The H1N1 outbreak in the spring of 2009 in NYC originated in a school in Queens before spreading to others nearby. Active surveillance established epidemiological links between students at the school and new cases at other schools through household connections. Such findings suggest that spatial cluster detection methods should be useful for identifying new influenza outbreaks in school-aged children. As school-to-school transmission should occur between those with high levels of interaction, existing cluster detection methods can be improved by accurately characterizing these links. We establish a prospective surveillance system that detects outbreaks in NYC schools using a flexible spatial scan statistic (FlexScan), with clusters identified on a network constructed from student interactions.
To improve cluster detection of influenza-like illness within New York City (NYC) public schools using school health and absenteeism data by characterizing the degree to which schools interact.