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Table 3 Chinese social media’s reaction to the first WHO report of MERS-CoV outbreak

From: Chinese social media reaction to the MERS-CoV and avian influenza A(H7N9) outbreaks

  Baseline mean (s.d.) (time period*) Number per million Weibo posts that contain a given keyword on a given day (number of s.d. away from the mean)
   Sep 22 Sep 23 Sep 24 Sep 25 Sep 26 Sep 27 Sep 28 Sep 29 Sep 30
非典 (Feidian, shortened for atypical pneumonia) 46.95 (s.d., 20.62) (Apr 1 - Jul 1) 16.3 (−1.44) 15.6 (−1.47) 32.7 (−0.64) 40.3 (−0.27) 36.5 (−0.46) 66.2 (0.98) 49.4 (0.17) 39.0 (−0.34) 37.2 (−0.42)
沙士 (phonetic translation of SARS) 3.97(s.d., 3.84) (May 1 - Sep 1) 2.7 (−0.33) 20.8 (4.39) 14.0 (2.62) 87.4 (21.75) 58.3 (14.17) 66.2 (16.22) 15.7 (3.06) 0 (−1.04) 8.0 (1.04)
SARS 7.81 (s.d., 6.59) (Apr 1 - Jul 1) 2.7 (−0.77) 5.2 (−0.40) 32.7 (3.78) 210.7 (30.80) 119.1 (16.89) 75.3 (10.25) 24.7 (2.56) 33.4 (3.88) 13.3 (0.83)
冠状病毒 (coronavirus) 0.33 (s.d., 22.74) (Jan 1 - Sep 1) 0 (−0.01) 0 (−0.01) 0 (−0.01) 51.6 (2.25) 63.2 (2.76) 70.8 (3.10) 65.1 (2.85) 306.3 (13.45) 125.0 (5.48)
  1. Note: The term "Middle East Respiratory Syndrome" had not been invented in 2012. Most users of Weibo would use terminology related to SARS to refer to the novel coronavirus that was renamed Middle East Respiratory Syndrome-Coronavirus (MERS-CoV) in 2013. *We chose a different time period as the baseline to avoid outliers related to other events in the news that would bias the data. SARS, Severe Acute Respiratory Syndrome; s.d., standard deviation.
  2. Baseline and peak values are presented as number per million Weibo posts that contain keywords related to MERS-CoV, namely keywords of SARS and coronavirus in our sample of about 50,000 users with ≥10,000 followers, in 2012. This table shows that three of the four keywords were sensitive to the news of the novel coronavirus causing a disease similar to SARS.