Pittsburgh Influenza Prevention Project

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DESCRIPTION (provided by applicant): Pandemic influenza threatens to cause substantial disability, death, and societal disruption and to overwhelm health care systems in the United States and around the world. Non-pharmacological personal protection and behavioral changes may be the only means to combat the epidemic. In our computational modeling work (through the Models of Infectious Disease Agent Study network), we have shown the potential value of multiple targeted and layered non-pharmacological interventions in blunting the peak impact and slowing of a pandemic (Nature, in press). However, model policy outcomes were often dependent on specific parameter estimates, especially those relating to influenza transmission dynamics in schools and households. We propose a two year "Pittsburgh Influenza Prevention Project" with six tightly integrated specific aims: (1) Develop a public school-based early warning system in Pittsburgh to identify cases and early outbreaks of influenza; (2) Measure the spread of influenza from elementary school students to their households; (3) Quantitate the actual anti-contagion behaviors employed in households to prevent spread of influenza illness during flu season; (4) Re-create the epidemiological patterns observed in Specific Aims 1-3 in agent-based computational simulations; (5) Test a 'Home Health Hygiene' influenza control intervention in households experimentally and assess effectiveness; and (6) Collect and archive influenza specimens from school and household clusters for future molecular epidemiological studies. We have obtained agreement to collaborate from the Pittsburgh Public School System and we have assembled a multi-disciplinary team of epidemiologists, systems analysts, modelers, community and minority health workers, and virologists. Year one of the project will be a pilot project in a single school. We estimate that we will detect 200 influenza infections among students, that 100 of their families will participate in household studies, and that we will detect an additional 150 influenza infections among household contacts. In Year 2 of the project we will expand the study population eight-fold and carry out a controlled study of personal protective behavioral interventions. The activities described in this grant application will greatly improve our understanding of influenza transmission in community settings, and thereby improve the accuracy of computational modeling. This research will provide important advances in our ability intervene in future influenza pandemics.