evidence in narrative and tabular formats. We rated the certainty of evidence for days to outbreak, transmission, cases missed and detected, diagnostic accuracy (i.e. true positives, false positives, true negatives, false negatives) using the GRADE approach.
We included 22 publications. Two modelling studies reported on effectiveness of universal screening. Twenty studies (17 cohort studies and 3 modelling studies) reported on screening test accuracy. Effectiveness of screening We included two modelling studies. One study suggests that symptom screening at travel hubs, such as airports, may slightly slow but not stop the importation of infected cases (assuming 10 or 100 infected travellers per week reduced the delay in a local outbreak to 8 days or 1 day, respectively). We assessed risk of bias as minor or no concerns, and certainty of evidence was low, downgraded for very serious indirectness. The second modelling study provides very low-certainty evidence that screening of healthcare workers in emergency departments using laboratory tests may reduce transmission to patients and other healthcare workers (assuming a transmission constant of 1.2 new infections per 10,000 people, weekly screening reduced infections by 5.1% within 30 days). The certainty of evidence was very low, downgraded for high risk of bias (major concerns) and indirectness. No modelling studies reported on harms of screening. Screening test accuracy All 17 cohort studies compared an index screening strategy to a reference reverse transcriptase polymerase chain reaction (RT-PCR) test. All but one study reported on the accuracy of single point-in-time screening and varied widely in prevalence of SARS-CoV-2, settings, and methods of measurement. We assessed the overall risk of bias as unclear in 16 out of 17 studies, mainly due to limited information on the index test and reference standard. We rated one study as being at high risk of bias due to the inclusion of two separate populations with likely different prevalences. For several screening strategies, the estimates of sensitivity came from small samples. For single point-in-time strategies, for symptom assessment, the sensitivity from 12 cohorts (524 people) ranged from 0.00 to 0.60 (very low-certainty evidence) and the specificity from 12 cohorts (16,165 people) ranged from 0.66 to 1.00 (low-certainty evidence). For screening using direct temperature measurement (3 cohorts, 822 people), international travel history (2 cohorts, 13,080 people), or exposure to known infected people (3 cohorts, 13,205 people) or suspected infected people (2 cohorts, 954 people), sensitivity ranged from 0.00 to 0.23 (very low- to low-certainty evidence) and specificity ranged from 0.90 to 1.00 (low- to moderate-certainty evidence). For symptom assessment plus direct temperature measurement (2 cohorts, 779 people), sensitivity ranged from 0.12 to 0.69 (very low-certainty evidence) and specificity from 0.90 to 1.00 (low-certainty evidence). For rapid PCR test (1 cohort, 21 people), sensitivity was 0.80 (95% confidence interval (CI) 0.44 to 0.96; very low-certainty evidence) and specificity was 0.73 (95% CI 0.39 to 0.94; very low-certainty evidence). One cohort (76 people) reported on repeated screening with symptom assessment and demonstrates a sensitivity of 0.44 (95% CI 0.29 to 0.59; very low-certainty evidence) and specificity of 0.62 (95% CI 0.42 to 0.79; low-certainty evidence). Three modelling studies evaluated the accuracy of screening at airports. The main outcomes measured were cases missed or detected by entry or exit screening, or both, at airports. One study suggests very low sensitivity at 0.30 (95% CI 0.1 to 0.53), missing 70% of infected travellers. Another study described an unrealistic scenario to achieve a 90% detection rate, requiring 0% asymptomatic infections. The final study provides very uncertain evidence due to low methodological quality.
The evidence base for the effectiveness of screening comes from two mathematical modelling studies and is limited by their assumptions. Low-certainty evidence suggests that screening at travel hubs may slightly slow the importation of infected cases. This review highlights the uncertainty and variation in accuracy of screening strategies. A high proportion of infected individuals may be missed and go on to infect others, and some healthy individuals may be falsely identified as positive, requiring confirmatory testing and potentially leading to the unnecessary isolation of these individuals. Further studies need to evaluate the utility of rapid laboratory tests, combined screening, and repeated screening. More research is also needed on reference standards with greater accuracy than RT-PCR. Given the poor sensitivity of existing approaches, our findings point to the need for greater emphasis on other ways that may prevent transmission such as face coverings, physical distancing, quarantine, and adequate personal protective equipment for frontline workers.
For the evaluation of infectious-diseases interventions, the transmissible nature of such diseases plays a central role. Agent-based models (ABM) allow for dynamic transmission modeling but ...publications are limited. We aim to provide an overview of important characteristics of ABM for decision-analytic modeling of infectious diseases. A case study of dengue epidemics illustrates model characteristics, conceptualization, calibration and model analysis. First, major characteristics of ABM are outlined and discussed based on ISPOR and ISPOR-SMDM Good Practice guidelines. Second, in our case study, we modeled a dengue outbreak in Cebu City (Philippines) to assess the impact interventions to control the relative growth of the mosquito population. Model outcomes include prevalence and incidence of infected persons. The modular ABM simulates persons and mosquitoes over an annual time horizon considering daily time steps. The model was calibrated and validated. ABM is a dynamic, individual-level modeling approach that is capable to reproduce direct and indirect effects of interventions for infectious diseases. The ability to replicate emerging behavior and to include human behavior or the behavior of other agents is a distinguishing modeling characteristic (e.g., compared to Markov models). Modeling behavior may, however, require extensive calibration and validation. The analyzed hypothetical effectiveness of dengue interventions showed that a reduced human-mosquito ratio of 1:2.5 during rainy seasons leads already to a substantial decrease of infected persons. ABM can support decision-analyses for infectious diseases including disease dynamics, emerging behavior, and providing a high level of reusability due to modularity.
Abstract State-transition modeling is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling including both Markov model cohort simulation and individual-based ...(first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, state-transition modeling is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. State-transition models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. The goal of this article was to provide consensus-based guidelines for the application of state-transition models in the context of health care. We structured the best practice recommendations in the following sections: choice of model type (cohort vs. individual-level model), model structure, model parameters, analysis, reporting, and communication. In each of these sections, we give a brief description, address the issues that are of particular relevance to the application of state-transition models, give specific examples from the literature, and provide best practice recommendations for state-transition modeling. These recommendations are directed both to modelers and to users of modeling results such as clinicians, clinical guideline developers, manufacturers, or policymakers.
Liberal internationalism JAHN, BEATE
International affairs (London),
01/2018, Letnik:
94, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Liberal internationalism has been in crisis for a while now. Yet, until recently, its supporters have argued that its prospects are better than ever, as the successful spread of liberal principles, ...practices and institutions in the international sphere provides the necessary basis for reform. Alas, recent political developments do not support these expectations. In fact, the Brexit vote, the election of President Trump, and the rise of populism more generally challenge liberalism in the domestic sphere and aim to unravel its international achievements. But the idea that these movements are therefore liberalism’s nemeses does not quite follow. Providing a theoretical and historical analysis of liberalism, this article shows that the separation of domestic and international politics is constitutive of liberalism itself. The successful extension of liberal principles into the international sphere undermines this separation and thus liberalism itself. Ironically, therefore, the prospects of liberal internationalism are dependent on the reestablishment of a clear divide between domestic and international politics. And this, I argue, is precisely the goal of contemporary populist movements.
The distribution of the newly developed vaccines presents a great challenge in the ongoing SARS-CoV-2 pandemic. Policy makers must decide which subgroups should be vaccinated first to minimize the ...negative consequences of the pandemic. These decisions must be made upfront and under uncertainty regarding the amount of vaccine doses available at a given time. The objective of the present work was to develop an iterative optimization algorithm, which provides a prioritization order of predefined subgroups. The results of this algorithm should be optimal but also robust with respect to potentially limited vaccine supply.
We present an optimization meta-heuristic which can be used in a classic simulation-optimization setting with a simulation model in a feedback loop. The meta-heuristic can be applied in combination with any epidemiological simulation model capable of depicting the effects of vaccine distribution to the modeled population, accepts a vaccine prioritization plan in a certain notation as input, and generates decision making relevant variables such as COVID-19 caused deaths or hospitalizations as output. We finally demonstrate the mechanics of the algorithm presenting the results of a case study performed with an epidemiological agent-based model.
We show that the developed method generates a highly robust vaccination prioritization plan which is proven to fulfill an elegant supremacy criterion: the plan is equally optimal for any quantity of vaccine doses available. The algorithm was tested on a case study in the Austrian context and it generated a vaccination plan prioritization favoring individuals age 65+, followed by vulnerable groups, to minimize COVID-19 related burden.
The results of the case study coincide with the international policy recommendations which strengthen the applicability of the approach. We conclude that the path-dependent optimum optimum provided by the algorithm is well suited for real world applications, in which decision makers need to develop strategies upfront under high levels of uncertainty.
Two broad positions—the "gap-bridgers" and the "gap-minders"—dominate the current debate on the (lack of) political relevance of International Relations (IR) theory. Missing from this debate, ...however, is a broader theoretical framework for contextualizing—and moving beyond—their disagreements. Hence, this article provides a theoretical account of the relationship between politics and knowledge. It shows that, in the modern context, scientific knowledge achieves political relevance by distancing itself—through theorizing—from the particularities of politics. This paradoxical relationship gives rise to three different dimensions of political relevance, which operate at different levels of abstraction. Metatheory plays a crucial role in constituting the modern conception of politics; theories establish concrete political spaces; and empirical studies can influence specific policies. Taking this context into account, moreover, calls for a reassessment of core features of the discipline: its supposed poverty, fragmentation, and immaturity are common features of all modern sciences; they function as a driver of scientific progress; and metatheoretical debates address the political dimension of the modern sciences. Hence, the source of IR's political relevance lies in its theoretical foundations. Abandoning theory in favor of policyoriented studies would simultaneously undermine the discipline's policy relevance and its standing as a modern science.
Objectives
Benefit and cost effectiveness of breast cancer screening are still matters of controversy. Risk-adapted strategies are proposed to improve its benefit-harm and cost–benefit relations. Our ...objective was to perform a systematic review on economic breast cancer models evaluating primary and secondary prevention strategies in the European health care setting, with specific focus on model results, model characteristics, and risk-adapted strategies.
Methods
Literature databases were systematically searched for economic breast cancer models evaluating the cost effectiveness of breast cancer screening and prevention strategies in the European health care context. Characteristics, methodological details and results of the identified studies are reported in evidence tables. Economic model outputs are standardized to achieve comparable cost-effectiveness ratios.
Results
Thirty-two economic evaluations of breast cancer screening and seven evaluations of primary breast cancer prevention were included. Five screening studies and none of the prevention studies considered risk-adapted strategies. Studies differed in methodologic features. Only about half of the screening studies modeled overdiagnosis-related harms, most often indirectly and without reporting their magnitude. All models predict gains in life expectancy and/or quality-adjusted life expectancy at acceptable costs. However, risk-adapted screening was shown to be more effective and efficient than conventional screening.
Conclusions
Economic models suggest that breast cancer screening and prevention are cost effective in the European setting. All screening models predict gains in life expectancy, which has not yet been confirmed by trials. European models evaluating risk-adapted screening strategies are rare, but suggest that risk-adapted screening is more effective and efficient than conventional screening.
Chronic obstructive pulmonary disease (COPD) causes significant morbidity and mortality worldwide. Estimation of incidence, prevalence and disease burden through routine insurance data is challenging ...because of under-diagnosis and under-treatment, particularly for early stage disease in health care systems where outpatient International Classification of Diseases (ICD) diagnoses are not collected. This poses the question of which criteria are commonly applied to identify COPD patients in claims datasets in the absence of ICD diagnoses, and which information can be used as a substitute. The aim of this systematic review is to summarize previously reported methodological approaches for the identification of COPD patients through routine data and to compile potential criteria for the identification of COPD patients if ICD codes are not available.
A systematic literature review was performed in Medline via PubMed and Google Scholar from January 2000 through October 2018, followed by a manual review of the included studies by at least two independent raters. Study characteristics and all identifying criteria used in the studies were systematically extracted from the publications, categorized, and compiled in evidence tables.
In total, the systematic search yielded 151 publications. After title and abstract screening, 38 publications were included into the systematic assessment. In these studies, the most frequently used (22/38) criteria set to identify COPD patients included ICD codes, hospitalization, and ambulatory visits. Only four out of 38 studies used methods other than ICD coding. In a significant proportion of studies, the age range of the target population (33/38) and hospitalization (30/38) were provided. Ambulatory data were included in 24, physician claims in 22, and pharmaceutical data in 18 studies. Only five studies used spirometry, two used surgery and one used oxygen therapy.
A variety of different criteria is used for the identification of COPD from routine data. The most promising criteria set in data environments where ambulatory diagnosis codes are lacking is the consideration of additional illness-related information with special attention to pharmacotherapy data. Further health services research should focus on the application of more systematic internal and/or external validation approaches.
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