Search Here

When a disease outbreak occurs, scientists and healthcare professionals need information and data about the disease and the people and place affected by the disease in order to come up with possible solutions to the outbreak. However, the needed epidemiological data is scarce and slow to reach the scientists.

A recent study shows the potential of the use of the Internet and social media to get the needed the data and help in the forecast of disease outbreaks.

The study, published in the Journal of Infectious Diseases, used the data collected from the Internet and social media sites during the 2014-2015 Ebola epidemic in West Africa and the 2015 Middle East Respiratory Syndrome (MERS) outbreak in South Korea. According to the researchers, the data collected during the outbreaks in these countries helped in improving preparedness and response to the disease outbreaks.

The researchers point out that online reports are publicly available and released in real time. These Internet-based data are used to identify key features of the outbreak including information on exposure and transmission patterns.

In addition, data collected by the researchers during the Ebola and MERS outbreak is in good agreement with the official epidemiological data collected through traditional surveillance methods.

Furthermore, the data collected from the Internet and social media sites emphasize the importance of disease amplification in hospitals and funeral rites (in the case of West Africa) before the implementation of control interventions during the outbreak.

With these positive outcomes from internet-based data, researchers are suggesting the use of data collected from the Internet and social media sites as an alternative tool for the collection of epidemiology data especially in cases of epidemic emergencies.

The study recommends the use of internet-based data as reliable tools during epidemic outbreaks. In addition, researchers are looking into the improvement and development of internet-based approaches to study transmission dynamics.