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  1. Article ; Online: Author Correction: Measuring sensitivity to social distancing behavior during the COVID-19 pandemic.

    Kontokosta, Constantine E / Hong, Boyeong / Bonczak, Bartosz J

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 2192

    Language English
    Publishing date 2023-02-07
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-29283-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Author Correction

    Constantine E. Kontokosta / Boyeong Hong / Bartosz J. Bonczak

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    Measuring sensitivity to social distancing behavior during the COVID-19 pandemic

    2023  Volume 1

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Measuring sensitivity to social distancing behavior during the COVID-19 pandemic.

    Kontokosta, Constantine E / Hong, Boyeong / Bonczak, Bartosz J

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 16350

    Abstract: Social distancing remains an effective nonpharmaceutical behavioral interventions to limit the spread of COVID-19 and other airborne diseases, but monitoring and enforcement create nontrivial challenges. Several jurisdictions have turned to "311" ... ...

    Abstract Social distancing remains an effective nonpharmaceutical behavioral interventions to limit the spread of COVID-19 and other airborne diseases, but monitoring and enforcement create nontrivial challenges. Several jurisdictions have turned to "311" resident complaint platforms to engage the public in reporting social distancing non-compliance, but differences in sensitivity to social distancing behaviors can lead to a mis-allocation of resources and increased health risks for vulnerable communities. Using hourly visit data to designated establishments and more than 71,000 social distancing complaints in New York City during the first wave of the pandemic, we develop a method, derived from the Weber-Fechner law, to quantify neighborhood sensitivity and assess how tolerance to social distancing infractions and complaint reporting behaviors vary with neighborhood characteristics. We find that sensitivity to non-compliance is lower in minority and low-income neighborhoods, as well as in lower density areas, resulting in fewer reported complaints than expected given measured levels of overcrowding.
    MeSH term(s) COVID-19/epidemiology ; COVID-19/prevention & control ; Humans ; Minority Groups ; New York City/epidemiology ; Pandemics/prevention & control ; Physical Distancing
    Language English
    Publishing date 2022-09-29
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-20198-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Measuring inequality in community resilience to natural disasters using large-scale mobility data

    Boyeong Hong / Bartosz J. Bonczak / Arpit Gupta / Constantine E. Kontokosta

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 9

    Abstract: Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes ... ...

    Abstract Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes neighborhood disparities in resilience capacity and recovery.
    Keywords Science ; Q
    Language English
    Publishing date 2021-03-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Measuring inequality in community resilience to natural disasters using large-scale mobility data.

    Hong, Boyeong / Bonczak, Bartosz J / Gupta, Arpit / Kontokosta, Constantine E

    Nature communications

    2021  Volume 12, Issue 1, Page(s) 1870

    Abstract: While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, ... ...

    Abstract While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods.
    Language English
    Publishing date 2021-03-25
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-021-22160-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: A data-driven framework for abnormally high building energy demand detection with weather and block morphology at community scale

    Lin, Qi / Liu, Ke / Hong, Boyeong / Xu, Xiaodong / Chen, Jiayu / Wang, Wei

    Elsevier Ltd Journal of cleaner production. 2022 June 20, v. 354

    2022  

    Abstract: Buildings are one of the most important energy use sectors in cities, and forecasting the abnormal increase in building energy demand in certain climatic conditions is necessary to adjust building energy operations and implement energy policy. ... ...

    Abstract Buildings are one of the most important energy use sectors in cities, and forecasting the abnormal increase in building energy demand in certain climatic conditions is necessary to adjust building energy operations and implement energy policy. Accordingly, this research proposes a data-driven abnormally high energy demand detection framework in urban buildings based on their design parameters and local weather data, with the support of machine learning techniques. In this study, 71 public buildings with energy records in Jianhu city, Jiangsu province, China, were selected to abstract urban morphologies at community scale. The weather profile for the city was obtained from year 2015–2018 to create weather characteristics. Three machine learning algorithms—random forest, support vector machine, and artificial neural network—were applied to identify the months of abnormally high electricity consumption in different building types. This framework also explores key variables in the data and provides the basis for a system that prioritizes the acquisition of variables when complete data is unavailable. The results show that, with complete data, the accuracy score of the system in this study can reach 0.854 with the SVM algorithm, and the model returned an accuracy of 0.865 with the RF model after the key variable selection. Based on those results, the framework in this study can generate preemptive warnings for months with an expected abnormally high energy consumption in target buildings as a prerequisite of energy policy.
    Keywords electric energy consumption ; energy ; energy policy ; forests ; meteorological data ; models ; support vector machines ; China
    Language English
    Dates of publication 2022-0620
    Publishing place Elsevier Ltd
    Document type Article
    ISSN 0959-6526
    DOI 10.1016/j.jclepro.2022.131602
    Database NAL-Catalogue (AGRICOLA)

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  7. Article ; Online: Exposure density and neighborhood disparities in COVID-19 infection risk.

    Hong, Boyeong / Bonczak, Bartosz J / Gupta, Arpit / Thorpe, Lorna E / Kontokosta, Constantine E

    Proceedings of the National Academy of Sciences of the United States of America

    2021  Volume 118, Issue 13

    Abstract: Although there is increasing awareness of disparities in COVID-19 infection risk among vulnerable communities, the effect of behavioral interventions at the scale of individual neighborhoods has not been fully studied. We develop a method to quantify ... ...

    Abstract Although there is increasing awareness of disparities in COVID-19 infection risk among vulnerable communities, the effect of behavioral interventions at the scale of individual neighborhoods has not been fully studied. We develop a method to quantify neighborhood activity behaviors at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social-distancing policies vary with socioeconomic and demographic characteristics. We define
    MeSH term(s) Built Environment ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; Geographic Information Systems ; Health Status Disparities ; Humans ; New York City/epidemiology ; Physical Distancing ; Residence Characteristics/statistics & numerical data ; Risk Factors ; SARS-CoV-2 ; Socioeconomic Factors ; Spatio-Temporal Analysis
    Language English
    Publishing date 2021-03-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.2021258118
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1148: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article: Exposure Density and Neighborhood Disparities in COVID-19 Infection Risk: Using Large-scale Geolocation Data to Understand Burdens on Vulnerable Communities

    Hong, Boyeong / Bonczak, Bartosz / Gupta, Arpit / Thorpe, Lorna / Kontokosta, Constantine E.

    Abstract: This study develops a new method to quantify neighborhood activity levels at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social distancing policies vary with socioeconomic and demographic ... ...

    Abstract This study develops a new method to quantify neighborhood activity levels at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social distancing policies vary with socioeconomic and demographic characteristics. We define exposure density as a measure of both the localized volume of activity in a defined area and the proportion of activity occurring in non-residential and outdoor land uses. We utilize this approach to capture inflows/outflows of people as a result of the pandemic and changes in mobility behavior for those that remain. First, we develop a generalizable method for assessing neighborhood activity levels by land use type using smartphone geolocation data over a three-month period covering more than 12 million unique users within the Greater New York area. Second, we measure and analyze disparities in community social distancing by identifying patterns in neighborhood activity levels and characteristics before and after the stay-at-home order. Finally, we evaluate the effect of social distancing in neighborhoods on COVID-19 infection rates and outcomes associated with localized demographic, socioeconomic, and infrastructure characteristics in order to identify disparities in health outcomes related to exposure risk. Our findings provide insight into the timely evaluation of the effectiveness of social distancing for individual neighborhoods and support a more equitable allocation of resources to support vulnerable and at-risk communities. Our findings demonstrate distinct patterns of activity pre- and post-COVID across neighborhoods. The variation in exposure density has a direct and measurable impact on the risk of infection.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  9. Book ; Online: Exposure Density and Neighborhood Disparities in COVID-19 Infection Risk

    Hong, Boyeong / Bonczak, Bartosz / Gupta, Arpit / Thorpe, Lorna / Kontokosta, Constantine E.

    Using Large-scale Geolocation Data to Understand Burdens on Vulnerable Communities

    2020  

    Abstract: This study develops a new method to quantify neighborhood activity levels at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social distancing policies vary with socioeconomic and demographic ... ...

    Abstract This study develops a new method to quantify neighborhood activity levels at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social distancing policies vary with socioeconomic and demographic characteristics. We define exposure density as a measure of both the localized volume of activity in a defined area and the proportion of activity occurring in non-residential and outdoor land uses. We utilize this approach to capture inflows/outflows of people as a result of the pandemic and changes in mobility behavior for those that remain. First, we develop a generalizable method for assessing neighborhood activity levels by land use type using smartphone geolocation data over a three-month period covering more than 12 million unique users within the Greater New York area. Second, we measure and analyze disparities in community social distancing by identifying patterns in neighborhood activity levels and characteristics before and after the stay-at-home order. Finally, we evaluate the effect of social distancing in neighborhoods on COVID-19 infection rates and outcomes associated with localized demographic, socioeconomic, and infrastructure characteristics in order to identify disparities in health outcomes related to exposure risk. Our findings provide insight into the timely evaluation of the effectiveness of social distancing for individual neighborhoods and support a more equitable allocation of resources to support vulnerable and at-risk communities. Our findings demonstrate distinct patterns of activity pre- and post-COVID across neighborhoods. The variation in exposure density has a direct and measurable impact on the risk of infection.
    Keywords Computer Science - Computers and Society ; Computer Science - Social and Information Networks ; Statistics - Applications ; covid19
    Subject code 910
    Publishing date 2020-08-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: The novel chicken interleukin 26 protein is overexpressed in T cells and induces proinflammatory cytokines.

    Truong, Anh Duc / Park, Boyeong / Ban, Jihye / Hong, Yeong Ho

    Veterinary research

    2016  Volume 47, Issue 1, Page(s) 65

    Abstract: In the present study, we describe the cloning and functional characterization of chicken interleukin 26 (ChIL-26). ChIL-26, a member of the IL-10 cytokine family, induces the production of proinflammatory cytokines by T cells. The ChIL-26 cDNA encodes an ...

    Abstract In the present study, we describe the cloning and functional characterization of chicken interleukin 26 (ChIL-26). ChIL-26, a member of the IL-10 cytokine family, induces the production of proinflammatory cytokines by T cells. The ChIL-26 cDNA encodes an 82-amino-acid protein whose amino acid sequence has 22.63, 46.31 and 43.15% homology with human IL-26, pig IL-26 and canary IL-26, respectively. ChIL-26 signals through a heterodimeric receptor complex composed of the IL-20R1 and IL-10R2 chains, which are expressed primarily in the CU91 T cell line as well as CD4(+) and CD8(+) T cells. Recombinant ChIL-26 protein induced Th1 cytokines (IL-16 and IFN-γ), Th2 cytokines (IL-4, IL-6 and IL-10), Th17 cytokines (IL-17A, IL-17D, and IL-17F), and chemokine transcripts (mainly CCL3, CCL4, CCL5, CCL20 and CXCL13) in the CU91 T cell line and in CD4(+) and CD8(+) T cells, however IL-18 was not expressed in the CU91 T cell line. Taken together, the data demonstrates that T cells express the functional ChIL-26 receptor complex and that ChIL-26 modulates T cell proliferation and proinflammatory gene expression. To the best of our knowledge, this is the first report of cloned ChIL-26. We evaluated its functional roles, particularly in the pathogenic costimulation of T cells, which may be significantly associated with the induction of cytokines.
    MeSH term(s) Animals ; Blotting, Western/veterinary ; Canaries/genetics ; Canaries/immunology ; Chickens/immunology ; Chickens/metabolism ; Cloning, Molecular ; Cytokines/metabolism ; Gene Expression Regulation/genetics ; Gene Expression Regulation/physiology ; Humans ; Interleukins/genetics ; Interleukins/physiology ; Real-Time Polymerase Chain Reaction/veterinary ; Sequence Homology ; Swine/genetics ; Swine/immunology ; T-Lymphocytes/immunology ; T-Lymphocytes/metabolism
    Chemical Substances Cytokines ; IL26 protein, human ; Interleukins
    Language English
    Publishing date 2016-06-16
    Publishing country England
    Document type Journal Article
    ZDB-ID 1146298-x
    ISSN 1297-9716 ; 0928-4249
    ISSN (online) 1297-9716
    ISSN 0928-4249
    DOI 10.1186/s13567-016-0342-0
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    Zs.B 1313: Show issues Location:
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