Paleodemographic and ancient DNA study of a potential epidemic site

中世纪的黑死病（瘟疫）、20世纪的埃博拉病毒和SARS-CoV-2等传染病塑造了过去和现在人类死亡的模式。这个项目促进了我们对人类传染病及其对人口和社会影响的理解。调查人员汇集了生物考古学、遗传学和古流行病学专业知识，研究了一个史前定居点，在那里发现了流行病和灾难性死亡的迹象。该项目可以促进对致命传染病如何在人群中表现和演变的了解，并为疾病预测、预防和控制的现代研究拓宽比较背景。该项目还支持学生在STEM、公共科学推广工作和国际科学合作方面的培训和指导。除了估计人口统计信息和病理指标外，研究人员还重建了健康和死亡率概况。将死亡率模式与其他已知的致命传染病，特别是黑死病进行比较，在这种疾病中，老年人和所有年龄的体弱者都不成比例地死亡。此外，还收集了骨骼和牙齿样本，利用最先进的技术进行遗传分析，以确定导致灾难性死亡的病原体。通过病原体鉴定，调查人员可以检查它所产生的死亡模式的地理和时间变化。项目数据可以生成模型，供有兴趣进一步分析影响过去人口的人类健康和疾病的遗传和环境因素的研究人员使用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Infectious diseases such as the medieval Black Death (plague), 20th-century Ebola, and SARS-CoV-2 have shaped patterns of human mortality past and present. This project advances our understanding of human infectious diseases and their impact on human populations and societies. The investigators bring together bioarchaeological, genetic, and paleoepidemiological expertise to examine a prehistoric settlement where signs of epidemic disease and catastrophic mortality have been detected. The project can advance knowledge of how deadly infectious diseases have behaved and evolved in human populations and broadens the comparative context for modern-day research on disease prediction, prevention, and control. The project also supports student training and mentoring in STEM, public science outreach efforts, and international scientific collaborations. The researchers reconstruct health and mortality profiles in addition to estimating demographic information and pathological indicators. Mortality patterns are compared to those of other known deadly infectious diseases, especially the Black Death, during which the elderly and frail individuals of all ages were disproportionately killed. In addition, bone and tooth samples are collected for genetic analysis using state-of-the-art techniques to identify the pathogen that caused the catastrophic mortality. With a pathogen identification the investigators can examine geographic and temporal variation in the mortality patterns it produced. The project data can generate models available to researchers interested in further analyses of genetic and environmental factors influencing human health and disease in past populations.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.