Pandemic preparedness in schools: A community based approach for sentinel surveillance

项目摘要 COVID-19大流行促使各国政府实施一系列公共卫生措施，包括 关闭学校，以减缓SARS-CoV-2的传播。然而，学校传播SARS冠状病毒的作用- 2、需要哪些缓解水平和测试政策，以及学校关闭的价值 有争议的问题。亲自学校关闭或隔离政策，阻止学生在学校 可能对儿童的发展产生直接和长期的负面影响。在纽约市， 由于COVID-19和从基于课堂的过渡，学生水平的学习损失的程度 平均125（69%）和212（118%）天的阅读和数学，分别相对于一个 典型的180天学年。在整个美国，教育程度的降低估计会转化为 终生收入工资损失百分之四到五。因此，开放学校进行面对面的学习是一种 这是重新开放经济和促进学生发展和成功的重要一步;然而， 随之而来的是接触网络和传播机会增加的危险。为了评估这种权衡， 以及增加传播的可能性，我们将建立模型， 监测数据沿着社区一级的检测数据、疫苗接种数据、免疫学和血清学数据， 除了学校环境的建筑环境指标之外，还在学生和教职员工中制定了指标。这些 模型将使我们能够确定社区水平的传播率和测试阳性率之间的关联 （目标1），建立流行病传播模式，确定如何 以成本效益高的方式收集哨点学校监测数据（目标2），并确定政策触发点以进行预测 何时应在学校实施干预措施以预防疾病传播（目标3）。虽然我 必要的工程背景和开发传染病模型的经验，额外的培训 将最大限度地提高拟议项目的成功，并促进一个强大的独立研究计划。到 为了实现这些目标，我将获得生物科学和公共卫生方面的额外培训，特别是 社区参与、免疫学、病毒学和流行病学。我将通过教学来培养这些技能 培训，独立研究，并从这些领域的专家指导：博士。麦达Galvez，雷切尔Vreeman， Jeffrey Shaman Andrea Graham Nicole Bouvier和Chris Gennings在这次培训结束后，我将 在全面研究未来呼吸道疾病传播的影响方面具有独特的地位 research.此外，我将在未来使用所获得的知识和开发的疾病传播模型 这是我朝着最佳设计传染性疾病的长期目标迈出的关键一步。 疾病监测网络，以减少疾病的传播和改善社区的健康。

PROJECT SUMMARY The COVID-19 pandemic prompted governments to implement a range of public health measures, including school closures, to slow the spread of SARS-CoV-2. However, the role of in-school transmission of SARS-CoV- 2, what mitigation levels and testing policies are needed, and the value of school closures have been contentious issues. In-person school closures or quarantine policies that prevent students from being in school can have immediate and long-lasting negative impacts on child development. In New York City, the calculated magnitude of student-level learning losses due to COVID-19 and the transition away from classroom-based instruction was on average 125 (69%) and 212 (118%) days of reading and math, respectively, relative to a typical 180-day school year. Across the United States, reduced educational attainment is estimated to translate into a loss of four to five percent of lifetime earning wages. Thus, opening schools to in-person learning is an important step in re-opening the economy and promoting development and success of students; however, it comes with the danger of increasing contact networks and transmission opportunities. To assess this trade-off and the potential for increased transmission, we will build models to incorporate school-level infection monitoring data along with community-level testing data, vaccination data, immunological and serological indicators among students and faculty, in addition to built environment indicators of school settings. These models will allows us to determine associations between community-level transmission rates and test positivity rates within schools (Aim 1), develop an epidemiological disease transmission model that identifies how to cost-effectively collect sentinel school surveillance data (Aim 2), and identify policy trigger points to predict when interventions should be implemented in schools to prevent disease transmission (Aim 3). Although I have the requisite engineering background and experience developing infectious disease models, additional training will maximize success of the proposed project and catalyze a robust independent research program. To accomplish these goals, I will obtain additional training in biological sciences and public health, particularly in community engagement, immunology, virology, and epidemiology. I will develop these skills through didactic training, independent study, and mentorship from experts in these fields: Drs. Maida Galvez, Rachel Vreeman, Jeffrey Shaman, Andrea Graham, Nicole Bouvier, and Chris Gennings. At the end of this training period, I will be uniquely positioned to comprehensively examine the effects of respiratory disease transmission in future research. Further, I will use the knowledge gained and the developed disease transmission models in future grant applications, establishing a crucial step toward my long-term goal of optimally designing infectious disease monitoring networks to reduce the spread of disease and improve the health of communities.