The rapid spread of the Ebola virus has captured news headlines worldwide. Considered the worst health crisis of the 21st century, epidemiologists and health workers are scrambling to find ways to contain the West Africa outbreak.
With approximately 10,000 confirmed cases and a death toll of almost 4,900 and rising, time is of the essence. Health workers must have the ability to track trends in a timely and speedy manner, and it appears that Big Data has the potential to move fast enough to mitigate and even completely eradicate the Ebola scourge from spreading further.
What is Big Data
Big Data consists of large amount of data so broad that it includes anything that can be found online and via mobile devices. It covers data gleaned from financial data to tweets, blog posts, emails, videos, to text messages. Because the data is so vast, traditional software tools fall short in making any meaningful analysis, so it requires techniques and analytical tools specifically made for its use.
Health organizations usually rely on survey and census to collate meaningful data that will allow them to monitor the lifespan of a disease. Information has to be gathered from hospitals, schools, or clinics and not real time data, which makes it more challenging to identify outbreaks before they got out of hand. Big Data has the potential to change that.
Stopping an Epidemic
Harvard’s Healthmap is an example of such a system that uses Big Data techniques to detect public health threats. By mining data from news articles, blog posts, social media and other informal media, it is widely credited for its ability to flag the Ebola outbreak nine days before the World Health Organization issued its formal statement and first warning on March 19, 2014.
Big Data analysis was also employed in tracking the recent malaria outbreaks in Kenya and Namibia, while the spread of the Mexican swine flu virus was successfully monitored in 2009 using the same technology. Researchers and aid workers also relied on Big Data, particularly information from cellphone data records (CDR), to implement the best plan of action to deal with the 2010 Haiti cholera epidemic.
Cellphones and Big Data
Mobile phone records, specifically CDRs, have the biggest potential help contain the Ebola crisis. By using real-time information from CDRs, health workers have the ability to see where people are going and track population movement to make accurate conclusions as to where the next outbreak might likely occur. Having this information at hand is crucial in deciding where limited resources will be dispatched, and which areas need help the most. The most glaring challenge, however, is that many West Africans do not own a cellphone. Nevertheless, limited but accurate information is better than stale, outdated data.
The huge benefit that Big Data has had and its potential to fight the Ebola crisis is widely recognized by epidemiologists, health organizations, and the private sector. Proof of this can be seen from the multimillion donations made by Mark Zuckerberg and the Bill and Melinda Gates Foundation, to philanthropist Paul Allen (who pledged $100 Million).
Microsoft is allowing Ebola researchers to take advantage the cloud computing platform Azure for research and, hopefully, to find a cure. The IMF proposed to pour in $127 Million to aid countries in their fight against Ebola, and the EU has earmarked €24.4 million from their budget to fund Ebola research.
However the public sector has yet to catch up: too many public health infrastructures are underfunded, mobile phone companies are reluctant to provide CDR over privacy concerns, and decision makers need to properly coordinate with health workers in implementing fast solutions when it’s needed, as needed. The bureaucratic red tape need to be resolved, and once everyone works from the same page and see these benefits, the unlimited potential that Big Data can provide can be unlocked, and everyone benefits.