Norovirus, Networks, and Big-Data

Another norvirus outbreak has been in the news related to a group of cases on a cruise ship.  With over  700 passengers and crew falling ill, it is one of the largest outbreaks on a cruise ship ever reported.  Norovirus is a highly contagious member of the Caliciviridae family, and contains multiple genotypes and subtypes.  Small mutations in the norovirus genome lead to new strains, similar to the phenomenon of antigenic shift in influenza viruses.  Larger mutations can lead to pandemic strains when the prevailing population immunity to older strains is no longer effective against the new strain.  The United States is in the midst of the norovirus season, with a new strain being responsible for most cases.

How is Big Data Science revolutionizing the tracking and prediction of norovirus outbreaks?  The US Center for Disease Control now tracks norovirus outbreaks through a combination of traditional outbreak surveillance as reported by public health departments around the US and confirmed by molecular testing of specimens from symptomatic individuals. But, an alternative Big Data real-time social media monitoring approach is being tested in the UK by the Food Standards Agency.  Tweet the hashtag #Barf in London, and your tweet will be added to the FSA statistics, along with the geographic location.  About 50% of gastrointestinal intestinal illnesses in the US and UK are caused by norovirus, so tweets and Google Searches about stomach cramps, vomiting and diarrhea have a high likelihood of being norovirus related!   FSA researchers found an upswing in hashtags describing GI symptoms occurred 3-4 weeks before an outbreak was identified by traditional laboratory surveillance.

#Vomit:  Predicting Norovirus Outbreaks with Twitter

So how can Big Data Science contribute to solutions?  Recognizing outbreaks in real time using Big Data analytics is a start.  Taming data velocity and volume are key here.  Early recognition can lead to containment and public health strategies can limit the outbreak.  But potential solutions go beyond larger public health responses.  One of the major ways individuals can prevent the spread of the virus, and themselves from being infected, is simple good hygiene such as had washing.  Norovirus outbreaks occur more frequently in places where people are living together and have risk factors such as being elderly, immunosuppressed, or very young.  Day care centers, nursing homes and hospitals are the key areas.  In a novel application of Big Data Science real-time analytics, IBM has developed a method of tracking handwashing among healthcare workers after each patient contact.  An RFID tag carried by the worker, couples with sensors which record entry into the room, exit, and use of a hand sanitizer dispenser, have lead to pronounced increases in had-washing.  The data is still out on whether this will reduce infectious outbreaks or their spread, but if the promise bears out, look for such systems in high risk areas such as institutional kitchens, day care centers and other areas.  It does seem a bit Big Brother-ish, which is a topic for my next post…

For now….wash your hands, tweet your symptoms, and stay healthy!