PIPP Phase I: Center for Emerging Pathogen Prediction and Integration

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The Predictive Intelligence for Pandemic Prevention (PIPP) Phase I: Development Grants Center for Emerging Pathogen Prediction and Integration (CEPPI) will lead strategic surveillance of wildlife pathogens across changing environments. Understanding and preventing the emergence of new infectious diseases requires interpreting many types of data (e.g., information on the disease-causing pathogens, interactions between the human and wildlife populations, and changes in their associated environments). The team will use the vast historical data and sampling available in biorepositories, such as museums, to systematically investigate pathogen emergence to enable reliable predictions of zoonotic disease to help prevent or mitigate future pandemics. Many aspects of pathogen biology in wildlife remain poorly documented worldwide, particularly in low-income, biodiverse regions. Pandemics pose a challenge that requires international, collaborative, proactive solutions, so the Center will focus on developing best methods in training the next generation of pathogen biologists, improving basic biodiversity infrastructure, databases, and workflows, and then sharing these new approaches globally. Working especially with partner museums in the Americas, the Center will expand wildlife sampling strategies to develop a more comprehensive, decentralized network of specimen repositories and researchers to improve pathogen identification and surveillance.To improve pathogen detection, surveillance, and mitigation, the Center will promote state-of-the-art biorepositories, genomic screening, and bioinformatic workflows, which are empowered by intuitively interactive visualization web tools, computational and mathematical modeling, and machine learning. Rapid visual and intelligent integration of pathobiology into the vast global, digital infrastructure for wild mammals is the cornerstone of this Center, which will act as an early warning system for pandemic prediction and prevention. In Phase I, the cross-disciplinary team aims to develop internationally scalable multidisciplinary workflows to build: 1) informatics baselines for pathogens and hosts derived from existing archival biorepositories representing decadal sampling of mammalian communities that will be linked directly to targeted strategies for improved monitoring and surveillance; 2) pipelines that streamline sequencing and bioinformatic methods for rapid, affordable, large-scale screening of mammalian host and parasite samples to provide scalable views of diversity and change over space and time; 3) pathogen risk assessments linking novel methods that integrate social and environmental parameters and pathogen diversity to predict the outcomes of accelerating anthropogenic change; 4) collaborations across local biorepositories to develop strategic sampling and digitization protocols for expanded geographic, temporal and taxonomic coverage; and 5) problem-solving networks through educational modules, direct engagement, and collaborative learning. CEPPI helps standardize exploration of pathogens and biodiversity by building new connections with local communities, sequencing and bioinformatic facilities, and public health and natural resource agencies. New capacities for visualization, informatics interpretation, and translation emanate from the development of fast, affordable, and scalable sequencing and bioinformatic technologies. These capacities will stimulate new methods of pathogen detection, discovery, and monitoring that will foster global pathogen surveillance and mitigation. 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.