Social Media Helps Forecast Outbreak Transmission Patterns

National Institutes of Health tracked and analyzed reports from public health authorities and reputable media outlets posted via social media or their websites during the 2014-2015 Ebola epidemic in West Africa and the 2015 Middle East Respiratory Syndrome (MERS) outbreak in South Korea, in order to study and collect data on the viruses' exposure patterns and transmission chains, and to test the reliability of alternative data streams.

The researchers found they were able to use internet reports describing Ebola cases in the three hardest hit countries (Guinea, Sierra Leone, and Liberia) to provide detailed accounts of epidemiological clusters, particularly useful to characterize time trends. They also found that exposure patterns based on the internet reports aligned with those derived from epidemiological surveillance data on MERS and Ebola, underscoring the importance of disease amplification in hospitals and during funeral rituals prior to the implementation of control interventions. The study was published in the December 2016 supplemental issue of The Journal of Infectious Diseases.

“Mathematical models forecasting disease transmission are often used to guide public health control strategies, but they can be difficult to formulate during the early stages of an outbreak when accurate data are scarce,” concluded lead author GSU associate professor of epidemiology and biostatistics Gerardo Chowell, PhD, and colleagues. “In the absence of detailed epidemiological information rapidly available from traditional surveillance systems, alternative data streams are worth exploring to gain a reliable understanding of disease dynamics in the early stages of an outbreak.”

“Our study offers proof of concept that publicly available online reports released in real-time by ministries of health, local surveillance systems, the World Health Organization, and authoritative media outlets are useful to identify key information on exposure and transmission patterns during epidemic emergencies,” added Dr. Chowell. “Our Internet-based findings on exposure patterns are in good agreement with those derived from traditional epidemiological surveillance data, which can be available after considerable delays.”