scholarly journals Impact of Modelling Approach on the Estimation of Government Intervention Effects in COVID-19

2021 ◽  
Author(s):  
Lun Liu ◽  
Zhu Zhang ◽  
Hui Wang ◽  
Shenhao Wang ◽  
Shengsheng Zhuang
Keyword(s):  
Behavioral Changes ◽  
Future Research ◽  
Difference In Difference ◽  
Intervention Effects ◽  
Data Set ◽  
Government Interventions ◽  
Bayesian Hierarchical ◽  
Epidemic Response ◽  
Modelling Approach ◽  
Modelling Approaches

Abstract The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, which is partly related to the varying modelling approaches employed by existing studies. This paper therefore aims to examine how the choice of modelling approach would affect the estimation results of intervention effects, by experimenting with different modelling approaches on a same data set composed of the 500 most affected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods are likely to produce larger estimates of intervention effects due to simultaneous voluntary behavioral changes. In contrast, natural experimental methods are more likely to extract the true effect of interventions. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.

scholarly journals The COVID Connection: Pandemic Anxiety, COVID-19 Comprehension, and Digital Confidence

2021 ◽  
pp. 000276422110031
Author(s):  
Laura Robinson ◽  
Jeremy Schulz ◽  
Øyvind N. Wiborg ◽  
Elisha Johnston
Keyword(s):  
Logistic Models ◽  
The United States ◽  
Sociodemographic Factors ◽  
Future Research ◽  
Lower Probability ◽  
Data Set ◽  
Digital Inequality ◽  
Partner Status ◽  
General Anxiety ◽  
Nationally Representative

This article presents logistic models examining how pandemic anxiety and COVID-19 comprehension vary with digital confidence among adults in the United States during the first wave of the pandemic. As we demonstrate statistically with a nationally representative data set, the digitally confident have lower probability of experiencing physical manifestations of pandemic anxiety and higher probability of adequately comprehending critical information on COVID-19. The effects of digital confidence on both pandemic anxiety and COVID-19 comprehension persist, even after a broad range of potentially confounding factors are taken into account, including sociodemographic factors such as age, gender, race/ethnicity, metropolitan status, and partner status. They also remain discernable after the introduction of general anxiety, as well as income and education. These results offer evidence that the digitally disadvantaged experience greater vulnerability to the secondary effects of the pandemic in the form of increased somatized stress and decreased COVID-19 comprehension. Going forward, future research and policy must make an effort to address digital confidence and digital inequality writ large as crucial factors mediating individuals’ responses to the pandemic and future crises.

scholarly journals A data acquisition setup for data driven acoustic design

2021 ◽  
pp. 1351010X2098690
Author(s):  
Romana Rust ◽  
Achilleas Xydis ◽  
Kurt Heutschi ◽  
Nathanael Perraudin ◽  
Gonzalo Casas ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Interdisciplinary Approach ◽  
Computational Design ◽  
Surface Structures ◽  
Future Research ◽  
Data Set ◽  
Process Measures ◽  
First Results ◽  
Spatio Temporal ◽  
Automated Data Acquisition

In this paper, we present a novel interdisciplinary approach to study the relationship between diffusive surface structures and their acoustic performance. Using computational design, surface structures are iteratively generated and 3D printed at 1:10 model scale. They originate from different fabrication typologies and are designed to have acoustic diffusion and absorption effects. An automated robotic process measures the impulse responses of these surfaces by positioning a microphone and a speaker at multiple locations. The collected data serves two purposes: first, as an exploratory catalogue of different spatio-temporal-acoustic scenarios and second, as data set for predicting the acoustic response of digitally designed surface geometries using machine learning. In this paper, we present the automated data acquisition setup, the data processing and the computational generation of diffusive surface structures. We describe first results of comparative studies of measured surface panels and conclude with steps of future research.

A point-based Bayesian hierarchical model to predict the outcome of tennis matches

2019 ◽  
Vol 15 (4) ◽  
pp. 313-325 ◽  
Author(s):  
Martin Ingram
Keyword(s):  
Random Walk ◽  
Hierarchical Model ◽  
Bayesian Hierarchical Model ◽  
Bayesian Hierarchical ◽  
Gaussian Random Walk ◽  
Over Time ◽  
Modelling Approach ◽  
Independent And Identically Distributed

Abstract A well-established assumption in tennis is that point outcomes on each player’s serve in a match are independent and identically distributed (iid). With this assumption, it is enough to specify the serve probabilities for both players to derive a wide variety of event distributions, such as the expected winner and number of sets, and number of games. However, models using this assumption, which we will refer to as “point-based”, have typically performed worse than other models in the literature at predicting the match winner. This paper presents a point-based Bayesian hierarchical model for predicting the outcome of tennis matches. The model predicts the probability of winning a point on serve given surface, tournament and match date. Each player is given a serve and return skill which is assumed to follow a Gaussian random walk over time. In addition, each player’s skill varies by surface, and tournaments are given tournament-specific intercepts. When evaluated on the ATP’s 2014 season, the model outperforms other point-based models, predicting match outcomes with greater accuracy (68.8% vs. 66.3%) and lower log loss (0.592 vs. 0.641). The results are competitive with approaches modelling the match outcome directly, demonstrating the forecasting potential of the point-based modelling approach.

scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

In the Face of Critique

2011 ◽  
Vol 34 (2) ◽  
pp. 241-282 ◽  
Author(s):  
Elyse Amend ◽  
David M. Secko
Keyword(s):  
The State ◽  
Future Research ◽  
Jigsaw Puzzle ◽  
Science Journalism ◽  
Data Set ◽  
Literature Searches ◽  
The Face ◽  
Qualitative Knowledge ◽  
Qualitative Literature

The qualitative literature related to health and science journalism often states that little is known about the perspectives of journalists. This is, in part, because of individual studies being like scattered pieces of a jigsaw puzzle. In this article, the authors report the results of a qualitative metasynthesis aimed at reassembling the qualitative literature involving health and science journalists. Comprehensive literature searches gave a data set of 21 studies whose synthesis produced 14 metathemes and four taxonomic groupings. This synthesis is used to show the state of qualitative knowledge and the potential for future research.

Competition and Contestability in the UK Package Tour Industry: Some Econometric Observations

1998 ◽  
Vol 4 (3) ◽  
pp. 241-251 ◽  
Author(s):  
Brian Davies ◽  
Paul Downward
Keyword(s):  
Panel Data ◽  
Market Power ◽  
Power Efficiency ◽  
Econometric Analysis ◽  
Future Research ◽  
Research Needs ◽  
Data Set ◽  
The Uk ◽  
Efficiency Hypothesis

This paper explores competition and contestability in the UK package tour industry. Using econometric analysis of a panel-data set evidence is presented that rules out the market power/efficiency hypothesis. In keeping with Evans and Stabler (1995), there is evidence that the industry is segmented according to the size of the firms. In contrast with Gratton and Richards (1997), the results suggest that it is difficult to support the contestability hypothesis in the industry overall. Future research needs to offer less generalized conclusions in characterizing the industry.

A Theory of Sex Differences in Technical Aptitude and Some Supporting Evidence

2011 ◽  
Vol 6 (6) ◽  
pp. 560-573 ◽  
Author(s):  
Frank L. Schmidt
Keyword(s):  
Sex Differences ◽  
Job Performance ◽  
Large Data ◽  
Future Research ◽  
Mental Ability ◽  
Supporting Evidence ◽  
Data Set ◽  
Aptitude Tests ◽  
General Mental Ability ◽  
Technical Aptitude

In this article, I present a theory that explains the origin of sex differences in technical aptitudes. The theory takes as proven that there are no sex differences in general mental ability (GMA), and it postulates that sex differences in technical aptitude (TA) stem from differences in experience in technical areas, which is in turn based on sex differences in technical interests. Using a large data set, I tested and found support for four predictions made by this theory: (a) the construct level correlation between technical aptitude and GMA is larger for females than males, (b) the observed and true score variability of technical aptitude is greater among males than females, (c) at every level of GMA females have lower levels of technical aptitude, and (d) technical aptitude measures used as estimates of GMA for decision purposes would result in underestimation of GMA levels for girls and women. Given that GMA carries the weight of prediction of job performance, the support found for this last prediction suggests that, for many jobs, technical aptitude tests may underpredict the job performance of female applicants and employees. Future research should examine this question.

Aircraft Propulsion System Accident Causal Analysis

2000 ◽  
Author(s):  
Todd D. Jack ◽  
Carl N. Ford ◽  
Shari-Beth Nadell ◽  
Vicki Crisp
Keyword(s):  
Time Frame ◽  
Causal Analysis ◽  
Propulsion System ◽  
Mitigation Strategies ◽  
Transportation Safety ◽  
Future Research ◽  
Data Set ◽  
Depth Analysis ◽  
Aircraft Propulsion System ◽  
Engine Type

A causal analysis of aviation accidents by engine type is presented. The analysis employs a top-down methodology that performs a detailed analysis of the causes and factors cited in accident reports to develop a “fingerprint” profile for each engine type. This is followed by an in-depth analysis of each fingerprint that produces a sequential breakdown. Analysis results of National Transportation Safety Board (NTSB) accidents, both fatal and non-fatal, that occurred during the time period of 1990–1998 are presented. Each data set is comprised of all accidents that involved aircraft with the following engine types: turbofan, turbojet, turboprop, and turboshaft (includes turbine helicopters). During this time frame there were 1461 accidents involving turbine powered aircraft; 306 of these involved propulsion malfunctions and/ or failures. Analyses are performed to investigate the sequential relationships between propulsion system malfunctions or failures with other causes and factors for each engine type. Other malfunctions or events prominent within each data set are also analyzed. Significant trends are identified. The results from this study can be used to identify areas for future research into intervention, prevention, and mitigation strategies.

Assessing the Psychosocial Elements of Crowds at Mass Gatherings

2011 ◽  
Vol 26 (6) ◽  
pp. 414-421 ◽  
Author(s):  
Alison Hutton ◽  
Kathryn Zeitz ◽  
Steve Brown ◽  
Paul Arbon
Keyword(s):  
Health And Safety ◽  
Pilot Project ◽  
Assessment Tools ◽  
Future Research ◽  
Mass Gathering ◽  
Crowd Behavior ◽  
Descriptive Data ◽  
Data Set ◽  
Mass Gatherings ◽  
Psychosocial Domain

AbstractIntroduction: The environmental aspects of mass gatherings that can affect the health and safety of the crowd have been well described. Although it has been recognized that the nature of the crowd will directly impact the health and safety of the crowd, the majority of research focuses on crowd behavior in a negative context such as violence or conflict. Within the mass gathering literature, there is no agreement on what crowd behavior, crowd mood and crowd type actually mean. At the same time, these elements have a number of applications, including event management and mass gathering medicine. These questions are worthy of exploration.Methods: This paper will report on a pilot project undertaken to evaluate how effective current crowd assessment tools are in understanding the psychosocial domain of a mass gathering event.Results: The pilot project highlighted the need for a more consistent descriptive data set that focuses on crowd behavior.Conclusions: The descriptive data collected in this study provide a beginning insight into the science of understanding crowds at a mass gathering event. This pilot has commenced a process of quantifying the psychosocial nature of an event. To maximize the value of this work, future research is required to understand the interplay among the three domains of mass gatherings (physical, environmental and psychological), along with the effects of each element within the domains on safety and health outcomes for participants at mass gatherings.

scholarly journals A review of biomass burning emissions, part II: Intensive physical properties of biomass burning particles

2004 ◽  
Vol 4 (5) ◽  
pp. 5135-5200 ◽  
Author(s):  
J. S. Reid ◽  
R. Koppmann ◽  
T. F. Eck ◽  
D. P. Eleuterio
Keyword(s):  
Particle Size ◽  
Biomass Burning ◽  
Measurement Techniques ◽  
Emission Factors ◽  
Future Research ◽  
Data Set ◽  
Particle Properties ◽  
In Situ Experiments ◽  
Literature Base ◽  
Biomass Burning Particles

Abstract. The last decade has seen tremendous advances in atmospheric aerosol particle research that is often performed in the context of climate and global change science. Biomass burning, one of the largest sources of accumulation mode particles globally, has been closely studied for its radiative, geochemical, and dynamic impacts. These studies have taken many forms including laboratory burns, in situ experiments, remote sensing, and modeling. While the differing perspectives of these studies have ultimately improved our qualitative understanding of biomass burning issues, the varied nature of the work make inter-comparisons and resolutions of some specific issues difficult. In short, the literature base has become a milieu of small pieces of the biomass-burning puzzle. This manuscript, the second part of four, examines the properties of biomass-burning particle emissions. Here we review and discuss the literature concerning the measurement of smoke particle size, chemistry, thermodynamic properties, and emission factors. Where appropriate, critiques of measurement techniques are presented. We show that very large differences in measured particle properties have appeared in the literature, in particular with regards to particle carbon budgets. We investigate emissions uncertainties using scale analyses, which shows that while emission factors for grass and brush are relatively well known, very large uncertainties still exist in emission factors of boreal, temperate and some tropical forests. Based on an uncertainty analysis of the community data set of biomass burning measurements, we present simplified models for particle size and emission factors. We close this review paper with a discussion of the community experimental data, point to lapses in the data set, and prioritize future research topics.

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