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  • 1
    In: American Journal of Public Health, American Public Health Association, Vol. 110, No. S3 ( 2020-10), p. S319-S325
    Abstract: Objectives. To examine the role that bots play in spreading vaccine information on Twitter by measuring exposure and engagement among active users from the United States. Methods. We sampled 53 188 US Twitter users and examined who they follow and retweet across 21 million vaccine-related tweets (January 12, 2017–December 3, 2019). Our analyses compared bots to human-operated accounts and vaccine-critical tweets to other vaccine-related tweets. Results. The median number of potential exposures to vaccine-related tweets per user was 757 (interquartile range [IQR] = 168–4435), of which 27 (IQR = 6–169) were vaccine critical, and 0 (IQR = 0–12) originated from bots. We found that 36.7% of users retweeted vaccine-related content, 4.5% retweeted vaccine-critical content, and 2.1% retweeted vaccine content from bots. Compared with other users, the 5.8% for whom vaccine-critical tweets made up most exposures more often retweeted vaccine content (62.9%; odds ratio [OR]  = 2.9; 95% confidence interval [CI] = 2.7, 3.1), vaccine-critical content (35.0%; OR = 19.0; 95% CI = 17.3, 20.9), and bots (8.8%; OR = 5.4; 95% CI = 4.7, 6.3). Conclusions. A small proportion of vaccine-critical information that reaches active US Twitter users comes from bots.
    Type of Medium: Online Resource
    ISSN: 0090-0036 , 1541-0048
    RVK:
    Language: English
    Publisher: American Public Health Association
    Publication Date: 2020
    detail.hit.zdb_id: 2054583-6
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  • 2
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 2023
    In:  Epidemiology and Infection Vol. 151 ( 2023)
    In: Epidemiology and Infection, Cambridge University Press (CUP), Vol. 151 ( 2023)
    Abstract: Surveillance is a key public health function to enable early detection of infectious disease events and inform public health action. Data linkage may improve the depth of data for response to infectious disease events. This study aimed to describe the uses of linked data for infectious disease events. A systematic review was conducted using Pubmed, CINAHL and Web of Science. Studies were included if they used data linkage for an acute infectious disease event (e.g. outbreak of disease). We summarised the event, study aims and designs; data sets; linkage methods; outcomes reported; and benefits and limitations. Fifty-four studies were included. Uses of linkage for infectious disease events included assessment of severity of disease and risk factors; improved case finding and contact tracing; and vaccine uptake, safety and effectiveness. The ability to conduct larger scale population level studies was identified as a benefit, in particular for rarer exposures, risk factors or outcomes. Limitations included timeliness, data quality and inability to collect additional variables. This review demonstrated multiple uses of data linkage for infectious disease events. As infectious disease events occur without warning, there is a need to establish pre-approved protocols and the infrastructure for data-linkage to enhance information available during an event.
    Type of Medium: Online Resource
    ISSN: 0950-2688 , 1469-4409
    RVK:
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1470211-3
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