scholarly journals Substantial Decreases in NO2 Pollution Measured by Ground-Based Monitors in US Cities During COVID-19 Shutdowns from Reduced Transportation Volumes

2020 ◽  
Author(s):  
Asrah Heintzelman ◽  
Vijay Lulla ◽  
Gabriel Filippelli
Keyword(s):  
Substantial Reduction ◽  
Population Level ◽  
Severe Form ◽  
Air Pollutant ◽  
Sensor Data ◽  
Traffic Patterns ◽  
Sharp Drop ◽  
Related Data ◽  
Travel Restrictions ◽  
Us Cities

The air pollutant NO2 is derived largely from transportation sources and is known to cause respiratory disease. A substantial reduction in transport and industrial processes around the globe from the novel SARS-CoV-2 coronavirus and subsequent pandemic resulted in sharp declines in emissions, including for NO2. Additionally, the COVID-19 disease that results from the coronavirus may present in its most severe form in those who have been exposed to high levels of air pollution. To explore these links, we compared ground-based NO2 sensor data from 11 US cities from a two-month window (March-April) over the previous five years versus the same window during 2020 shutdowns. NO2 declined roughly 12-41% in the 11 cities. This decreased coincided with a sharp drop in vehicular traffic from shutdown-related travel restrictions. To explore this link more closely, we gathered more detailed traffic count data in one city, Indianapolis, Indiana, and found a strong correlation between traffic counts/classification and vehicle miles travelled, and a moderate correlation between NO2 and traffic related data. This finding indicates that we can use such analysis in targeting reduction in pollutants like NO2 by examining and manipulating traffic patterns, thus potentially leading to more population-level health resilience in the future.

scholarly journals Substantial Decreases in U.S. Cities’ Ground-Based NO2 Concentrations during COVID-19 from Reduced Transportation

2021 ◽  
Vol 13 (16) ◽  
pp. 9030
Author(s):  
Asrah Heintzelman ◽  
Gabriel Filippelli ◽  
Vijay Lulla
Keyword(s):  
Substantial Reduction ◽  
Population Level ◽  
Adverse Outcomes ◽  
Sensor Data ◽  
The Novel ◽  
Traffic Patterns ◽  
Sharp Drop ◽  
Related Data ◽  
Global Transport ◽  
Travel Restrictions

A substantial reduction in global transport and industrial processes stemming from the novel SARS-CoV-2 coronavirus and subsequent pandemic resulted in sharp declines in emissions, including for NO2. This has implications for human health, given the role that this gas plays in pulmonary disease and the findings that past exposure to air pollutants has been linked to the most adverse outcomes from COVID-19 disease, likely via various co-morbidities. To explore how much COVID-19 shutdown policies impacted urban air quality, we examined ground-based NO2 sensor data from 11 U.S. cities from a two-month window (March–April) during shutdown in 2020, controlling for natural seasonal variability by using average changes in NO2 over the previous five years for these cities. Levels of NO2 and VMT reduction in March and April compared to January 2020 ranged between 11–65% and 11–89%, consistent with a sharp drop in vehicular traffic from shutdown-related travel restrictions. To explore this link closely, we gathered detailed traffic count data in one city—Indianapolis, Indiana—and found a strong correlation (0.90) between traffic counts/classification and vehicle miles travelled, a moderate correlation (0.54) between NO2 and traffic related data, and an average reduction of 1.11 ppb of NO2 linked to vehicular data. This finding indicates that targeted reduction in pollutants like NO2 can be made by manipulating traffic patterns, thus potentially leading to more population-level health resilience in the future.

scholarly journals Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

2021 ◽  
Author(s):  
Mincheng Wu ◽  
Chao Li ◽  
Zhangchong Shen ◽  
Shibo He ◽  
Lingling Tang ◽  
...  
Keyword(s):  
Participation Rate ◽  
Population Level ◽  
User Participation ◽  
Contact Tracing ◽  
Prevention Measures ◽  
Contact Graph ◽  
Individual Level ◽  
Related Data ◽  
Epidemic Size ◽  
Travel Restrictions

Abstract Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected contacted individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

scholarly journals Measuring social networks in primates: wearable sensors versus direct observations

2020 ◽  
Vol 476 (2236) ◽  
pp. 20190737
Author(s):  
Valeria Gelardi ◽  
Jeanne Godard ◽  
Dany Paleressompoulle ◽  
Nicolas Claidiere ◽  
Alain Barrat
Keyword(s):  
Data Collection ◽  
Wearable Sensors ◽  
A Priori ◽  
Population Level ◽  
Sensor Data ◽  
Collection Method ◽  
Data Collection Method ◽  
The Social ◽  
Different Types ◽  
Data Yield

Network analysis represents a valuable and flexible framework to understand the structure of individual interactions at the population level in animal societies. The versatility of network representations is moreover suited to different types of datasets describing these interactions. However, depending on the data collection method, different pictures of the social bonds between individuals could a priori emerge. Understanding how the data collection method influences the description of the social structure of a group is thus essential to assess the reliability of social studies based on different types of data. This is however rarely feasible, especially for animal groups, where data collection is often challenging. Here, we address this issue by comparing datasets of interactions between primates collected through two different methods: behavioural observations and wearable proximity sensors. We show that, although many directly observed interactions are not detected by the sensors, the global pictures obtained when aggregating the data to build interaction networks turn out to be remarkably similar. Moreover, sensor data yield a reliable social network over short time scales and can be used for long-term studies, showing their important potential for detailed studies of the evolution of animal social groups.

scholarly journals Data safe havens to combine health and genomic data: benefits and challenges

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Kerina H Jones ◽  
Arron S Lacey ◽  
Brian L Perkins ◽  
Mark I Rees
Keyword(s):  
Association Studies ◽  
Genomic Data ◽  
Population Level ◽  
Data Availability ◽  
Genome Wide Association Studies ◽  
Related Data ◽  
Research Areas ◽  
Individual Privacy ◽  
Access Controls ◽  
Health Related

ABSTRACTObjectivesData safe havens can bring together and combine a rich array of anonymised person-based data for research and policy evaluation within a secure setting. To date, the majority of available datasets have been structured micro-data derived from routine health-related records. Possibilities are opening up for the greater reuse of genomic data such as Genome Wide Association studies (GWAS) and Whole Exome/Genome Sequencing (WES or WGS). However, there are considerable challenges to be addressed if the benefits of using these data in combination with health-related data are to be realized safely. ApproachWe explore the benefits and challenges of using genomic datasets with health-related data, and using the Secure Anonymised Information Linkage (SAIL) system as a case study, the implications and way forward for Data Safe Havens in seeking to incorporate genomic data for use with health-related data. ResultsThe benefits of using GWAS, WES and WGS data in conjunction with health-related data include the potential to explore genetics at a population level and open up novel research areas. These include the ability to increasingly stratify and personalize how medical indications are detected and treated through precision medicine by understanding rare conditions and adding socioeconomic and environmental context to genomic data. Among the challenges are: data availability, computing capacity, technical solutions, legal and regulatory frameworks, public perceptions, individual privacy and organizational risk. Many of the challenges within these areas are common to person-based data in general, and often Data Safe Havens have been designed to address these. But there are also aspects of these challenges, and other challenges, specific to genomic data. These include issues due to the unknown clinical significance of genomic information now or in the future, with corresponding risks for privacy and impact on individuals. ConclusionGenomic data sets contain vast amounts of valuable information, some of which is currently undefined, but which may have direct bearing on individual health at some point. The use of these data in combination with health-related data has the potential to bring great benefits, better clinical trial stratification, epidemiology project design and clinical improvements. It is, therefore, essential that such data are surrounded by a properly-designed, robust governance framework including technical and procedural access controls that enable the data to be used safely.

scholarly journals How have governments supported citizens stranded abroad due to COVID-19 travel restrictions? A comparative analysis of the financial and health support in eleven countries

2021 ◽  
Author(s):  
Pippa McDermid ◽  
Adam Craig ◽  
Meru Sheel ◽  
Holly Seale
Keyword(s):  
Information Needs ◽  
Design Tool ◽  
Government Support ◽  
Website Design ◽  
Global Public Health ◽  
Related Data ◽  
Related Information ◽  
Travel Restrictions ◽  
Health Support ◽  
Content Accessibility

Abstract Background: In response to the continuing threat of COVID-19, many countries have implemented some form of border restriction. A repercussion of these restrictions has been that some travellers have been stranded abroad unable to return to their country of residence, and in need for government support. Our analysis explores the COVID-19-related information and support options provided by 11 countries to their citizens stranded overseas due to travel restrictions. We also examined the quality (i.e., readability, accessibility, and useability) of the information that was available from selected governments’ web-based resources.Methods: Between June 18 to June 30, 2021, COVID-19-related webpages from 11 countries (Australia, New Zealand, Fiji, Canada, United States of America (USA), United Kingdom (UK), France, Spain, Japan, Singapore, and Thailand) were reviewed and content relating to information and support for citizens stuck overseas analysed. Government assistance-related data from each webpage was extracted and coded for the following themes: travel arrangements, health and wellbeing, finance and accommodation, information needs, and sources. Readability was examined using the Simplified Measure of Gobbledygook (SMOG) and the Flesch Kincaid readability tests; content ‘accessibility’ was measured using the Web Content Accessibility Guidelines (WCAG) Version 2.1; and content ‘usability’ assessed using the usability heuristics for website design tool.Results: Ninety-eight webpages from 34 websites were evaluated. No country assessed covered all themes analysed. Most provided information and some level of support regarding repatriation options; border control and re-entry measures; medical assistance; and traveller registration. Only three countries provided information or support for emergency housing while abroad, and six provided some form of mental health support for their citizens. Our analysis of the quality of COVID-19-related information available on a subset of four countries’ websites found poor readability and multiple accessibility and usability issues.Conclusion: With large variance in the information and services available across the countries analysed, our results highlight gaps, inconsistencies, and potential inequities in support available, and raise issues pertinent to the quality, accessibility, and usability of information. This study will assist policymakers plan and communicate comprehensive support packages for citizens stuck abroad due to the COVID-19 situation and design future efforts to prepare for global public health emergencies.

scholarly journals Self-Directedness and Cooperativeness, Psychosocial Dysfunction and Suffering in ESSENCE

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Danilo Garcia ◽  
Henrik Anckarsäter ◽  
Sebastian Lundström
Keyword(s):  
Developmental Coordination Disorder ◽  
Population Level ◽  
Autism Spectrum ◽  
Severe Form ◽  
Therapeutic Interventions ◽  
Psychosocial Dysfunction ◽  
Hyperactivity Disorder ◽  
Character Inventory ◽  
Novel Method ◽  
The Impact

Background. The acronym ESSENCE (Early Symptomatic Syndromes Eliciting Neurodevelopmental Clinical Examinations) highlights that children seeking clinical treatment are often multiply impaired, thus requiring treatment from several specialties. The aim was to map and relate, on a population level, ESSENCE to two salient predictors of health and adaptation to adversities, namely, Self-Directedness and Cooperativeness and also to dysfunction and suffering.Methods. Participants were twins(N=1892)aged 9 or 12 whose parents were interviewed with the Autism-Tics, ADHD and other Comorbidities inventory (A-TAC), and the Junior Temperament and Character Inventory (J-TCI). The A-TAC was first used to discern four ESSENCE-related screening diagnoses: autism spectrum disorders, attention deficit hyperactivity disorder, learning disabilities, and developmental coordination disorder; second, to quantify dysfunction and suffering in important social areas.Results. ESSENCE symptoms were continuously and categorically associated with deficiency in Self-Directedness and Cooperativeness and higher ratings of dysfunction and suffering. The impact of ESSENCE symptoms on these measures of mental health was found in a milder form in about 16% of all children and in a severe form in about 2%.Conclusion. Therapeutic interventions focusing on Self-Directedness and Cooperativeness might provide a novel method for child psychiatry in its approach to ESSENCE.

Abstract 265: Million Hearts TM and the PINNACLE Registry ® : Preliminary Data

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Nathan T Glusenkamp ◽  
Brendan Mullen ◽  
Fran Fiocchi ◽  
Joseph P Drozda ◽  
William J Oetgen
Keyword(s):  
Blood Pressure ◽  
Blood Pressure Control ◽  
Performance Measures ◽  
Clinical Performance ◽  
Substantial Reduction ◽  
Population Level ◽  
Pressure Control ◽  
Dietary Sodium ◽  
Smoking Cessation Counseling ◽  
Baseline Performance

Introduction: In September 2011, the Centers for Medicare & Medicaid Services and the Centers for Disease Control launched the Million Hearts campaign - a national public health initiative with the goal of reducing the number of heart attacks and strokes suffered in the US by 1 million over the next 5 years. Multiple federal agencies and private health care institutions have committed to become Million Hearts partners and bring their resources to bear in order to achieve this goal. The Million Hearts goal will be reached by the substantial reduction of dietary sodium and trans fats and by improving the “ABCS” of clinical prevention: Aspirin use for indicated conditions, Blood pressure control, Cholesterol treatment, and Smoking cessation counseling or medications. These four clinical performance measures are within the ken of practicing physicians and are readily measured in the American College of Cardiology’s (ACC) PINNACLE Registry. As a Million Hearts partner, the ACC pledged to provide data and engage in performance improvement initiatives to increase compliance with the four clinical measures. In this study, we compared compliance rates from PINNACLE to the Million Hearts baseline estimates for the nation and to their 2017 cardiovascular goals. Methods: The PINNACLE Registry contains data from more than 2.5 million outpatient encounters recorded over the past four years - representing approximately 800,000 discrete patients. Around 1,000 providers electronically submit data to PINNACLE and receive quarterly performance reports. Data queries determined PINNACLE provider compliance with analogs of the four Million Hearts performance measures. Results: see attached jpg Conclusion: Baseline performance measures in PINNACLE are favorable compared to the Million Hearts initial national estimates and 5-year goals. Million Hearts goals are population-level targets based on national survey data whereas PINNACLE patients are, by definition, in care, so some elevation of rates in the latter cohort is to be expected. There is, however, room for improvement in three of the four PINNACLE baseline performance measures. Concordant with the plans of the Million Hearts executive and scientific leadership, initial improvement efforts developed by the ACC will be directed toward improvement in blood pressure control of patients in the PINNACLE Registry. As the Million Hearts initiative moves forward, we can undertake formal efforts to learn from the higher rates of measure adherence and performance seen in cardiology practices by using top PINNACLE sites as a source for modular best practices around the ABCS.

Stand-alone low-cost sensor network in the inner city of Munich for modeling urban air pollutants

2021 ◽  
Author(s):  
Adrian Wenzel ◽  
Jia Chen ◽  
Florian Dietrich ◽  
Sebastian T. Thekkekara ◽  
Daniel Zollitsch ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Sensor Network ◽  
Air Pollutants ◽  
Low Cost ◽  
Air Pollutant ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Small Scale ◽  
Urban Air

<p>Modeling urban air pollutants is a challenging task not only due to the complicated, small-scale topography but also due to the complex chemical processes within the chemical regime of a city. Nitrogen oxides (NOx), particulate matter (PM) and other tracer gases, e.g. formaldehyde, hold information about which chemical regime is present in a city. As we are going to test and apply chemical models for urban pollution – especially with respect to spatial and temporally variability – measurement data with high spatial and temporal resolution are critical.</p><p>Since governmental monitoring stations of air pollutants such as PM, NOx, ozone (O<sub>3</sub>) or carbon monoxide (CO) are large and costly, they are usually only sparsely distributed throughout a city. Hence, the official monitoring sites are not sufficient to investigate whether small-scale variability and its integrated effects are captured well by models. Smart networks consisting of small low-cost air pollutant sensors have the ability to provide the required grid density and are therefore the tool of choice when it comes to setting up or validating urban modeling frameworks. Such sensor networks have been established and run by several groups, achieving spatial and temporal high-resolution concentration maps [1, 2].</p><p>After having conducted a measurement campaign in 2016 to create a high-resolution NO<sub>2</sub> concentration map for Munich [3], we are currently setting up a low-cost sensor network to measure NOx, PM, O<sub>3</sub> and CO concentrations as well as meteorological parameters [4]. The sensors are stand-alone, so that they do not demand mains supply, which gives us a high flexibility in their deployment. Validating air quality models not only requires dense but also high-accuracy measurements. Therefore, we will calibrate our sensor nodes on a weekly basis using a mobile reference instrument and apply the gathered sensor data to a Machine Learning model of the sensor nodes. This will help minimize the often occurring drawbacks of low-cost sensors such as sensor drift, environmental influences and sensor cross sensitivities.</p><p> </p><p>[1] Bigi, A., Mueller, M., Grange, S. K., Ghermandi, G., and Hueglin, C.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, https://doi.org/10.5194/amt-11-3717-2018, 2018</p><p>[2] Kim, J., Shusterman, A. A., Lieschke, K. J., Newman, C., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors, Atmos. Meas. Tech., 11, 1937–1946, https://doi.org/10.5194/amt-11-1937-2018, 2018</p><p>[3] Zhu, Y., Chen, J., Bi, X., Kuhlmann, G., Chan, K. L., Dietrich, F., Brunner, D., Ye, S., and Wenig, M.: Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities, Atmos. Chem. Phys., 20, 13241–13251, https://doi.org/10.5194/acp-20-13241-2020, 2020</p><p>[4] Zollitsch, D., Chen, J., Dietrich, F., Voggenreiter, B., Setili, L., and Wenig, M.: Low-Cost Air Quality Sensor Network in Munich, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19276, https://doi.org/10.5194/egusphere-egu2020-19276, 2020</p>

scholarly journals Smart Monitoring of Population Health Risk Behaviour

2019 ◽  
Vol 8 (1) ◽  
pp. 76-80
Author(s):  
Kirti Sundar Sahu ◽  
Arlene Oetomo ◽  
Plinio Morita
Keyword(s):  
Physical Activity ◽  
Health Risk ◽  
Health Agency ◽  
Health Indicators ◽  
Population Level ◽  
Risk Behaviour ◽  
Sensor Data ◽  
Health Risk Behaviour ◽  
Individual Level ◽  
Smart Technologies

Monitoring population-level health-risk behaviour is integral to preventing chronic diseases (i.e., diabetes, cardiovascular disease, cancer, etc.). Physical activity and sleep are the key behaviours which influence human health. Smart technologies can be used to improve real-time monitoring of risky behaviours. The objective of this study is to explore population- and individual-level remote monitoring of sleep, indoor physical activity and sedentary behaviours in Canada using data from the Internet of Things (IoT) (ecobee smart thermostat) and fitness trackers. Method: 386 person-hours of data were collected in a pilot study (n =8) to validate the motion sensor data from ecobee smart thermostats. Then, using “Donate your Data” data from ecobee indicators of population-level health were calculated. Results: A positive Spearman correlation coefficient 0.8 (p>0.0001) was found between standard fitness tracker data and ecobee sensors validating its use for population-level analysis. Our results were similar to the Public Health Agency of Canada’s results derived from self-reported surveillance methods. Discussion: This project demonstrates the use of data from non-health sources, like ubiquitous IoT to curate population- and individual-level health indicators. We will deliver novel indicators and insights into health status through the creation of user-centered designed dashboards for individuals, researchers, and policy-makers.

scholarly journals GP.1 Changes in ischemic stroke presentations and associated workflow during the first wave of the COVID-19 pandemic: A population study

2021 ◽  
Vol 48 (s3) ◽  
pp. S12-S12
Author(s):  
A Ganesh ◽  
JM Stang ◽  
FA McAlister ◽  
O Shlakhter ◽  
JK Holodinsky ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Population Level ◽  
Stroke Care ◽  
Hospital Treatment ◽  
Stroke Severity ◽  
Care Needs ◽  
Acute Therapy ◽  
Treatment Delays ◽  
Related Data ◽  
Adjusted Incidence Rate

Background: Pandemics may promote hospital avoidance among patients with emergencies, and added precautions may exacerbate treatment delays. Methods: We used linked administrative data and data from the Quality Improvement and Clinical Research Alberta Stroke Program – a registry capturing stroke-related data on the entire Albertan population(4.3 million) – to identify all patients hospitalized with stroke in the pre-pandemic(01/01/2016-27/02/2020) and COVID-19 pandemic(28/02/2020-30/08/2020) periods. We examined changes in stroke presentation rates and use of thrombolysis and endovascular therapy(EVT), adjusted for age, sex, comorbidities, and pre-admission care needs; and in workflow, stroke severity(National Institutes of Health Stroke Scale/NIHSS), and in-hospital outcomes. Results: We analyzed 19,531 patients with ischemic stroke pre-pandemic versus 2,255 during the pandemic. Hospitalizations/presentations dropped(weekly adjusted-incidence-rate-ratio[aIRR]:0.48,95%CI:0.46-0.50), as did population-level incidence of thrombolysis(aIRR:0.49,0.44-0.56) or EVT(aIRR:0.59,0.49-0.69). However, proportions of presenting patients receiving thrombolysis/EVT did not decline (thrombolysis:11.7% pre-pandemic vs 13.1% during-pandemic, aOR:1.02,0.75-1.38). For out-of-hospital strokes, onset-to-door times were prolonged(adjusted-coefficient:37.0-minutes, 95%CI:16.5-57.5), and EVT recipients experienced greater door-to-reperfusion delays(adjusted-coefficient:18.7-minutes,1.45-36.0). NIHSS scores and in-hospital mortality did not differ. Conclusions: The first COVID-19 wave was associated with a halving of presentations and acute therapy utilization for ischemic stroke at a population level, and greater pre-/in-hospital treatment delays. Our data can inform public health messaging and stroke care in future pandemic waves.

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