Conference: Ecology and Evolution of Infectious Diseases 2024 Workshop

该奖项将资助2024年6月22日至24日在斯坦福大学举行的研讨会，以及年度传染病生态学和进化（EEID）会议。该讲习班将提供与经典分区流行病学模型、使用贝叶斯推断估计环境响应函数以及使用谷歌地球引擎进行地理空间数据分析有关的尖端定量培训和应用技能。学生将学习疾病生态学模型如何应用于具有公共卫生和非营利部门工作经验的从业者的现实世界场景。研讨会将采用动态时间表，穿插定量和应用培训课程。该研讨会将支持来自不同人口群体，机构和教育背景的至少40名学生在疾病生态学中的尖端定量和应用工具方面的科学培训和网络机会。基于项目的教学将鼓励学生建立学生之间的合作，这将有助于形成持久的债券。学生还将在小教室（每个轨道约30名学生）接受实践指导，以确保与教师建立联系的机会。一些早期的职业导师将获得教学机会，展示他们的工作在应用背景下，并建立自己的网络与学生和博士后学者。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

This award will fund a workshop at Stanford University June 22-24, 2024, in conjunction with the annual Ecology and Evolution of Infectious Diseases (EEID) conference. The workshop will offer a mix of cutting-edge quantitative training and applied skills related to classic compartmental epidemiological models, estimating environmental response functions using Bayesian inference, and geospatial data analysis using Google Earth Engine. Students will learn how disease ecology models are applied in real-world scenarios from practitioners with experience working in public health and nonprofit sectors. The workshop will feature a dynamic schedule that intersperses quantitative and applied training sessions. This workshop will support scientific training and networking opportunities for at least 40 students from across demographic groups, institutions, and educational backgrounds in cutting edge quantitative and applied tools in disease ecology. The project-based instruction will encourage students to build collaborations among students that will help to form lasting bonds. Students will also receive hand-on instruction in small classrooms (~30 students per track) to ensure networking opportunities with the instructors. Several early-career instructors will receive teaching opportunities to showcase their work in an applied context and to build up their networks with students and post-doctoral scholars.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.