Jennifer Surtees

Photo of Jennifer Surtees.

The Surtees lab explores mechanisms of genome stability, the many and varied pathways that protect the integrity of genomes. Surtees believes that scientists have a responsibility to communicate clearly with the public as discoveries push the boundaries of knowledge and technology in biology. An informed public is better able to support science and benefit from it.

Surtees serves as co-director of the Genome, Environment and Microbiome (GEM) Community of Excellence at UB, which advances understanding of the genome and microbiome and their interaction with the environment through research, education, community programs and art.

During the COVID-19 pandemic, Surtees has worked with UB colleagues and a number of COVID-19 testing partners to conduct genomic sequencing of virus samples in Western New York. These efforts have aided the region’s COVID-19 response, identifying the arrival of new variants and helping the community understand how SARS-CoV2 infections are changing locally as the virus evolves. She also collaborated with faculty students and staff to develop K-12 “Covid Chats” and vaccine information for all ages.

Surtees feels strongly that we must learn from the lessons of the COVID-19 pandemic and prepare ourselves for future outbreaks and other potential pandemics by building on the infrastructure we have established since 2020. Surtees has assembled a strong interdisciplinary team, with expertise in genetics, environmental engineering, and mathematical modeling, to develop an early warning system for infectious diseases that integrates multiple types of ecosystem data from a wide range of stakeholders, including the community. But detection is only the first step. We must also develop true partnership and trust among researchers, public health officials, government, and the public. To do this, are actively and continuously engaging and partnering with members of diverse community groups. Our goal is to promote community resilience and support a proactive response. This work is supported by an NSF Predictive Intelligence in Pandemic Prevention grant.