US-UK Collab: Adaptive surveillance and control for the elimination of endemic disease

对传染病发病率的定量观察确定了人类和动物健康问题的范围，并随着时间的推移揭示了使我们能够制定并随后评估有效控制策略的潜在动态。因此，监测系统对于制定以证据为基础的政策至关重要。开发一个有效的监视网络需要了解受监视的系统。这一建议为监测系统的演变及其适应制定了一个框架，同时开发了支持决策的模型、控制和消除政策的变化以及疾病传播对控制的不断变化的动态。在监测网络仍然不完善的许多情况下(例如，在资源不足或尚未被视为优先事项的疾病)，缺乏针对当地的人口、监测、血清型和流动/连通性数据，阻碍了循证政策的发展。虽然收集这些数据的努力将始终促进科学理解，但我们建议，基于模型的数据收集和监测系统设计的优先顺序将导致更有效地定向数据收集，以具体支持疾病控制和根除目标。这项工作将利用土耳其2001-2012年口蹄疫(FMD)病毒发病率的高分辨率、长期、特定毒株的监测数据，开发基于模型的数据收集和监测系统设计的一般方法。这项拟议的工作将开发第一个国家规模的、特定毒株的地方性口蹄疫传播模型。口蹄疫在许多低收入和中等收入国家是一种严重的家畜疾病，这里开发的模型将为口蹄疫持续存在的机制提供洞察，并为制定特定于当地的模型以支持流行国家的政策发展提供指导。这项提议将开发新的方法来开发混合监测系统，以有效地结合1)被动监测与基于模型的主动监测工作分配，以及2)现场诊断与诊断确认。土耳其现有的数据反映了目前正在制定口蹄疫控制和消除计划的国家所能实现的“黄金标准”。本提案将制定的方法将涉及口蹄疫经验模型和监测系统的迭代开发，并将为目前没有高度分辨率监测数据的国家提供路线图。联合调查员将通过年度会议与土耳其的口蹄疫管理人员接触，转让关于监测和控制战略的模型和见解，并制定更多的控制战略，以利用本文开发的模型进行评估。联合调查员将通过现有的EuFMD培训讲习班，进一步与肯尼亚和乌干达的口蹄疫管理人员接触，以开发土耳其案例研究的经验教训在这些国家的应用。许多地方病控制项目的数据收集有限或不完善。本提案中提出的例子和方法将广泛适用于需要同时制定监测、模型和政策的人类和动物疾病环境。这项提案的联合调查人员与人类和动物健康政策组织有着长期的接触历史，并将努力将口蹄疫案例研究的经验教训转化为其他背景。初级项目工作人员将接受培训，了解本建议中制定的应用于口蹄疫的方法，并鼓励他们开发应用于其他地方性动物和人类疾病系统(例如禽流感、麻疹、风疹、脑膜炎、轮状病毒)的方法。在他们的职业生涯中，这些人将在将定量科学进一步转化为区域和国家机构方面发挥宝贵的作用。

Quantitative observations of infectious disease incidence define the scope of human and animal health problems, and, over time, reveal the underlying dynamics that allow us to develop, and then evaluate, effective control strategies. As such, surveillance systems are crucial to developing evidence based policy. Developing an efficient surveillance network requires knowledge of the system under surveillance. This proposal develops a framework for the evolution of surveillance systems and their adaptation in tandem with the development of models to support decision-making, changes in control and elimination policies, and the evolving dynamics of disease transmission in response to control. In many settings where surveillance networks remain rudimentary (e.g. in under-resourced settings or diseases that are not yet considered priorities), development of evidence-based policy is hampered by lack of locally-specific demographic, surveillance, serotype, and movement/connectivity data. While efforts to collect these data will always advance scientific understanding, we propose that model-based prioritization of data collection and surveillance system design will lead to more efficient targeting of data collection to specifically support disease control and eradication goals. This work will develop general methods for model-based prioritization of data collection and surveillance system design using highly resolved, long-term, strain-specific surveillance data on foot-and-mouth disease (FMD) virus incidence in Turkey from 2001-2012. This proposed work will develop the first country-scale, strain-specific models of endemic FMD transmission. FMD is a significant livestock disease in many low and middle income countries (LMICs) and the models developed here will provide insight into the mechanisms of FMD persistence and serve as a guide for the development of locally specific models to support policy development in endemic countries. This proposal will develop novel methods for developing hybrid surveillance systems to efficiently mix 1) passive surveillance with model-based allocation of active surveillance effort, and 2) field diagnosis with diagnostic confirmation. The data available for Turkey reflect a "gold standard" for what could be achieved in counties that are currently developing FMD control and elimination plans. The methods that will be developed in this proposal will address the iterative development of empirical models and surveillance systems for FMD and will provide a roadmap for countries that currently do not have highly resolved surveillance data. The co-investigators will engage with FMD managers in Turkey, through annual meetings, to transfer models and insights on surveillance and control strategies, and to develop additional control strategies to be evaluated with the models developed herein. The co-investigators will further engage with FMD managers in Kenya and Uganda through existing EuFMD training workshops to develop applications of lessons from the Turkey case-study in those countries. Many control programs for endemic disease suffer from limited, or imperfect, data collection. The examples and methods developed in this proposal will be broadly applicable to human and animal disease settings where surveillance, models, and policy need to be developed in tandem. The co-investigators for this proposal have a long history of engagement with both human and animal health policy organizations and will work to translate lessons from the FMD case study to additional settings. Junior project staff will be trained on the methods developed in this proposal in application to FMD and encouraged to develop applications in other endemic animal and human disease systems (e.g. avian influenza, measles, rubella, meningitis, rotavirus) studied by the assembled co-PIs. These individuals will serve a valuable role in the onward translation of quantitative science to regional and national agencies throughout their careers.