TY  - JOUR
AU  - Chen, Shi
AU  - Xu, Qian
AU  - Buchenberger, John
AU  - Bagavathi, Arunkumar
AU  - Fair, Gabriel
AU  - Shaikh, Samira
AU  - Krishnan, Siddharth
PY  - 2018
DA  - 2018/11/22
TI  - Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic
JO  - JMIR Public Health Surveill
SP  - e10827
VL  - 4
IS  - 4
KW  - Centers for Disease Control and Prevention
KW  - public engagement
KW  - Twitter
KW  - time series analysis
KW  - Zika epidemic
KW  - social media
KW  - infodemiology
KW  - infoveillance
AB  - Background: Social 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. Objective: The 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. Methods: All 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. Results: CDC 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. Conclusions: Considerable 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. 
SN  - 2369-2960
UR  - http://publichealth.jmir.org/2018/4/e10827/
UR  - https://doi.org/10.2196/10827
UR  - http://www.ncbi.nlm.nih.gov/pubmed/30467106
DO  - 10.2196/10827
ID  - info:doi/10.2196/10827
ER  -