Purpose

We sought to determine whether big data from social media might reveal seasonal trends of conjunctivitis, most forms of which are nonreportable.

Methods

Social media posts (from Twitter, and from online forums and blogs) were classified by age and by conjunctivitis type (allergic or infectious) using Boolean and machine learning methods. Based on spline smoothing, we estimated the circular mean occurrence time (a measure of central tendency for occurrence) and the circular variance (a measure of uniformity of occurrence throughout the year, providing an index of seasonality). Clinical records from a large tertiary care provider were analyzed in a similar way for comparison.

Results

Social media posts machine-coded as being related to infectious conjunctivitis showed similar times of occurrence and degree of seasonality to clinical infectious cases, and likewise for machine-coded allergic conjunctivitis posts compared to clinical allergic cases. Allergic conjunctivitis showed a distinctively different seasonal pattern than infectious conjunctivitis, with a mean occurrence time later in the spring. Infectious conjunctivitis for children showed markedly greater seasonality than for adults, though the occurrence times were similar; no such difference for allergic conjunctivitis was seen.

Conclusions

Social media posts broadly track the seasonal occurrence of allergic and infectious conjunctivitis, and may be a useful supplement for epidemiologic monitoring.

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.