Few public health events over the past decade have galvanized the attention of the American public like the outbreak of the H1N1 virus in 2009. Health officials scrambled to build models predicting how the disease might spread and to find measures to mitigate its impact.
A 2010 study published in the Proceedings of the National Academy of Sciences, “Role of Social Networks in Shaping Disease Transmission During a Community Outbreak of 2009 H1N1 Pandemic Influenza,” analyzed the spread of the flu in an elementary school in Pennsylvania. Researchers used seating charts, timetables, bus schedules, nurse logs and attendance records to model and diagnose trends in H1N1 transmission in a “real world” setting.
The study’s key findings include:
- While the transmission rate was five times higher among classmates than among children in different classrooms, sitting next to an infected child didn’t significantly increase a child’s risk of catching the disease.
- Children were three times more likely to transmit influenza to those of the same gender than those of the opposite gender, indicating that it spread through social networks.
- There was no statistically significant reduction in transmission once the school was closed. However, the researchers concede that this is likely a function of the timing of the school closure being too late in the epidemic cycle.
The authors state that the data could help inform public health decisions, such as “whether and when it would be appropriate to close a school, or whether it might be better to close individual classes or grades.”