scholarly journals High resolution proximity statistics as early warning for US universities reopening during COVID-19

2020 ◽  
Author(s):  
Zakaria Mehrab ◽  
Akhilandeshwari Goud Ranga ◽  
Debarati Sarkar ◽  
Srinivasan Venkatramanan ◽  
Youngyun Chung Baek ◽  
...  
Keyword(s):  
High Resolution ◽  
Disease Surveillance ◽  
Lead Time ◽  
The United States ◽  
Median Income ◽  
Land Grant University ◽  
Student Community ◽  
Case Rate ◽  
Rate Intensity ◽  
The Impact

AbstractReopening of colleges and universities for the Fall semester of 2020 across the United States has caused significant COVID-19 case spikes, requiring reactive responses such as temporary closures and switching to online learning. Until sufficient levels of immunity are reached through vaccination, Institutions of Higher Education will need to balance academic operations with COVID-19 spread risk within and outside the student community. In this work, we study the impact of proximity statistics obtained from high resolution mobility traces in predicting case rate surges in university counties. We focus on 50 land-grant university counties (LGUCs) across the country and show high correlation (PCC > 0.6) between proximity statistics and COVID-19 case rates for several LGUCs during the period around Fall 2020 reopenings. These observations provide a lead time of up to ∼3 weeks in preparing resources and planning containment efforts. We also show how features such as total population, population affiliated with university, median income and case rate intensity could explain some of the observed high correlation. We believe these easily explainable mobility metrics along with other disease surveillance indicators can help universities be better prepared for the Spring 2021 semester.

Foodborne Disease in Canada - a 5-year Summary

1983 ◽  
Vol 46 (7) ◽  
pp. 650-675 ◽  
Author(s):  
E. C. D. TODD
Keyword(s):  
Food Processing ◽  
Disease Surveillance ◽  
The United States ◽  
Foodborne Disease ◽  
Salmonella Spp ◽  
Naturally Occurring ◽  
Time Period ◽  
Etiologic Agents ◽  
The Impact ◽  
Disease Specific

Five years of foodborne disease surveillance in Canada were examined. Microorganisms, particularly Salmonella spp., Staphylococcus aureus and Clostridium perfringens, were the main etiologic agents, but diseases also resulted from contaminanation of food with chemicals and parasites or food containing naturally-occurring plant and animal toxins. The foods involved were, in general, potentially hazardous items, such as meat and poultry. Where information is known, most of the problems associated with foodborne illness occurred at foodservice establishments, but the impact of mishandling in homes and food processing establishments was also great. The kinds of data accumulated were similar to those from the United States for the same time period, In order to reduce the prevalence of foodborne disease, specific educational and enforcement programs have to be initiated. Similar approaches could be taken for both countries.

scholarly journals Socioeconomic privilege and political ideology are associated with racial disparity in COVID-19 vaccination

2021 ◽  
Vol 118 (33) ◽  
pp. e2107873118
Author(s):  
Ritu Agarwal ◽  
Michelle Dugas ◽  
Jui Ramaprasad ◽  
Junjie Luo ◽  
Gujie Li ◽  
...  
Keyword(s):  
Racial Disparities ◽  
Republican Party ◽  
Political Ideology ◽  
Adult Population ◽  
The United States ◽  
Vaccine Uptake ◽  
Vaccine Hesitancy ◽  
Median Income ◽  
Structural Inequities ◽  
The Impact

Vaccine uptake is critical for mitigating the impact of COVID-19 in the United States, but structural inequities pose a serious threat to progress. Racial disparities in vaccination persist despite the increased availability of vaccines. We ask what factors are associated with such disparities. We combine data from state, federal, and other sources to estimate the relationship between social determinants of health and racial disparities in COVID-19 vaccinations at the county level. Analyzing vaccination data from 19 April 2021, when nearly half of the US adult population was at least partially vaccinated, we find associations between racial disparities in COVID-19 vaccination and median income (negative), disparity in high school education (positive), and vote share for the Republican party in the 2020 presidential election (negative), while vaccine hesitancy is not related to disparities. We examine differences in associations for COVID-19 vaccine uptake as compared with influenza vaccine. Key differences include an amplified role for socioeconomic privilege factors and political ideology, reflective of the unique societal context in which the pandemic has unfolded.

scholarly journals The Impact of State Mask-Wearing Requirements on the Growth of COVID-19 Cases, Hospitalizations, and Deaths in the United States

2021 ◽  
Author(s):  
Peter F Rebeiro ◽  
David M Aronoff ◽  
M Kevin Smith
Keyword(s):  
United States ◽  
The United States ◽  
Us States ◽  
Case Rate ◽  
Multivariable Models ◽  
The Impact

Abstract In ecologic analyses of US states, piecewise multivariable models showed lower post- vs. pre-mask requirement case-rate slopes, with -1.0% (95%CI: -1.34%, -0.57%) and -0.44% (95%CI: -0.86%, -0.03%) per 100,000 per day among early- and late- versus never-adopter states, respectively. Our findings support statewide mask requirements to mitigate COVID-19 transmission.

scholarly journals High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S.

2021 ◽  
Vol 12 (4) ◽  
pp. 1-20
Author(s):  
Shixiang Zhu ◽  
Alexander Bukharin ◽  
Liyan Xie ◽  
Mauricio Santillana ◽  
Shihao Yang ◽  
...  
Keyword(s):  
High Resolution ◽  
Demographic Factors ◽  
The United States ◽  
County Level ◽  
Current Time ◽  
Pairwise Correlation ◽  
Community Mobility ◽  
Temporal Model ◽  
Spatio Temporal ◽  
The Impact

We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases 1 week ahead of the current time, at the county level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (1) temporal auto- and pairwise correlation of the two local time series (confirmed cases and deaths from the COVID-19), (2) correlation between locations (propagation between counties), and (3) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model’s high dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top 10 metropolitan areas in the nation, which we refer to (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multivariate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability.

scholarly journals A global repository of novel antimicrobial emergence events

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 1320
Author(s):  
Emma Mendelsohn ◽  
Noam Ross ◽  
Allison M. White ◽  
Karissa Whiting ◽  
Cale Basaraba ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
English Language ◽  
Bacterial Species ◽  
The United States ◽  
Antibiotic Drugs ◽  
Open Access Database ◽  
Global Events ◽  
The Impact ◽  
Bacteria Resistance ◽  
Global Drivers

Despite considerable global surveillance of antimicrobial resistance (AMR), data on the global emergence of new resistance genotypes in bacteria has not been systematically compiled. We conducted a study of English-language scientific literature (2006-2017) and ProMED-mail disease surveillance reports (1994-2017) to identify global events of novel AMR emergence (first clinical reports of unique drug-bacteria resistance combinations). We screened 24,966 abstracts and reports, ultimately identifying 1,757 novel AMR emergence events from 268 peer-reviewed studies and 26 disease surveillance reports (294 total). Events were reported in 66 countries, with most events in the United States (152), China (128), and India (127). The most common bacteria demonstrating new resistance were Klebsiella pneumoniae (344) and Escherichia coli (218). Resistance was most common against antibiotic drugs imipenem (89 events), ciprofloxacin (84) and ceftazidime (83). We provide an open-access database of emergence events with standardized fields for bacterial species, drugs, location, and date. We discuss the impact of reporting and surveillance bias on database coverage, and we suggest guidelines for data analysis. This database may be broadly useful for understanding rates and patterns of AMR evolution, identifying global drivers and correlates, and targeting surveillance and interventions.

scholarly journals Investigating the Impact of High-Resolution Land–Sea Masks on Hurricane Forecasts in HWRF

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 888 ◽  
Author(s):  
Zaizhong Ma ◽  
Bin Liu ◽  
Avichal Mehra ◽  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
...  
Keyword(s):  
High Resolution ◽  
Gulf Coast ◽  
Surface Wind ◽  
The United States ◽  
Near Surface ◽  
Hurricane Wind ◽  
Atlantic Hurricanes ◽  
Environmental Prediction ◽  
The Impact ◽  
First Time

Realistic wind information is critical for accurate forecasts of landfalling hurricanes. In order to provide more realistic near-surface wind forecasts of hurricanes over coastal regions, high-resolution land–sea masks are considered. As a leading hurricane modeling system, the National Centers for Environmental Prediction (NCEP) Hurricane Weather Research Forecast (HWRF) system has been widely used in both operational and research environments for studying hurricanes in different basins. In this study, high-resolution land–sea mask datasets are introduced to the nested domain of HWRF, for the first time, as an attempt to improve hurricane wind forecasts. Four destructive North Atlantic hurricanes (Harvey and Irma in 2017; and Florence and Michael in 2018), which brought historic wind damage and storm surge along the Eastern Seaboard of the United States and Northeastern Gulf Coast, were selected to demonstrate the methodology of extending the capability to HWRF, due to the introduction of the high-resolution land–sea masks into the nested domains for the first time. A preliminary assessment of the numerical experiments with HWRF shows that the introduction of high-resolution land–sea masks into the nested domains produce significantly more accurate definitions of coastlines, land-use, and soil types. Furthermore, the high-resolution land–sea mask not only improves the quality of simulated wind information along the coast, but also improves the hurricane track, intensity, and storm-size predictions.

scholarly journals The Impact of Climate Change on Hazardous Convective Weather in the United States: Insight from High-Resolution Dynamical Downscaling

2017 ◽  
Vol 30 (24) ◽  
pp. 10081-10100 ◽  
Author(s):  
Kimberly A. Hoogewind ◽  
Michael E. Baldwin ◽  
Robert J. Trapp
Keyword(s):  
Climate Change ◽  
United States ◽  
High Resolution ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
The United States ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Daily Frequency ◽  
Convective Weather ◽  
The Impact

This study explores the potential impact anthropogenic climate change may have upon hazardous convective weather (HCW; i.e., tornadoes, large hail, and damaging wind gusts) in the United States. Utilizing the Weather Research and Forecasting (WRF) Model, high-resolution (4 km) dynamically downscaled simulations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), are produced for a historical (1971–2000) and future (2071–2100) period. Synthetic HCW day climatologies are created using upward vertical velocity (UVV) exceeding 22 m s−1 as a proxy for HCW occurrence and subsequently compared to the environmental approach of estimating changes in daily frequency of convective environments favorable for HCW (NDSEV) from the driving climate model. Results from the WRF simulations demonstrate that the proxy for HCW becomes more frequent by the end of the twenty-first century, with the greatest absolute increases in daily frequency occurring during the spring and summer. Compared to NDSEV from GFDL CM3, both approaches suggest a longer HCW season, perhaps lengthening by more than a month. The change in environmental estimates are 2–4 times larger than that gauged from WRF; further analyses show that the conditional probability of HCW given NDSEV declines during summer for much of the central United States, a result that may be attributed to both an increase in the magnitude of convective inhibition (CIN) and decreased forcing for ascent, hindering convective initiation. Such an outcome supports the motivation for continued use of dynamical downscaling to overcome the limitations of the GCM-based environmental analysis.

Atomic resolution characterisation of interface structures by Electron Energy Loss Spectroscopy

1993 ◽  
Vol 51 ◽  
pp. 576-577
Author(s):  
N. D. Browning ◽  
M. M. McGibbon ◽  
M. F. Chisholm ◽  
S. J. Pennycook
Keyword(s):  
High Resolution ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Imaging Technique ◽  
Atomic Scale ◽  
Atomic Resolution ◽  
Reference Image ◽  
The Impact ◽  
Electron Energy Loss

The recent development of the Z-contrast imaging technique for the VG HB501 UX dedicated STEM, has added a high-resolution imaging facility to a microscope used mainly for microanalysis. This imaging technique not only provides a high-resolution reference image, but as it can be performed simultaneously with electron energy loss spectroscopy (EELS), can be used to position the electron probe at the atomic scale. The spatial resolution of both the image and the energy loss spectrum can be identical, and in principle limited only by the 2.2 Å probe size of the microscope. There now exists, therefore, the possibility to perform chemical analysis of materials on the scale of single atomic columns or planes.In order to achieve atomic resolution energy loss spectroscopy, the range over which a fast electron can cause a particular excitation event, must be less than the interatomic spacing. This range is described classically by the impact parameter, b, which ranges from ~10 Å for the low loss region of the spectrum to <1Å for the core losses.

Demonstrating Nutrient Cost Gradients: A Brooklyn Case Study

2014 ◽  
Vol 84 (5-6) ◽  
pp. 244-251 ◽  
Author(s):  
Robert J. Karp ◽  
Gary Wong ◽  
Marguerite Orsi
Keyword(s):  
Low Income ◽  
Energy Content ◽  
Food Selection ◽  
The United States ◽  
United States Department ◽  
Micronutrient Deficiencies ◽  
Caloric Density ◽  
Low Income Families ◽  
The Cost ◽  
The Impact

Abstract. Introduction: Foods dense in micronutrients are generally more expensive than those with higher energy content. These cost-differentials may put low-income families at risk of diminished micronutrient intake. Objectives: We sought to determine differences in the cost for iron, folate, and choline in foods available for purchase in a low-income community when assessed for energy content and serving size. Methods: Sixty-nine foods listed in the menu plans provided by the United States Department of Agriculture (USDA) for low-income families were considered, in 10 domains. The cost and micronutrient content for-energy and per-serving of these foods were determined for the three micronutrients. Exact Kruskal-Wallis tests were used for comparisons of energy costs; Spearman rho tests for comparisons of micronutrient content. Ninety families were interviewed in a pediatric clinic to assess the impact of food cost on food selection. Results: Significant differences between domains were shown for energy density with both cost-for-energy (p < 0.001) and cost-per-serving (p < 0.05) comparisons. All three micronutrient contents were significantly correlated with cost-for-energy (p < 0.01). Both iron and choline contents were significantly correlated with cost-per-serving (p < 0.05). Of the 90 families, 38 (42 %) worried about food costs; 40 (44 %) had chosen foods of high caloric density in response to that fear, and 29 of 40 families experiencing both worry and making such food selection. Conclusion: Adjustments to USDA meal plans using cost-for-energy analysis showed differentials for both energy and micronutrients. These differentials were reduced using cost-per-serving analysis, but were not eliminated. A substantial proportion of low-income families are vulnerable to micronutrient deficiencies.

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