2 datasets found
  1. D

    Duke RDS^2: Respondent-driven sampling for respiratory disease surveillance,...

    • research.repository.duke.edu
    Updated Mar 25, 2024
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    Welsh, Whitney; Pasquale, Dana K.; Moody, James; Bentley-Edwards, Keisha L.; Olson, Andrew (2024). Duke RDS^2: Respondent-driven sampling for respiratory disease surveillance, the snowball sampling study (social mixing and referrals dataset) [Dataset]. http://doi.org/10.7924/r43f4zj2q
    Explore at:
    Dataset updated
    Mar 25, 2024
    Dataset provided by
    Duke Research Data Repository
    Authors
    Welsh, Whitney; Pasquale, Dana K.; Moody, James; Bentley-Edwards, Keisha L.; Olson, Andrew
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Dec 2020 - Jul 2022
    Dataset funded by
    Eunice Kennedy Shriver National Institute of Child Health and Human Development
    National Institutes of Health
    National Science Foundation
    Centers for Disease Control and Prevention
    Description

    Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n=384 index cases + n=2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized. The project described was supported by Grant/Cooperative Agreement Number 75D30120C09551 made to Duke University from the Centers for Disease Control and Prevention (CDC), US Department of Health and Human Services (HHS), awarded to D.K.P., J.M., and K. B.-E. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC or US HHS. D.K.P. and J.M. were also supported by the National Institutes of Health (NIH) Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (Grant Awards R25HD079352 (awarded to J.M.), R21HD104431 (awarded to J.M. and D.K.P.), and R21HD101268 (awarded to J.M. and D.K.P)) and National Science Foundation (Grant Award SES-2029790 (awarded to J.M. and D.K.P)). The contents are solely the responsibility of the authors and do not necessarily represent the official views of NIH or NSF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ... [Read More]

  2. o

    Data from: Racial Disparities in U.S. Climate Migration

    • openicpsr.org
    Updated Oct 24, 2023
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    Gabriela Nagle Alverio; David Leblang (2023). Racial Disparities in U.S. Climate Migration [Dataset]. http://doi.org/10.3886/E194684V1
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    Dataset updated
    Oct 24, 2023
    Dataset provided by
    Duke University
    University of Virginia
    Authors
    Gabriela Nagle Alverio; David Leblang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Floods are increasingly frequent and severe due to climate change, thereby impacting migration within the United States. Considering that Black and Brown populations are disproportionately exposed to floods, less likely to receive disaster-related government funds, and vulnerable during subsequent displacement, an examination of differences in migration patterns across racial/ethnic groups is critical. The prevailing conjecture is that after floods, Black and Brown populations will migrate while White ones remain in place. We test this hypothesis by examining the effect of floods on migration across all U.S. county-pairs between 2006-2016 and find that this hypothesis is incorrect: generally, after floods Black populations remain in place and White populations migrate. However, this pattern reverses when the Federal Emergency Management Agency provides financial support. Notably, migration by Hispanic and Asian populations is not significantly affected by floods. These results provide the first evidence of racial disparities in climate migration.

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    Learn how you can add new datasets to our index.

Share
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Click to copy link
Link copied
Close
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Welsh, Whitney; Pasquale, Dana K.; Moody, James; Bentley-Edwards, Keisha L.; Olson, Andrew (2024). Duke RDS^2: Respondent-driven sampling for respiratory disease surveillance, the snowball sampling study (social mixing and referrals dataset) [Dataset]. http://doi.org/10.7924/r43f4zj2q

Duke RDS^2: Respondent-driven sampling for respiratory disease surveillance, the snowball sampling study (social mixing and referrals dataset)

Explore at:
Dataset updated
Mar 25, 2024
Dataset provided by
Duke Research Data Repository
Authors
Welsh, Whitney; Pasquale, Dana K.; Moody, James; Bentley-Edwards, Keisha L.; Olson, Andrew
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Time period covered
Dec 2020 - Jul 2022
Dataset funded by
Eunice Kennedy Shriver National Institute of Child Health and Human Development
National Institutes of Health
National Science Foundation
Centers for Disease Control and Prevention
Description

Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n=384 index cases + n=2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized. The project described was supported by Grant/Cooperative Agreement Number 75D30120C09551 made to Duke University from the Centers for Disease Control and Prevention (CDC), US Department of Health and Human Services (HHS), awarded to D.K.P., J.M., and K. B.-E. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC or US HHS. D.K.P. and J.M. were also supported by the National Institutes of Health (NIH) Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (Grant Awards R25HD079352 (awarded to J.M.), R21HD104431 (awarded to J.M. and D.K.P.), and R21HD101268 (awarded to J.M. and D.K.P)) and National Science Foundation (Grant Award SES-2029790 (awarded to J.M. and D.K.P)). The contents are solely the responsibility of the authors and do not necessarily represent the official views of NIH or NSF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ... [Read More]

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