Developing New Statistical Methods for Vector-Borne Disease Surveillance to Improve Accuracy while Reducing Cost

开发新的媒介传播疾病监测统计方法，以提高准确性并降低成本

• 批准号: 10774013
• 负责人: Stella Coker Watson Self
• 金额: $ 75.86万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10774013
• 关键词: Amblyomma; Ambylomma americanum; Annual Reports; Area; Arizona; Bacteria; Biocompatible Materials; Case Fatality Rates; Case Study; Centers for Disease Control and Prevention (U.S.); Climate; Collection; Complication; Data; Delaware; Dermacentor; Diagnosis; Diagnostic; Disease; Disease Surveillance; Doxycycline; Environment; Environmental Risk Factor; Exposure to; Fever; Financial Hardship; Future; Geographic Distribution; Geography; Goals; Guidelines; Habitats; Health Personnel; Illinois; Incidence; Infection; Laboratories; Methods; Midwestern United States; Modeling; Monitor; Municipalities; Nature; Pathogenicity; Patients; Pattern; Population; Predisposition; Procedures; Process; Public Health; Reporting; Reproduction; Rhipicephalus sanguineus; Rickettsia; Rickettsia Infections; Rickettsia parkeri; Rickettsia rickettsii; Risk; Rocky Mountain Spotted Fever; South Carolina; Spatial Distribution; Specimen; Statistical Methods; Statistical Models; Surveillance Methods; Techniques; Testing; Tick-Borne Diseases; Ticks; Time; United States; Update; Vector-transmitted infectious disease; Weather; accurate diagnosis; cost; cost effective; cost efficient; data streams; data structure; design; disorder risk; empowerment; gulf coast; improved; interest; land cover; machine learning method; novel; pathogen; spatiotemporal; spotted fever; surveillance strategy; tool; trend; vector; vector tick; vector-borne infection; weather patterns

Project Summary/Abstract Vector-borne disease surveillance requires monitoring the geographic distribution of infected vectors and is a costly process that typically involves collecting vectors in the field and subsequently testing them for the presence of various pathogens. These costs are often prohibitive to financially strained public health labs and local municipalities, thus leaving the geographic distribution of many vector-borne diseases poorly understood. This is especially true for emerging diseases and those with expanding geographical ranges. Firmly understanding the spatial distribution of vectors infected with various pathogens is critical for healthcare providers who are using potential exposure to guide diagnostic and treatment decisions. To provide these assessments, this project will develop multiple cost-efficient vector-borne disease surveillance strategies, including both active and passive strategies. The active strategy reduces cost by leveraging pool testing techniques; i.e., rather than testing vectors one-by-one, multiple vectors are physically amalgamated to form a pooled specimen which is tested for the pathogen of interest. These techniques have the potential to drastically reduce testing cost, especially for surveillance efforts, but do so at the expense of a far more complicated data structure. To overcome this complication, we will develop a novel suite of spatial and spatio-temporal regression models which can be used to analyze pool testing data with an end goal of being able to better understand the geographic distribution and expansion of various vector-borne diseases. The passive strategies will leverage existing information, as well as data collected through this proposal, to develop ‘nowcasts’ of vector activity levels. These nowcasts will assimilate climate and habitat suitability, weather patterns and other key environmental factors to forecast activity, and therefore can be updated in real time without any associated cost. These nowcasts are intended to supplement active surveillance efforts and field collection, especially in areas where large scale collection is not feasible. To validate our surveillance strategies, we plan to undertake an ambitious study aimed at collecting and testing ticks for spotted fever group Rickettsia along the expanding geographic range of A. maculatum (South Carolina) and A. americanum (the Midwest). The data from this study will be used to validate and inform the design of both our active and passive surveillance strategies. In summary, our proposal seeks to transform the paradigm of vector-borne disease surveillance by reducing costs, improving accuracy, and quantifying risk in real time, while elucidating the spatio-temporal patterns vector infection by spotted fever group Rickettsia species.

项目摘要/摘要 向量传播疾病监测需要监测感染媒介的地理分布，这是一个 昂贵的过程，通常涉及在现场收集向量并随后对其进行测试以确保存在 各种病原体。这些费用通常被禁止用于财务紧张的公共卫生实验室和地方 市政当局，因此留下了许多媒介传播疾病的地理分布。这 对于新兴疾病和具有扩展地理范围的疾病而言，尤其如此。坚定的理解 感染各种病原体的载体的空间分布对于使用的医疗保健提供者至关重要 潜在的指导诊断和治疗决策。为了提供这些评估，该项目将 制定多种成本效益的媒介疾病监视策略，包括主动和被动 策略。主动策略通过利用泳池测试技术来降低成本；即，而不是测试向量 一对一的，多个向量在物理上融合以形成一个合并的样品，该标本已被测试 感兴趣的病原体。这些技术有可能大幅度降低测试成本，尤其是 监视努力，但要以更复杂的数据结构为代价。克服这一点 并发症，我们将开发一套新型的空间和时空回归模型，可以使用 分析池测试数据的最终目标，即能够更好地了解地理分布和 各种媒介传播疾病的扩展。被动策略将利用现有信息以及 通过此提案收集的数据，以开发矢量活动水平的“现象”。这些现象会 吸收气候和栖息地的适用性，天气模式和其他关键环境因素，以预测 活动，因此可以实时更新，而无需任何相关费用。这些现象旨在 补充积极的监视工作和现场收集，尤其是在大规模收集的领域 可行的。为了验证我们的监视策略，我们计划进行一项旨在收集和的雄心勃勃的研究 在扩大的地理范围内，斑点发烧组的立克斑点（South） 卡罗来纳州）和A. americanum（中西部）。这项研究的数据将用于验证和通知 我们的主动和被动监视策略的设计。总而言之，我们的建议旨在改变 通过降低成本，提高准确性和量化风险，对媒介传播疾病监测的范例 实时，同时阐明了斑点发烧组人力体的空间量表矢量感染 物种。