Slots: 1. An organization may submit no more than one Letter of Intent to this solicitation as lead organization. An organization may submit up to one full proposal that corresponds to a Letter of Intent submitted to this solicitation. A full proposal that does not correspond to a Letter of Intent submitted to the program will be returned without review.
Research Deans to contact RII with any interested parties by Monday, July 31st, 2023. Closed.
LOI: August 25, 2023 (required)
External Deadline: December 8, 2023
Award Type: Cooperative Agreement
Estimated Number of Awards: 4 to 7
Anticipated Award Amount: $126,500,000
Who May Serve as PI:
The Lead PI must be a faculty member or equivalent at the lead organization. A letter of commitment from the Dean or equivalent at the lead organization must be submitted as part of the proposal given the broad focus of the centers.
NOTE: Submission or award of a Development Grant (PIPP Phase I) is not required to participate in the PIPP Phase II Centers Program competition
Link to Award: https://www.nsf.gov/pubs/2023/nsf23608/nsf23608.htm
Process for Limited Submissions
PIs must submit their application as a Limited Submission through the Research Initiatives and Infrastructure (RII) Application Portal: https://rii.usc.edu/oor-portal/. Use the template provided here: RII Limited Submission Applicant Template
Materials to submit include:
- (1) Two-Page Proposal Summary (1” margins; single-spaced; standard font type, e.g. Arial, Helvetica, Times New Roman, or Georgia typeface; font size: 11 pt). Page limit includes references and illustrations. Pages that exceed the 2-page limit will be excluded from review. You must use the template linked above.
- (2) CV – (5 pages maximum)
Note: The portal requires information about the PIs in addition to department and contact information, including the 10-digit USC ID#, Gender, and Ethnicity. Please have this material prepared before beginning this application.
Building on visioning exercises and the PIPP Phase I Development Grant Program, the PIPP Phase II program will fund Centers comprised of scientists, engineers, practitioners, and/or educators united by a common focus on advancing the research frontiers of epidemic and pandemic preparedness and national and global health security. The program seeks to build a broad, nationwide set of centers to pursue transformational advances in a range of science and engineering fields – see Center Themes, below. PIPP Phase II Centers will have as their primary focus the advancement of multidisciplinary, multi-stakeholder pandemic research on larger-scale, longer-time-horizon challenges than are supported in typical research grants.
Against this broad and ambitious scope, it is expected that each Center will pursue their vision in ways that are best suited to its selected research focus, facilities, collaborations, and other unique circumstances. Proposers are encouraged to convey the unique qualities of the proposed Center, while addressing the following:
- Centers are coherent multidisciplinary groups of scientists, engineers, practitioners, and/or educators appropriate for a large-scale, long-term research agenda for the advancement of pandemic research and innovation in application sectors of national importance. The multidisciplinary nature of these Centers will catalyze coordinated, convergent, and nimble responses to pandemics and pandemic research needs that are not hindered by silos and lack of shared data. Additionally, the individual projects that a Center may carry out should meaningfully integrate into fundamental contributions beyond the sum of the individual projects.
- PIPP Phase II Centers innovate and advance foundational research that will have broad and lasting impact, contributing new knowledge or methods toward understanding the rise, spread and response to pandemics (see the program vision specified above). Centers aimed at advancing established lines of research should demonstrate the potential to radically advance these areas beyond the state of the art. For Phase II Center proposals that arise from a PIPP Phase I Development grant, proposals are expected to address how new foundational research and development priorities arose and advanced from previous funding. PIPP Phase II Center proposals that do not describe a clear plan to achieve ambitious advances in foundational research will not be responsive to this solicitation. It is critical that proposals clearly specify how the use-inspired context for Center research reveals the opportunities for foundational advances and how those foundational advances in turn contribute to the related sectors that define the use-inspired context. This dimension of a center-scale proposal will feature clear and compelling goals to enhance the transfer of knowledge through the meaningful exchange of scientific and technical information with external stakeholders such as industrial partners, public policy makers and users, or international organizations, as well as with the broader scientific and educational community. Through use-inspired contexts, Centers have the potential to create and share new community infrastructure, including data and software and/or analytical capacity, to further research, promote data and research reproducibility, and support education.
- PIPP Phase II Centers actively build the next generation of talent for a diverse, well-trained workforce. Specifically, a Center should leverage the visionary nature of their research foci to drive new and innovative education and development tailored toward e.g., undergraduates, graduate students, and post-doctoral researchers, as well as through community colleges and skilled technical workforce training and other opportunities as appropriate that advance knowledge and education of pandemic related research. This could include innovative pedagogy, curricula and instructional materials, advanced learning technologies, project-driven training, cross- disciplinary and collaborative research, industry partnerships, and new career pathways. Centers should offer broad, deep, and diverse experiences to build the next generation of a workforce ready to deal with pandemic threats, with a focus on broadening participation among the full range of groups currently under-represented in science and engineering. Centers should maximize their unique position to grow the next generation of talent that will provide new discoveries and leadership.
- Each Center will be comprised of multiple organizations/entities working together to create significant new research capabilities. NSF seeks to grow new Centers of pandemic research leadership throughout the country and encourages leveraging existing Centers of excellence as appropriate. Centers are strongly encouraged to include organizations that directly contribute to NSF’s commitment to broadening participation by engaging a diverse, globally engaged research community, integrating research with education and building capacity, and expanding efforts to include the participation of the full spectrum of diverse talent in STEM and diverse institutions across all geographical regions. Participants should be meaningfully integrated into a diverse Center. Each Center will have a lead PI with demonstrated vision, experience, and capacity to manage a complex, multi-faceted, and innovative enterprise that integrates research, education, broadening participation, and knowledge transfer. Each Center will also be staffed with a Managing Director or Project Manager (distinct from the lead PI) and a suitable Management Team to oversee the operations of the Center.
- PIPP Phase II Centers are nexus points for collaborative efforts. The “nexus point” function in this program is not a mere state of being, but rather an active set of priorities, programs, mechanisms, etc., whereby a Center pursues the continuing growth of collaborations with external partners to bring together people, ideas, problems, and technical approaches for maximum impact beyond the members and the boundaries of the Center itself. As nexus points, Centers have the potential to continue to connect with new partners with the best teams and approaches from institutions of higher education, federal agencies, industry, nonprofits/foundations, centers/institutes, and national networks. As nexus points, Centers promote organizational collaborations and linkages within and between campuses, schools, and the world beyond, and further the Center’s mission to broaden participation in research, education, and knowledge transfer activities through a network of partners and affiliates.
Building on previous visioning exercises and funding opportunities through the PIPP Phase I Developmental Grant effort, in this round, proposals are being solicited in the following high-priority areas, described below. The descriptions for each theme are only intended to provide a broad, principal focus, they are not exhaustive reviews of respective fields. Also, while each theme has a clear center of gravity in some disciplines, successful Center-scale proposals will integrate and innovate across all relevant areas of environmental, biological, chemical, physical, materials, social, behavioral, economic, mathematical, computer and information science and engineering science, and reflect this in balanced expertise on the team of collaborators and participants. Full proposal submissions MUST identify as a principal focus one of the themes described below. This principal theme must be reflected in the Title of the Project. However, the themes below are not mutually exclusive, and it is expected that connectivity exists between themes.
Theme 1: Pre-emergence – Predicting and detecting rare events in complex, dynamical Systems
Natural and social systems are dynamic, stochastic, nonlinear, multi-scale and complex, making both the theoretical prediction and modeling of its states challenging. Some examples in a predictive context include: epidemiological transitions from a pre-emergence stage to localized emergence (epidemic) and/or a pandemic; transition of an individual or a community from resistant to susceptible to disease; transition of a microbe from harmless to pathogenic.
Usually, these systems spend protracted periods of time in various metastable states and only very rarely, and at seemingly random times, transition to other states, often producing effects that cross spatial and organismal scales in the process. Predicting the dynamics of such systems across scales requires the development of frameworks of contextual predictive intelligence to understand how transition paths interact with a series of additional and often seemingly unrelated events and/or dynamic variables.
One challenge to innovation in data-driven and contextual predictive intelligence for pandemics is the need to develop Artificial Intelligence (AI)- and machine learning (ML)-based computational approaches that meaningfully analyze multiple biological data points (e.g., from bio-surveillance, host-pathogen interactions, at scale ecology) to timely (real-time, just-in-time) identify events that are biologically relevant and significant for pandemics. This will require robust mathematical and physical models, and new biologically-cognizant computational approaches to (1) detect and analyze data that are being collected continuously and across scales, and (2) identify the key events (which may appear unrelated at the onset) that precede pandemics. Another, related challenge is the integration of data-driven approaches with mechanistic models to facilitate our understanding of the biological underpinnings of the complex process of emergence. This will require integrating molecular to environmental scale data and models, with novel computational systems to identify biological, environmental, and/or sociological drivers of rare events and transition states that influence emergence.
Theme 2: Data, AI/Machine Learning and Design – Computing, sensing, manufacturing and technology innovation for pandemics
With the current and emerging challenges of increased spill-over risk of pathogens it is important that a paradigm shift occurs in how pathogens and diseases are identified across ecosystems and hosts in either real time, or times well ahead of outbreaks (see Theme 1 above). This shift involves improving the granularity and timeliness of available epidemiological information, with hybrid systems augmenting rather than supplanting traditional surveillance systems. On the data collection and information integration domain, most available technologies are designed for humans. Move towards new ideas to develop methods and devices grounded in advances of wireless technologies, computing software and hardware, algorithms, and machine learning that enable data monitoring, acquisition, and analysis for animal hosts and humans is warranted. We envision that information gained on changes in animal behavior and welfare, physiology, or range to intelligently and timely identify pre-pandemic conditions.
Another critical area of research to enhance prediction is in computational algorithms and frameworks for processing, analyzing, and modeling data to enable inference of difficult-to-measure information and integration of traditional computing and biological computing platforms. This highlights the effort needed to connect measurable with difficult/unmeasurable (observable versus unobservable) biological events/characteristics/processes for pre-emergence forecasting of pandemics. Progress in biological sensor technologies, in-situ sensors, and smart sensor networks to record difficult-to-measure or track in near real time cellular and molecular-scale effects as well as to monitor biological systems at all scales is critical. Monitoring systems at a higher level for effective and comprehensive disease emergence and spread prediction/analysis could benefit from coordinated solutions of in-situ detection, computation, and decision by networked sensors, actuators and processors, and physical processes, together with cybersystems (such ecosystems could be modeled as cyber-physical systems) of simulated events where the interactions between levels and systems can be simulated to enhance, understand, and generate empirically based policy. An important challenge and opportunity to advance in this field calls for a continuous and iterative feedback loop between simulated and real worlds, which must happen in either real time or at relevant time scales.
The development and strengthening of computational methods and process of data collection, analysis, storage, curation, and analytics, along with a “model commons” serving as a repository of leading-edge modeling and simulation about pathogens and pandemic disease is the basis for a successful predictive intelligence for pandemic prevention program. On the other hand, the increasing number of available models and the lack of best practices in coordination, integration and data sharing are major roadblocks in the development of the field. This solicitation calls for a clearly rationalized research plan that addresses these concerns at all steps in the design of computing and networked systems/infrastructure for predictive intelligence for pandemic prevention.
Theme 3: The Host as the Universe – Identifying host-pathogen tipping points that dictate control or spread of an infection
The host can be the bottleneck or the amplifier of a pathogen. The outcome of infection may change in the face of pathogen mutation and/or changes in the host environment. A concerted research effort spanning multiple research areas is required to understand the basis for host control in the spread of an infection under these changing conditions. Research submitted under this theme is expected to pursue critical aspects of molecular, cellular and physiological mechanisms that dictate the outcome of host-pathogen interactions, including disease outbreaks. This foundational knowledge could be exploited to inform insights to control or predict pathogen emergence, identify new therapeutics or vaccines, or predict and understand the emergence and maintenance of antimicrobial resistance.
A game-changer in pandemic prevention would be remote sensors that autonomously track and report on pathogens and their hosts in situ over time and space. Remote tools and technologies for detecting and monitoring changes in biological systems and processes that are also capable of analyzing and transmitting information from hosts could make possible the discovery of potential for outbreaks prior to society-scale dissemination. Although genome sequencing is now ubiquitous it remains difficult to use this sequence (or other -omics based methods) to accurately predict hosts for a new pathogen, or to detect transmission and amplification routes of a new pathogen. This challenge could be overcome by advances in engineering and in computational algorithms and frameworks for processing, analyzing and modeling data.
Molecular-level information exists about host responses to infection and about the bio-synthetic pathways required for a pathogen to survive in a specific host. This information can be leveraged to develop therapeutic and diagnostic tools. There is still a gap in understanding how these functions occur temporally and in concert within the entire host organism, and the hierarchy of mechanisms that result in control or spread of an infection within an individual and throughout homo- and heterogeneous hosts. An opportunity to advance in this field is developing mathematical and computational models that accurately predict infection outcomes from sub-cellular events.
Theme 4: Human Systems – The role of human behavior, activities and environment in disease emergence, transmission, response and mitigation.
The devastating human, economic, and social costs of the recent pandemic have highlighted the urgent need for coordinated research and actions to build resilient systems for pandemic prevention, preparedness, and response. Central to the development of resilient systems is a recognition of the role that humans and their environments play in disease and pandemic dynamics and an understanding of the complex behavior of humans at individual, group, organizational, societal, and global scales.
For the purpose of this solicitation, the term environment is broadly construed, it may include biological, physical and chemical components, and may consider a continuum of environments from those with very limited human populations (e.g., “natural” environments) to those in which human systems and processes fully dominate (e.g. cities, built environments). Research that meaningfully incorporates social and behavioral processes in epidemiological models relevant to human systems and environments is particularly critical.
Center projects submitted to this theme will therefore advance science and engineering research on human systems that are relevant to improved pandemic prevention and resilience. It is expected that research in this theme will be necessarily interdisciplinary and explore aspects of how human cognition, behavior and attitudes, and the sociocultural and socio-environmental drivers underlying these, contribute to disease emergence, transmission and mitigation. Research under this theme must address human behavior and/or social processes, and projects may, but need not, focus on human pathogens or human hosts. Understanding the human impact will also allow for the development and optimization of high impact methods for disease surveillance/prevention/suppression/containment/mitigation protocols. Examples of broad areas of focus that leverage and advance foundational research in science and engineering and support use-inspired goals include, but are not limited to: investigating how the environment and/or human attitudes, beliefs, decisions, and activity patterns contribute to disease transmission and affect pandemic resilience and responses; understanding the processes in water, soil, and/or air that trigger or amplify pathogen spread in human environments; understanding the role of organizations and policymakers in communicating disease risk, coordinating across stakeholders, shaping research efforts, and planning and implementing disease mitigation protocols; and utilizing and advancing sociocultural and economic models and theories about the ethical and logistical trade-offs between human health/privacy and economic/societal health in order to optimize disease prevention and mitigation strategies.
Visit our Institutionally Limited Submission webpage for more updates and other announcements.