Pittsburgh Influenza Prevention Project

描述(申请人提供)：大流行性流感有可能导致严重的残疾、死亡和社会混乱，并使美国和世界各地的卫生保健系统不堪重负。非药理学的个人保护和行为改变可能是抗击疫情的唯一手段。在我们的计算建模工作中(通过传染病代理研究网络的模型)，我们已经展示了多个有针对性和分层的非药物干预在钝化大流行的高峰影响和减缓大流行方面的潜在价值(《自然》，正在出版中)。 然而，示范政策成果往往取决于具体的参数估计，特别是与学校和家庭的流感传播动态有关的参数估计。我们提出了一个为期两年的“匹兹堡流感预防项目”，有六个紧密结合的具体目标：(1)在匹兹堡建立一个以公立学校为基础的早期流感预警系统，以识别流感病例和早期爆发；(2)测量流感从小学生到家庭的传播；(3)量化家庭在流感季节为防止流感疾病传播而采取的实际抗感染行为；(4)在基于代理的计算模拟中重建在特定目标1-3中观察到的流行病学模式；(5)在家庭中通过实验测试‘家庭健康’流感控制干预措施并评估有效性；以及(6)从学校和家庭群中收集和存档流感样本，以供未来的分子流行病学研究。我们已经从匹兹堡公立学校系统获得了合作协议，我们已经组建了一个由流行病学家、系统分析师、建模人员、社区和少数族裔卫生工作者以及病毒学家组成的多学科团队。该项目的第一年将是一所学校的试点项目。我们估计，我们将在学生中检测到200例流感感染，他们中的100名家庭将参加家庭研究，我们将在家庭接触者中检测到另外150例流感感染。在项目的第二年，我们将把研究人群扩大八倍，并开展一项关于个人防护行为干预的对照研究。这项赠款申请中描述的活动将极大地提高我们对社区环境中流感传播的理解，从而提高计算模型的准确性。这项研究将为我们干预未来流感大流行的能力提供重要进展。

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.