Presentation Type
Oral Presentation
Category
Social Sciences/Humanities
Abstract/Artist Statement
Microorganisms have plagued humankind for millennia and frequently participate in an evolutionary arms race against their hosts. Diseases from various microorganisms have crippled entire countries or led to massive population declines in recent history. However, much is unknown about epidemiology in ancient times. My project will be the first comprehensive paleoepidemiological approach to understand disease across populations in Europe during the Neolithic era (7000-1700BC). The Neolithic was one of the most profound transformations in human history, both culturally and biologically. Massive migrations, formations of the earliest settlements in Europe, and introduction of agriculture and pastoralism led to new environments for humans, domesticates, and microorganisms. By analyzing over 1000 genomes from across Europe, I will be able to identify certain pathogens in specific populations. This data will be coupled with archaeology and linguistics data to begin tracing the group’s movements to understand the disease dynamics and how disease started and spread. Eventually, a broad picture will be painted of the entire ancient history of disease on the European continent. This research will provide understanding of largescale disease progression and its many variables including cultural subsistence, population migration, and pathogen evolution. Conclusions from this research can be used as case studies for current or future disease outbreaks and the genetic information obtained from pathogens can potentially be used to identify ways around resistant strains, such as the modern Tuberculosis resistant strains.
Mentor Name
Dr. Meradeth Snow
Personal Statement
This research seeks to understand disease from an ancient lens and to further understand how massive, paradigmatic social changes at the time altered the landscape and biology of humans, animals, plants, and microbes forever. Though this research primarily focuses on the past, its value is not just a more thorough understanding of the past, but that these findings can be brought forward to the present and future to use the mechanisms of human and animal behavior, landscape changes, and climate to understand and potentially predict modern pathogen origins and outbreaks. This research was valuable before a global pandemic and the modern pandemic has helped confirm that these ancient disease studies are pivotal to understanding the complexity of disease origins and transmission.
The Forgotten Epidemic: Identification of MTBC in the Neolithic Trypillia of Verteba Cave, Ukraine
UC 326
Microorganisms have plagued humankind for millennia and frequently participate in an evolutionary arms race against their hosts. Diseases from various microorganisms have crippled entire countries or led to massive population declines in recent history. However, much is unknown about epidemiology in ancient times. My project will be the first comprehensive paleoepidemiological approach to understand disease across populations in Europe during the Neolithic era (7000-1700BC). The Neolithic was one of the most profound transformations in human history, both culturally and biologically. Massive migrations, formations of the earliest settlements in Europe, and introduction of agriculture and pastoralism led to new environments for humans, domesticates, and microorganisms. By analyzing over 1000 genomes from across Europe, I will be able to identify certain pathogens in specific populations. This data will be coupled with archaeology and linguistics data to begin tracing the group’s movements to understand the disease dynamics and how disease started and spread. Eventually, a broad picture will be painted of the entire ancient history of disease on the European continent. This research will provide understanding of largescale disease progression and its many variables including cultural subsistence, population migration, and pathogen evolution. Conclusions from this research can be used as case studies for current or future disease outbreaks and the genetic information obtained from pathogens can potentially be used to identify ways around resistant strains, such as the modern Tuberculosis resistant strains.