Zika pandemic online trends, incidence and health risk communication: a time trend study

Adebayo, Gbenga; Neumark, Yehuda; Gesser‐Edelsburg, Anat; Ahmad, Wiessam Abu; Levine, Hagai

doi:10.1136/bmjgh-2017-000296

Cited by 26 publications

(17 citation statements)

References 34 publications

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“…These quarterly time series were first modeled as autoregressive integrated moving average (ARIMA) models to reveal any potential temporal characteristics such as linear trend, seasonality, or temporal autocorrelation [16]. The following equation:…”

Section: Methodsmentioning

confidence: 99%

“…Evidently, for many infectious disease epidemics, it has been demonstrated that Web-based discussion in social media can be an imperative indicator of the actual disease severity and help health officials to more accurately evaluate the time-sensitive epidemic situation when actual case counts are still being gathered and verified [13-15]. Time series analysis is a versatile and powerful modeling framework to link Web-based discussion and reveal the disease dynamics, as demonstrated by the extant research on various epidemics [16-18].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Chen¹,

Xu²,

Buchenberger³

et al. 2018

JMIR Public Health Surveill

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BackgroundSocial media have been increasingly adopted by health agencies to disseminate information, interact with the public, and understand public opinion. Among them, the Centers for Disease Control and Prevention (CDC) is one of the first US government health agencies to adopt social media during health emergencies and crisis. It had been active on Twitter during the 2016 Zika epidemic that caused 5168 domestic noncongenital cases in the United States.ObjectiveThe aim of this study was to quantify the temporal variabilities in CDC’s tweeting activities throughout the Zika epidemic, public engagement defined as retweeting and replying, and Zika case counts. It then compares the patterns of these 3 datasets to identify possible discrepancy among domestic Zika case counts, CDC’s response on Twitter, and public engagement in this topic.MethodsAll of the CDC-initiated tweets published in 2016 with corresponding retweets and replies were collected from 67 CDC–associated Twitter accounts. Both univariate and multivariate time series analyses were performed in each quarter of 2016 for domestic Zika case counts, CDC tweeting activities, and public engagement in the CDC-initiated tweets.ResultsCDC sent out >84.0% (5130/6104) of its Zika tweets in the first quarter of 2016 when Zika case counts were low in the 50 US states and territories (only 560/5168, 10.8% cases and 662/38,885, 1.70% cases, respectively). While Zika case counts increased dramatically in the second and third quarters, CDC efforts on Twitter substantially decreased. The time series of public engagement in the CDC-initiated tweets generally differed among quarters and from that of original CDC tweets based on autoregressive integrated moving average model results. Both original CDC tweets and public engagement had the highest mutual information with Zika case counts in the second quarter. Furthermore, public engagement in the original CDC tweets was substantially correlated with and preceded actual Zika case counts.ConclusionsConsiderable discrepancies existed among CDC’s original tweets regarding Zika, public engagement in these tweets, and actual Zika epidemic. The patterns of these discrepancies also varied between different quarters in 2016. CDC was much more active in the early warning of Zika, especially in the first quarter of 2016. Public engagement in CDC’s original tweets served as a more prominent predictor of actual Zika epidemic than the number of CDC’s original tweets later in the year.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Chen¹,

Xu²,

Buchenberger³

et al. 2018

JMIR Public Health Surveill

View full text Add to dashboard Cite

show abstract

“…This is because Zika shares the same vector and similar symptoms with Dengue, using "Zika fever" as a disease topic as the search query may likely include those searches that are not only Zika but also dengue or other similar symptoms. The search data from Google Trends has been previously used as a surveillance tool to indicate the public interest in a particular topic and predict the spread of the infectious disease [19][20][21].…”

Section: Design and Data Collectionmentioning

confidence: 99%

Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic

Lwin

Sheldenkar

et al. 2020

BMC Public Health

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Background: While existing studies have investigated the role of social media on health-related communication, little is known about the potential differences between different users groups on different social media platforms in responses to a health event. This study sets out to explore the online discourse of governmental authorities and the public in Singapore during the recent Zika pandemic in 2016. Methods: Social media data were extracted from Facebook and Twitter using retroactive keyword sourcing of the word "Zika" to search for posts and a location filter of "Singapore". Government posts, public posts, and replies to these original posts were included in the temporal and textual analysis. Results: Overall, Facebook contained more government and individual content whereas Twitter had more content from news media accounts. Though the relative volume of Zika content from different data sources paralleled the peaks and troughs of Zika activities across time, discourses from different data sources differed in their temporal patterns, such that the public discourse died down faster than the government discourse after the outbreak was declared. In addition, the content of discourses differed among data sources. While government discourse included factual information of the disease, public discourse contained more elements of care such as worry about the risks to pregnant women, and elements of community such as well-wishes to each other. Conclusions: Our study demonstrates the temporal and content differences between user groups and social media platforms in social media conversations during the Zika pandemic. It suggests that future research should examine the collective discourse of a health event by investigating social media discourses within varied sources rather than focusing on a singular social media platform and by one particular type of users.

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“…With their research assessing the content and timing of Zika‐related press releases during public health emergencies Adebayo, Neumark, Gesser‐Edelsburg, Abu Ahmad, and Levine () provide helpful insights for improving communications during future emergencies. Their recommendations include urging government officials to monitor “online search trends as an additional surveillance tool during a pandemic.” The authors also suggest the need to “tailor messages for subgroups of the population audience” (p. 10).…”

Section: The Principle Of Tethering Communication To the Science And mentioning

confidence: 99%

Chronicling the Risk and Risk Communication by Governmental Officials During the Zika Threat

Allen¹

2018

Risk Analysis

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The unique circumstances surrounding Zika, including the fact that it is both mosquito-borne and sexually transmissible, brought to the fore concerns about optimal ways to communicate risk in an environment characterized by rapidly evolving knowledge. The difficulty in doing so is magnified by the fact that science-based health messages from governmental agencies must be developed in an evidence-based, audience-participative, and collaborative manner. A recent reminder in JAMA asserted the importance of preparing now for future threats. Understanding how the knowledge and messaging about Zika changed across time should help public health officials prepare for such challenges.

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Zika pandemic online trends, incidence and health risk communication: a time trend study

Cited by 26 publications

References 34 publications

Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic

Chronicling the Risk and Risk Communication by Governmental Officials During the Zika Threat

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