E Bruce Pitman
SUNY at Buffalo
Computer and Information Science and Engineering (CISE)
The ongoing COVID-19 pandemic has highlighted the need to design, build, and implement the next-generation of integrated environmental and clinical surveillance systems for monitoring and tracking the emergence, spread, and transmission of pathogens with pandemic potential at the local, regional, national, and global scale. In addition to pathogen and disease surveillance systems, there is a critical need for more robust networks, infrastructure, and protocols to communicate the risks of pandemic emergence to the right people at the right time including local, regional, and national health system leaders and stakeholders. The overarching goal of this project is to address the challenges associated with the development and deployment of an early warning system in Western New York that could 1) predict the onset of a pandemic by monitoring viral and human ecosystems and 2) communicate the risks of disease transmission and pandemic emergence to local/regional communities to guide the design and implementation of preventative measures and behaviors. To advance this goal, the project team will leverage funding for this PIPP Phase I planning grant to lay the foundation for the establishment of a Center that will integrate data from wastewater surveillance and the analyses of clinical nasopharyngeal samples to develop a baseline of infectious pathogens in communities with the aim of continuously tracking their spatial, temporal, and seasonal variations. In collaboration with the New York State Erie County Department of Health, the project team also proposes to explore the development and implementation of more effective strategies to communicate pandemic risks and mitigation recommendations including behavioral changes. The proposed Center development activities will include targeted research projects, workshops, and workforce development including the training and mentoring of two post-doctoral fellows and two graduate students at the University at Buffalo. This PIPP Phase I project will lay the foundation for the establishment of the Center for Ecosystems Data Integration and Pandemic Early Warning Systems in Western New York with a mission to 1) advance the design, development, and deployment of a robust and integrated early warning system for pandemic preparedness and 2) catalyze community engagement to build trust and partnerships to guide the design and implementation of preventative measures and behaviors to mitigate future pandemics. To advance this goal, the project team envisions an early warning system for disease outbreaks and pandemics based on the monitoring and surveillance of local/regional viral and human ecosystems. Building upon the availability of cutting-edge viral capture and sequencing techniques, the project team proposes to develop more efficient and robust assays and protocols for the routine monitoring of wastewater and de-identified human nasopharyngeal samples for known pathogenic viruses. In parallel, the project team proposes to evaluate the relative abundance of different viruses in the collected wastewater and nasopharyngeal samples to generate a detailed understanding of the local and regional viral ecosystems and viromes with the goal of identifying perturbations in these ecosystems that could be integrated into monitoring systems and models to serve as early indicators of pathogen and disease emergence. Finally, the project team proposes to develop mathematical and computational models including machine learning based models to 1) analyze and interpret the virome data and 2) explore the integration of clinical human data associated with a pandemic onset with the virome data to uncover patterns of viral infections and early signs of disease transmission and pandemic emergence in the local communities and broader Western New York region. This award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). 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.