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  1. Article ; Online: A Geographical Analysis of Socioeconomic and Environmental Drivers of Physical Inactivity in Post Pandemic Cities

    Alexander Hohl / Aynaz Lotfata

    Urban Science, Vol 6, Iss 28, p

    The Case Study of Chicago, IL, USA

    2022  Volume 28

    Abstract: The pandemic’s lockdown has made physical inactivity unavoidable, forcing many people to work from home and increasing the sedentary nature of their lifestyle. The link between spatial and socio-environmental dynamics and people’s levels of physical ... ...

    Abstract The pandemic’s lockdown has made physical inactivity unavoidable, forcing many people to work from home and increasing the sedentary nature of their lifestyle. The link between spatial and socio-environmental dynamics and people’s levels of physical activity is critical for promoting healthy lifestyles and improving population health. Most studies on physical activity or sedentary behaviors have focused on the built environment, with less attention to social and natural environments. We illustrate the spatial distribution of physical inactivity using the space scan statistic to supplement choropleth maps of physical inactivity prevalence in Chicago, IL, USA. In addition, we employ geographically weighted regression (GWR) to address spatial non-stationarity of physical inactivity prevalence in Chicago per census tract. Lastly, we compare GWR to the traditional ordinary least squares (OLS) model to assess the effect of spatial dependency in the data. The findings indicate that, while access to green space, bike lanes, and living in a diverse environment, as well as poverty, unsafety, and disability, are associated with a lack of interest in physical activities, limited language proficiency is not a predictor of an inactive lifestyle. Our findings suggest that physical activity is related to socioeconomic and environmental factors, which may help guide future physical activity behavior research and intervention decisions, particularly in identifying vulnerable areas and people.
    Keywords social and environmental factors ; physical inactivity prevalence ; urban health ; post pandemic cities ; Chicago ; Geography. Anthropology. Recreation ; G ; Social Sciences ; H
    Subject code 910
    Language English
    Publishing date 2022-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Sightseeing Accidents with Helicopters and Fixed-Wing Aircraft.

    de Voogt, Alexander J / Hohl, Caio Hummel / Kalagher, Hilary

    Aerospace medicine and human performance

    2022  Volume 93, Issue 6, Page(s) 532–535

    Abstract: BACKGROUND: ...

    Abstract BACKGROUND:
    MeSH term(s) Accidents, Aviation ; Aircraft ; Databases, Factual ; Geography ; Humans ; Weather
    Language English
    Publishing date 2022-06-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2809085-8
    ISSN 2375-6322 ; 2375-6314
    ISSN (online) 2375-6322
    ISSN 2375-6314
    DOI 10.3357/AMHP.6000.2022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Detecting space-time patterns of disease risk under dynamic background population.

    Hohl, Alexander / Tang, Wenwu / Casas, Irene / Shi, Xun / Delmelle, Eric

    Journal of geographical systems

    2022  Volume 24, Issue 3, Page(s) 389–417

    Abstract: We are able to collect vast quantities of spatiotemporal data due to recent technological advances. Exploratory space-time data analysis approaches can facilitate the detection of patterns and formation of hypotheses about their driving processes. ... ...

    Abstract We are able to collect vast quantities of spatiotemporal data due to recent technological advances. Exploratory space-time data analysis approaches can facilitate the detection of patterns and formation of hypotheses about their driving processes. However, geographic patterns of social phenomena like crime or disease are driven by the underlying population. This research aims for incorporating temporal population dynamics into spatial analysis, a key omission of previous methods. As population data are becoming available at finer spatial and temporal granularity, we are increasingly able to capture the dynamic patterns of human activity. In this paper, we modify the space-time kernel density estimation method by accounting for spatially and temporally dynamic background populations (ST-DB), assess the benefits of considering the temporal dimension and finally, compare ST-DB to its purely spatial counterpart. We delineate clusters and compare them, as well as their significance, across multiple parameter configurations. We apply ST-DB to an outbreak of dengue fever in Cali, Colombia during 2010-2011. Our results show that incorporating the temporal dimension improves our ability to delineate significant clusters. This study addresses an urgent need in the spatiotemporal analysis literature by using population data at high spatial and temporal resolutions.
    Language English
    Publishing date 2022-04-20
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 1481603-9
    ISSN 1435-5949 ; 1435-5930
    ISSN (online) 1435-5949
    ISSN 1435-5930
    DOI 10.1007/s10109-022-00377-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Fatality and Operational Specificity of Helicopter Accidents on the Ground.

    de Voogt, Alexander J / Hummel Hohl, Caio / Kalagher, Hilary

    Aerospace medicine and human performance

    2021  Volume 92, Issue 7, Page(s) 593–596

    Abstract: INTRODUCTION: ...

    Abstract INTRODUCTION:
    MeSH term(s) Accidents ; Accidents, Aviation ; Aircraft ; Databases, Factual ; Humans
    Language English
    Publishing date 2021-09-09
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2809085-8
    ISSN 2375-6322 ; 2375-6314
    ISSN (online) 2375-6322
    ISSN 2375-6314
    DOI 10.3357/AMHP.5801.2021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Spatial Distribution of Hateful Tweets Against Asians and Asian Americans During the COVID-19 Pandemic, November 2019 to May 2020.

    Hohl, Alexander / Choi, Moongi / Yellow Horse, Aggie J / Medina, Richard M / Wan, Neng / Wen, Ming

    American journal of public health

    2022  Volume 112, Issue 4, Page(s) 646–649

    Abstract: Objectives. ...

    Abstract Objectives.
    MeSH term(s) Asian ; COVID-19 ; Hate ; Humans ; Pandemics ; Public Health ; United States/epidemiology
    Language English
    Publishing date 2022-03-22
    Publishing country United States
    Document type Journal Article
    ZDB-ID 121100-6
    ISSN 1541-0048 ; 0090-0036 ; 0002-9572
    ISSN (online) 1541-0048
    ISSN 0090-0036 ; 0002-9572
    DOI 10.2105/AJPH.2021.306653
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States.

    Hohl, Alexander / Delmelle, Eric M / Desjardins, Michael R / Lan, Yu

    Spatial and spatio-temporal epidemiology

    2020  Volume 34, Page(s) 100354

    Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Wuhan City, China. The virus may cause novel coronavirus disease 2019 (COVID-19) in symptomatic individuals. Since December of 2019, there have been ... ...

    Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Wuhan City, China. The virus may cause novel coronavirus disease 2019 (COVID-19) in symptomatic individuals. Since December of 2019, there have been over 7,000,000 confirmed cases and over 400,000 confirmed deaths worldwide. In the United States (U.S.), there have been over 2,000,000 confirmed cases and over 110,000 confirmed deaths. COVID-19 case data in the United States has been updated daily at the county level since the first case was reported in January of 2020. There currently lacks a study that showcases the novelty of daily COVID-19 surveillance using space-time cluster detection techniques. In this paper, we utilize a prospective Poisson space-time scan statistic to detect daily clusters of COVID-19 at the county level in the contiguous 48 U.S. and Washington D.C. As the pandemic progresses, we generally find an increase of smaller clusters of remarkably steady relative risk. Daily tracking of significant space-time clusters can facilitate decision-making and public health resource allocation by evaluating and visualizing the size, relative risk, and locations that are identified as COVID-19 hotspots.
    MeSH term(s) COVID-19 ; Communicable Diseases, Emerging/epidemiology ; Coronavirus Infections/diagnosis ; Coronavirus Infections/epidemiology ; Databases, Factual ; Disease Outbreaks/statistics & numerical data ; Female ; Humans ; Male ; Mass Screening/methods ; Models, Statistical ; Monte Carlo Method ; Pandemics/statistics & numerical data ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/epidemiology ; Poisson Distribution ; Prevalence ; Prospective Studies ; Public Health ; Severe Acute Respiratory Syndrome/diagnosis ; Severe Acute Respiratory Syndrome/epidemiology ; Space-Time Clustering ; United States/epidemiology
    Keywords covid19
    Language English
    Publishing date 2020-06-27
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2515896-X
    ISSN 1877-5853 ; 1877-5845
    ISSN (online) 1877-5853
    ISSN 1877-5845
    DOI 10.1016/j.sste.2020.100354
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic ; an update

    Hohl, Alexander / Delmelle, Eric / Desjardins, Michael

    SIGSPATIAL Special

    2020  Volume 12, Issue 1, Page(s) 27–33

    Keywords covid19
    Language English
    Publisher Association for Computing Machinery (ACM)
    Publishing country us
    Document type Article ; Online
    ISSN 1946-7729
    DOI 10.1145/3404820.3404825
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic ; an update

    Hohl, Alexander / Delmelle, Eric / Desjardins, Michael

    SIGSPATIAL Special

    2020  Volume 12, Issue 1, Page(s) 27–33

    Keywords covid19
    Language English
    Publisher Association for Computing Machinery (ACM)
    Publishing country us
    Document type Article ; Online
    ISSN 1946-7729
    DOI 10.1145/3404111.3404116
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Histological examination of renal nerve distribution, density, and function in humans.

    Struthoff, Helge / Lauder, Lucas / Hohl, Mathias / Hermens, Alexander / Tzafriri, Abraham Rami / Edelman, Elazer R / Kunz, Michael / Böhm, Michael / Tschernig, Thomas / Mahfoud, Felix

    EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology

    2023  Volume 19, Issue 7, Page(s) 612–620

    Abstract: Background: Renal denervation is optimised when guided by knowledge of nerve distribution.: Aims: We aimed to assess sympathetic nerve distribution along the renal arteries, especially in post-bifurcation vessel segments.: Methods: Renal arteries ... ...

    Abstract Background: Renal denervation is optimised when guided by knowledge of nerve distribution.
    Aims: We aimed to assess sympathetic nerve distribution along the renal arteries, especially in post-bifurcation vessel segments.
    Methods: Renal arteries and surrounding tissue from 10 body donors were collected and examined histologically. Immunohistochemical staining was used to analyse nerve distribution and to identify afferent and efferent sympathetic nerves.
    Results: A total of 6,781 nerves surrounding 18 renal arteries were evaluated. The mean lumen-nerve distance of the left renal artery (2.32±1.95 mm) was slightly greater than the right (2.29±2.03 mm; p=0.161); this varied across the arteries' courses: 3.7±2.3 mm in proximal segments, 2.5±2.0 mm in middle segments, 1.9±1.6 mm in distal prebifurcation segments and 1.3±1.0 mm in post-bifurcation segments (p<0.001). The number of nerves per quadrant was highest in the proximal segments (13.7±18.6), followed by the middle (9.7±7.9), distal prebifurcation (8.0±7.6), and distal post-bifurcation (4.3±4.0) segments (p<0.001). Circumferentially, the number of nerves was highest in the superior (7.8±9.4) and the ventral (7.6±13.1) quadrants (p=0.638). The mean tyrosine hydroxylase (TH) to calcitonin gene-related peptide (CGRP) ratio increased from proximal (37.5±33.5) to distal (72.0±7.2 in the post-bifurcation segments; p<0.001). Thirty-eight neuroganglia were identified along 14 (78%) renal arteries.
    Conclusions: Nerves converge to the renal arteries' lumen in the distal segments and along branches, resulting in the lowest number of nerves per quadrant and the shortest lumen-nerve distance in the distal post-bifurcation segments. Efferent nerves occur predominantly, and the ratio of efferent to afferent nerves continues to increase in the vessels' course.
    MeSH term(s) Humans ; Sympathectomy/methods ; Sympathetic Nervous System ; Kidney ; Renal Artery/innervation
    Language English
    Publishing date 2023-07-27
    Publishing country France
    Document type Journal Article
    ZDB-ID 2457174-X
    ISSN 1969-6213 ; 1774-024X
    ISSN (online) 1969-6213
    ISSN 1774-024X
    DOI 10.4244/EIJ-D-23-00264
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Understanding Adverse Population Sentiment Towards the Spread of COVID-19 in the United States

    Hohl, Alexander / Choi, Moongi / Medina, Richard / Wan, Neng / Wen, Ming

    medRxiv

    Abstract: Background - During the ongoing COVID-19 pandemic, the immediate threat of illness and mortality is not the only concern. In the United States, COVID-19 is not only causing physical suffering to patients, but also great levels of adverse sentiment (e.g., ...

    Abstract Background - During the ongoing COVID-19 pandemic, the immediate threat of illness and mortality is not the only concern. In the United States, COVID-19 is not only causing physical suffering to patients, but also great levels of adverse sentiment (e.g., fear, panic, anxiety) among the public. Such secondary threats can be anticipated and explained through sentiment analysis of social media, such as Twitter. Methods - We obtained a dataset of geotagged tweets on the topic of COVID-19 in the contiguous United States during the period of 11/1/2019 - 9/15/2020. We classified each tweet into "adverse" and "non-adverse" using the NRC Emotion Lexicon and tallied up the counts for each category per county per day. We utilized the space-time scan statistic to find clusters and a three-stage regression approach to identify socioeconomic and demographic correlates of adverse sentiment. Results - We identified substantial spatiotemporal variation in adverse sentiment in our study area/period. After an initial period of low-level adverse sentiment (11/1/2019 - 1/15/2020), we observed a steep increase and subsequent fluctuation at a higher level (1/16/2020 - 9/15/2020). The number of daily tweets was low initially (11/1/2019 - 1/22/2020), followed by spikes and subsequent decreases until the end of the study period. The space-time scan statistic identified 12 clusters of adverse sentiment of varying size, location, and strength. Clusters were generally active during the time period of late March to May/June 2020. Increased adverse sentiment was associated with decreased racial/ethnic heterogeneity, decreased rurality, higher vulnerability in terms of minority status and language, and housing type and transportation. Conclusions - We utilized a dataset of geotagged tweets to identify the spatiotemporal patterns and the spatial correlates of adverse population sentiment during the first two waves of the COVID-19 pandemic in the United States. The characteristics of areas with high adverse sentiment may be relevant for communication of containment measures. The combination of spatial clustering and regression can be beneficial for understanding of the ramifications of COVID-19, as well as disease outbreaks in general.
    Keywords covid19
    Language English
    Publishing date 2021-07-19
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2021.07.15.21260543
    Database COVID19

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