Strains of seasonal influenza behave slightly differently season to season and strain to strain. The differences are revealing. The rate of transmission of the 1918 pandemic, which killed 40 million people, closely mirrors the data from the 2009 H1N1 pandemic. The two strains are, in fact, closely related.
At the Centers for Disease Control and Prevention (CDC), epidemiologists study the patterns of flu data from the current season against historic data. The comparison helps them make informed decisions about how to respond to the virus: what kind of vaccine to make, how to make it, and how and where to distribute it. As data sets improve, scientists will be able to better predict how future strains of seasonal influenza will spread.
Double dips: Seasonal influenza usually arrives in two waves: a small peak in mid-December followed by a doubling in the rate of transmission that spikes in early February. The first wave can be telling—high incident rates early in the season hint at particularly contagious strains. Data from 2007 versus 2008 seasons [in blue] shows an improved response.
Peak season: Although influenza generally reaches its highest prevalence in February, the 2009 H1N1 pandemic caused a spike in mid-October. By midwinter, thanks to heavy distribution of vaccine and an already high exposure rate, the flu was in rapid decline. In 2003, the CDC synthesized a vaccine for an older strain that ended up being less virulent than another (in a given season, there are about three flu strains), leading to more cases.
Breaking out the data: Over in that sidebar on the right, the lighter colors display data from the Epidemiology and Prevention Branch of the Influenza Division of the CDC, which aggregates its data from 3,000 doctors’ offices, 140 labs, 3,000 outpatient health-care providers, vital-statistics offices in 122 cities, and epidemiologists at health departments in every state to come up with a percentage of flu-related doctor and emergency-room visits every week. Google Flu Trends [the darker shades] computes the rate of infection in a population by tracking search terms such as “sore throat” and “cold chills.
Story by Katie Peek and Ryan Bradley, illustration by Pitch Interactive
Check out more from our Future of Medicine issue here.