scholarly journals Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions

2021 ◽  
Vol 118 (25) ◽  
pp. e2019284118
Author(s):  
Thomas P. Smith ◽  
Seth Flaxman ◽  
Amanda S. Gallinat ◽  
Sylvia P. Kinosian ◽  
Michael Stemkovski ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Population Density ◽  
Transmission Rate ◽  
The United States ◽  
Transmission Intensity ◽  
Epidemiological Modeling ◽  
Policy Interventions ◽  
Using Data ◽  
Nonpharmaceutical Interventions ◽  
The Impact

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention (“lockdown”) and reductions in individuals’ mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.

scholarly journals Environment influences SARS-CoV-2 transmission in the absence of non-pharmaceutical interventions

2020 ◽  
Author(s):  
Thomas P Smith ◽  
Seth Flaxman ◽  
Amanda S Gallinat ◽  
Sylvia P Kinosian ◽  
Michael Stemkovski ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Transmission Rate ◽  
The United States ◽  
Transmission Intensity ◽  
Policy Intervention ◽  
Policy Interventions ◽  
Winter Temperatures ◽  
Using Data ◽  
Autumn And Winter ◽  
The Impact

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on SARS-CoV-2 remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, UV radiation, and population density with estimates of transmission rate (R). Using data from the United States of America, we explore correlates of transmission across USA states using comparative regression and integrative epidemiological modelling. We find that policy intervention (`lockdown') and reductions in individuals' mobility are the major predictors of SARS-CoV-2 transmission rates, but in their absence lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioural changes. We outline how this information may improve the forecasting of SARS-CoV-2, its future seasonal dynamics, and inform intervention policies.

Cyber Place Management and Crime Prevention: The Effectiveness of Cybersecurity Awareness Training Against Phishing Attacks

2021 ◽  
pp. 104398622110016
Author(s):  
Sinchul Back ◽  
Rob T. Guerette
Keyword(s):  
Crime Prevention ◽  
Research University ◽  
Management Strategies ◽  
Large Body ◽  
The United States ◽  
Place Management ◽  
Online Setting ◽  
Using Data ◽  
Virtual Domain ◽  
The Impact

Criminologists and crime prevention practitioners recognize the importance of geographical places to crime activities and the role that place managers might play in effectively preventing crime. Indeed, over the past several decades, a large body of work has highlighted the tendency for crime to concentrate across an assortment of geographic areas, where place management tends to be absent or weak. Nevertheless, there has been a paucity of research evaluating place management strategies and cybercrime within the virtual domain. The purpose of this study was to investigate the effectiveness of place management techniques on reducing cybercrime incidents in an online setting. Using data derived from the information technology division of a large urban research university in the United States, this study evaluated the impact of an anti-phishing training program delivered to employees that sought to increase awareness and understanding of methods to better protect their “virtual places” from cybercrimes. Findings are discussed within the context of the broader crime and place literature.

Overeducation and the Earnings of Black, Hispanic, and White Male Workers

1988 ◽  
Vol 31 (2) ◽  
pp. 190-212 ◽  
Author(s):  
Richard R. Verdugo ◽  
Naomi Turner Verdugo
Keyword(s):  
United States ◽  
Mexican Americans ◽  
Minority Groups ◽  
Puerto Ricans ◽  
White Male ◽  
The United States ◽  
Using Data ◽  
The Impact ◽  
Male Workers ◽  
White Minority

This study addresses two issues: (1) the impact of overeducation on the earnings of male workers in the United States, and (2) white-minority earnings differences among males. Given that educational attainment levels are increasing among workers, there is some suspicion that earnings returns to education are not as great as might be expected. This topic is examined by including an overeducation variable in an earnings function. Regarding the second issue addressed in this article, little is actually known about white-minority differences because the bulk of such research compares whites and blacks. By including selected Hispanic groups in this analysis (Mexican Americans, Puerto Ricans, Cubans, and Other Hispanics) we are able to assess white-minority earnings differences to a greater degree. Using data from a 5% sample of the 1980 census to estimate an earnings function, we find that overeducated workers earn less than either undereducated or adequately educated workers. Second, we find that there are substantial earnings differences between whites and minorities, and, also, between the five minority groups examined.

Impact of Health Plan Deductibles and Health Insurance Marketplace Enrollment on Health Care Experiences

2018 ◽  
Vol 77 (5) ◽  
pp. 483-497
Author(s):  
Weiwei Chen ◽  
Timothy F. Page
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
The United States ◽  
Health Plans ◽  
Medical Needs ◽  
Care Access ◽  
Health Care Experiences ◽  
Monitoring Survey ◽  
Using Data ◽  
The Impact

High-deductible health plans (HDHPs) have become increasingly prevalent among employer-sponsored health plans and plans offered through the Health Insurance Marketplace in the United States. This study examined the impact of deductible levels on health care experiences in terms of care access, affordability, routine checkup, out-of-pocket cost, and satisfaction using data from the Health Reform Monitoring Survey. The study also tested whether the experiences of Marketplace enrollees differed from off-Marketplace individuals, controlling for deductible levels. Results from multivariable and propensity score weighted regression models showed that many of the outcomes were adversely affected by deductible levels and Marketplace enrollment. These results highlight the importance of efforts to help individuals choose the plan that fits both their medical needs and their budgets. The study also calls for more attention to improving provider acceptance of HDHPs and Marketplace plans as these plans become increasingly common over time.

scholarly journals Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

2020 ◽  
Author(s):  
Niayesh Afshordi ◽  
Benjamin Holder ◽  
Mohammad Bahrami ◽  
Daniel Lichtblau
Keyword(s):  
United States ◽  
Population Density ◽  
The United States ◽  
Effective Response ◽  
Susceptible Population ◽  
Local Climate ◽  
Climate Conditions ◽  
Mortality And Morbidity ◽  
Social Distancing ◽  
The Impact

The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., “herd immunity”), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.

scholarly journals Modeling a Bridge When Survey Questions Change: Evidence from the Current Population Survey Health Insurance Redesign

2019 ◽  
Vol 35 (1) ◽  
pp. 189-202
Author(s):  
Brett O’Hara ◽  
Carla Medalia ◽  
Jerry J. Maples
Keyword(s):  
Health Insurance ◽  
Current Population Survey ◽  
Time Trend ◽  
Population Survey ◽  
The United States ◽  
Community Survey ◽  
Historical Time ◽  
Current Population ◽  
Using Data ◽  
The Impact

Abstract Most research on health insurance in the United States uses the Current Population Survey Annual Social and Economic Supplement. However, a recent redesign of the health insurance questions disrupted the historical time trend in 2013. Using data from the American Community Survey, which has a parallel trend in the uninsured rate, we model a bridge estimate of the uninsured rate using the traditional questions. Also, we estimate the effect of changing the questionnaire. We show that the impact of redesigning the survey varies substantially by subgroup. This approach can be used to produce bridge estimates when other questionnaires are redesigned.

Quantifying changes in bicycle volumes using crowdsourced data

2022 ◽  
pp. 239980832110661
Author(s):  
Ali Al-Ramini ◽  
Mohammad A Takallou ◽  
Daniel P Piatkowski ◽  
Fadi Alsaleem
Keyword(s):  
Machine Learning ◽  
The United States ◽  
Crowdsourced Data ◽  
Machine Learning Approach ◽  
Bicycle Infrastructure ◽  
The Difference ◽  
Infrastructure Investments ◽  
Using Data ◽  
The Impact ◽  
The City

Most cities in the United States lack comprehensive or connected bicycle infrastructure; therefore, inexpensive and easy-to-implement solutions for connecting existing bicycle infrastructure are increasingly being employed. Signage is one of the promising solutions. However, the necessary data for evaluating its effect on cycling ridership is lacking. To overcome this challenge, this study tests the potential of using readily-available crowdsourced data in concert with machine-learning methods to provide insight into signage intervention effectiveness. We do this by assessing a natural experiment to identify the potential effects of adding or replacing signage within existing bicycle infrastructure in 2019 in the city of Omaha, Nebraska. Specifically, we first visually compare cycling traffic changes in 2019 to those from the previous two years (2017–2018) using data extracted from the Strava fitness app. Then, we use a new three-step machine-learning approach to quantify the impact of signage while controlling for weather, demographics, and street characteristics. The steps are as follows: Step 1 (modeling and validation) build and train a model from the available 2017 crowdsourced data (i.e., Strava, Census, and weather) that accurately predicts the cycling traffic data for any street within the study area in 2018; Step 2 (prediction) use the model from Step 1 to predict bicycle traffic in 2019 while assuming new signage was not added; Step 3 (impact evaluation) use the difference in prediction from actual traffic in 2019 as evidence of the likely impact of signage. While our work does not demonstrate causality, it does demonstrate an inexpensive method, using readily-available data, to identify changing trends in bicycling over the same time that new infrastructure investments are being added.

The Differential Impact of New Product Development “Make/Buy” Choices on Immediate and Future Product Quality: Insights from the Automobile Industry

2017 ◽  
Vol 81 (6) ◽  
pp. 1-23 ◽  
Author(s):  
Kartik Kalaignanam ◽  
Tarun Kushwaha ◽  
Tracey A. Swartz
Keyword(s):  
Product Development ◽  
Product Quality ◽  
New Product Development ◽  
Automobile Industry ◽  
Positive Impact ◽  
New Product ◽  
The United States ◽  
Trade Offs ◽  
Using Data ◽  
The Impact

This article examines the impact of new product development (NPD) “make/buy” choices on product quality using data from the automobile industry. Although the business press has lamented that NPD outsourcing compromises product quality, there is no systematic evidence to support or refute this assertion. Against this backdrop, this study tests a contingency model of the impact of NPD make/buy decisions on immediate and future product quality. The hypotheses are tested using data on NPD make/buy choices of 173 models of 12 automobile firms in the United States between 2007 and 2014. The authors find that whereas NPD buy has a more positive impact on immediate product quality, NPD make has a more positive impact on future product quality. Furthermore, the immediate product quality impact of NPD buy is stronger when (1) technologies are more complex and (2) firm NPD capability is higher. In contrast, the future product quality impact of NPD make is stronger when (1) there is postlaunch adverse feedback and (2) firm NPD capability is higher. The study highlights the complex trade-offs associated with NPD make/buy decisions and offers valuable insights on how firms could manage these decisions.

scholarly journals Re-calculating the cost of coccidiosis in chickens

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Damer P. Blake ◽  
Jolene Knox ◽  
Ben Dehaeck ◽  
Ben Huntington ◽  
Thilak Rathinam ◽  
...  
Keyword(s):  
Egg Production ◽  
The United States ◽  
The United Kingdom ◽  
Chicken Population ◽  
Global Cost ◽  
Using Data ◽  
The Uk ◽  
The Cost ◽  
The Impact ◽  
Significant Disease

Abstract Coccidiosis, caused by Eimeria species parasites, has long been recognised as an economically significant disease of chickens. As the global chicken population continues to grow, and its contribution to food security intensifies, it is increasingly important to assess the impact of diseases that compromise chicken productivity and welfare. In 1999, Williams published one of the most comprehensive estimates for the cost of coccidiosis in chickens, featuring a compartmentalised model for the costs of prophylaxis, treatment and losses, indicating a total cost in excess of £38 million in the United Kingdom (UK) in 1995. In the 25 years since this analysis the global chicken population has doubled and systems of chicken meat and egg production have advanced through improved nutrition, husbandry and selective breeding of chickens, and wider use of anticoccidial vaccines. Using data from industry representatives including veterinarians, farmers, production and health experts, we have updated the Williams model and estimate that coccidiosis in chickens cost the UK £99.2 million in 2016 (range £73.0–£125.5 million). Applying the model to data from Brazil, Egypt, Guatemala, India, New Zealand, Nigeria and the United States resulted in estimates that, when extrapolated by geographical region, indicate a global cost of ~ £10.4 billion at 2016 prices (£7.7–£13.0 billion), equivalent to £0.16/chicken produced. Understanding the economic costs of livestock diseases can be advantageous, providing baselines to evaluate the impact of different husbandry systems and interventions. The updated cost of coccidiosis in chickens will inform debates on the value of chemoprophylaxis and development of novel anticoccidial vaccines.

P2653Seasonal variations of myocardial infarction and sex-specific differences in Germany

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K Keller ◽  
L Hobohm ◽  
T Munzel ◽  
M A Ostad
Keyword(s):  
Myocardial Infarction ◽  
Seasonal Variation ◽  
Mortality Rate ◽  
Hospital Mortality ◽  
Seasonal Variations ◽  
The United States ◽  
Summer Season ◽  
Recurrent Event ◽  
Acute Mi ◽  
The Impact

Abstract Background Ischemic heart disease (IHD) is the most common cause of death with an increasing frequency worldwide. It accounts for approximately 20% of all deaths in Europe and the United States of America. Approximately 1/3 of the IHD patients present with sudden cardiac death. The acute presentation of IHD myocardial infarction (MI) is a life-threatening, serious health problem, which causes substantially morbidity and mortality. It is well established that the onset of MI follows a circadian and seasonal periodicity. Seasonal variation regarding the incidence and the short-term mortality of acute MI was frequently reported, but data about sex-specific differences are sparse. Purpose Thus, our objectives were to investigate seasonal variations of myocardial infarction. Methods We analyzed the impact of seasons on incidence and in-hospital mortality of patients with acute MI in Germany from 2005 to 2015. We included all MI patients (ICD code I21) with an acute MI (, but not those MI patients with a recurrent event in the first 28 days after a previous MI (ICD code I22)), who were hospitalized in Germany between 2005 and 2015, in this analysis (source: RDC of the Federal Statistical Office and the Statistical Offices of the federal states, DRG Statistics 2005–2015, own calculations). Results The nationwide sample comprised 3,008,188 hospitalizations of patients with MI (2005–2015). The annual incidence was 334.7 per 100.000 population. Incidence inclined from 316.3 to 341.6 per 100.000 population per year (β 0.17 [0.10 to 0.24], P<0.001), while in-hospital mortality rate decreased from 14.1% to 11.3% (β −0.29 [−0.30 to −0.28, P<0.001). Overall, 377,028 (12.5%) patients died in-hospital. Seasonal variation of both incidence and in-hospital mortality were of substantial magnitude. Seasonal incidence (86.1 vs. 79.0 per 100.000 population per year, P<0.001) and in-hospital mortality (13.2% vs. 12.1%, P<0.001) were higher in the winter than in the summer saeson. Risk to die in winter was elevated (OR 1.080 (95% CI 1.069–1.091), P<0.001) compared to summer season independently of sex, age and comorbidities. Reperfusion treatment with drug eluting stents and coronary artery bypass graft were more often used in summer. We observed sex-specific differences regarding the seasonal variation of in-hospital mortality: males showed lowest mortality in summer, while females during fall. Low temperature dependency of mortality seems more pronounced in males. Conclusions Incidence of acute MI increased 2005–2015, while in-hospital mortality rate decreased. Seasonal variations of incidence and in-hospital mortality were of substantial magnitude with lowest incidence and lowest mortality in the summer season. Additionally, we observed sex-specific differences regarding the seasonal variation of the in-hospital mortality. Acknowledgement/Funding This study was supported by the German Federal Ministry of Education and Research (BMBF 01EO1503)

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