Multidisplinary Emerging Infectious Disease Research at NSF

The Division of Biological Infrastructure (DBI) provides funds for research infrastructure and human resources through its core programs in Infrastructure Innovation for Biological Research, Infrastructure Capacity for Biological Research, Sustaining Infrastructure for Biological Research, Postdoctoral Research Fellowships in Biology, Research Coordination Networks in Undergraduate Biology Education, and Research Experiences for Undergraduates. DBI is interested in the following topics related to EID:

• Development of software analytics or models relevant to predicting likelihood of emergence, infection and spread of infectious diseases.


• Design of novel methodologies, including bioinformatics approaches, research methods, and instrumentation, to elucidate the mechanisms of infectious disease from molecular to cellular level.


• Developing and sustaining computational platforms and tools that enable collecting, archiving, analyzing, updating, and integrating a variety of research data relevant to infectious diseases, and pathogens and their interaction with hosts.


• Creation of innovative components that integrate analytical and computational tools with a strong scientific grounding in biosciences that could lead to new discoveries or better technologies in emerging infectious disease.


• New and creative paradigm or models for training undergraduates and/or postdoctoral fellows that prepare them for a future in the emerging infection diseases.


• Postdoctoral training with sponsors in the area of emerging infectious disease, as long as they are addressing a basic science question.


• Creative use of networks of faculty and educators to address undergraduate biology education in emerging infectious diseases.

The Division of Environmental Biology (DEB) Core Track supports research and training on evolutionary and ecological processes acting at the level of populations, species, communities, and ecosystems. Research on EID related topics in the above-described areas should be discussed with a program director prior to submission to the core clusters (Ecosystem Sciences, Evolutionary Processes, Population and Community Ecology, and Systematics and Biodiversity Sciences). Additionally, EID related projects that engage quantitative, interdisciplinary, systems-oriented research on biosphere processes and their complex interactions with climate, land use, and changes in species distribution at regional to continental scales are encouraged to contact program directors in DEB's Macrosystems Biology and NEON-Enabled Science (MSB-NES): Research on Biological Systems at Regional to Continental Scales program.

The Division of Integrative Organismal Systems (IOS) funds multiple areas of EID research within their core funding opportunities. IOS funds research that elucidates how interactions between the host and the infectious agents results in severity of infection (including the full spectrum of infection outcomes from mutualism to acute infection). In addition, IOS funds research on physiological, developmental, and behavioral processes that are affected by recent or inherited infections. Finally, IOS funds research using comparative approaches to elucidate origins or development of the immune system. The Division in particular welcomes projects that employ systems approaches or tackle the complex multi-layered systems of interactions between hosts and infectious agents. IOS welcomes proposals to its core programs that include the Behavioral Systems Cluster (BSC), the Developmental Systems Cluster (DSC), the Physiological and Structural Systems (PSS) cluster (which houses the interagency Symbiosis, Infection & Immunity (SII) program and the Plant-Biotic Interactions (PBI), Programs) the Neural Systems Cluster (NSC), the Plant Genome Research Program (PGRP), and the Enabling Discovery Through Genomics (EDGE) Program that bring integrative approaches to:

• Identify elements in the host-pathogen arms race that either permit or deter establishment of infection; feed forward and feedback loops that dictate outcome or resolution of infection (PBI, SII)


• Examine how climate change stressors (both biotic and abiotic) impacts host behavior and resilience to infection; how environmental stressors impact the development or function of the immune system to the detriment of the host (IEP, PGRP, PBI, SII, BSC)


• Use comparative approaches to map host and pathogen gene interactions concurrently to identify genomic mechanisms responsible for disparate outcomes of infection (EDGE, PGRP)


• Understand the role of the neural-endocrine system during infection and the effect it has on behavior changes, including those involved in sickness (NSC)


• Understand the impact of animal behavior (e.g., sociality, species interactions, movement) as a disease spread factor and, conversely, understanding successful host-seeking behavior or behavioral manipulation by the pathogen (BSC)


• Understand immune system development during different stages of organismal development or aging (DSC)


• Characterize and understand the integrative context-dependent nature of infection outcomes (All IOS).

The Division of Molecular and Cellular Biosciences (MCB) funds research on the emergent properties of pathogens across the molecular, subcellular, and cellular scales, using laboratory, mathematical modeling, and computational approaches. MCB welcomes submissions to its core programs in Systems and Synthetic Biology (SSB), Cellular Dynamics and Function (CDF), Genetic Mechanisms (GM) and Molecular Biophysics (MB) and is especially interested in the following topics:

• Examination of mechanisms that give rise to viral or other pathogen genetic variation (GM).


• Emergent properties of pathogens across the molecular, subcellular, and cellular scales, using laboratory, mathematical modeling, and computational approaches (CDF, SSB).


• Design and development of novel biological platforms that are capable of sensing and responding to emerging infectious agents (SSB).


• Development of new computational and experimental tools that enable the prediction of and demonstrate the limits of prediction of viral evolution (GM, MB).


• Characterization of key biophysical properties of pathogenic virus through all atom simulations with a view to understanding function and sites of potential disruption (MB).


• Understanding the structure and function of potential pathogens with a view to identifying conserved regions of genomes and proteins that might be suitable as future treatment targets (GM).


• Understanding how host and viral genomes interact to predict potential disease outcomes as well as pathogenic range and virulence (GM, CDF).


• Understanding viral assembly pathways to enable disruption (MB).

• Ecology and Evolution of Infectious Diseases (EEID)


• Predictive Intelligence for Pandemic Prevention Phase I: Development Grants (PIPP Phase I)


• Incorporating Human Behavior in Epidemiological Models (IHBEM)

The Division of Computing and Communication Foundations (CCF)

• Foundations of Emerging Technologies (FET) Cluster

Division of Information and Intelligent Systems

• Information Integration and Informatics (III) Cluster

The purpose of this interagency program with the National Institutes of Health is to support the development of transformative high-risk, high-reward advances in computer and information science, engineering, mathematics, statistics, behavioral and/or cognitive research to address pressing questions in the biomedical and public health communities. Transformations hinge on scientific and engineering innovations by interdisciplinary teams that develop novel methods to intuitively and intelligently collect, sense, connect, analyze and interpret data from individuals, devices and systems to enable discovery and optimize health. Solutions to these complex biomedical or public health problems demand the formation of interdisciplinary teams that are ready to address these issues, while advancing fundamental science and engineering.

Addressing the challenges will require fundamental research and development of new tools, workflows and methods across many dimensions; some of the themes are highlighted below.

• Information Infrastructure: This theme encourages pursuit of fundamental research in data management to enable interoperable, distributed, federated, and scalable digital infrastructure to optimize knowledge discovery.


• Transformative Data Science: This theme supports development of novel computational approaches for fusion and analysis of multi-level and multi-scale clinical, imaging, biomedical, personal, behavioral, social, contextual, environmental, and organizational data to maximize inferences that can be derived from the data.


• Novel multimodal sensor system hardware: This theme addresses the need for new multimodal sensing systems/platforms and analytics to generate predictive and personalized models of health.


• Effective Usability: To generate technology that is usable and effective will require development of new approaches, taking into account ethical, behavioral and social considerations, to support individuals to effectively participate in their own health, diagnosis, and treatment, such as personalized information systems, personalized and dynamic treatment, accessing and visualizing health data and knowledge that support users across socio-economic status, digital and health literacy, technology and broadband access, geography, gender, and ethnicity.


• Automating Health: This theme supports work that enables interoperable, temporally synchronized, devices and systems to connect data and devices and create closed-loop or human-in-the-loop systems to assess, treat and reduce adverse health events.


• Medical image interpretation. This theme's goal is to determine how characteristics of human pattern recognition, visual search, perceptual learning, attentional biases, etc. can inform and improve use and development of presentation modalities (e.g., pathologists reading optical slides through a microscope vs. digital whole-slide imagery) and identify the sources of inter- and intra-observer variability in medical image interpretation.


• Unpacking health disparities. In this theme, proposals should seek to develop holistic, data-driven or mathematical models to address the structural and/or social determinants of health. The above listed themes are to provide examples for possible research activities that may be supported by this solicitation, but by no means should the proposed research activities be restricted to these themes. These research themes are clearly not mutually exclusive, and a given project may address multiple themes.

• Collaborative Research in Computational Research in Neuroscience (CRCNS)


• Integrative Strategies for Understanding Neural and Cognitive Systems (NCS)


• Predictive Intelligence for Pandemic Prevention Phase I: Development Grants (PIPP Phase I)


• Semiconductor Synthetic Biology Program (SemiSynBio)


• Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)

ENG Interdisciplinary Programs

• Predictive Intelligence for Pandemic Prevention Phase I: Development Grants (PIPP Phase I)


• Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)

• Ecology and Evolution of Infectious Diseases (EEID)

The Division of Chemistry (CHE) supports fundamental chemistry research that focuses on development of new chemical sensing and imaging tools for diagnostics or monitoring of bacterial and viral infections, as well as of novel approaches for understanding the underpinning molecular mechanisms and subsequent mitigating strategies against EIDs and future pandemics. For example, the successful development of mRNA vaccines has required and will continue to require fundamental research in unnatural nucleic acids as well the use of custom lipid synthesis for storage and biological delivery. For this meta-program, the most relevant programs in the CHE Division are: Chemical Measurement and Imaging (CMI), Chemistry of Life Processes (CLP), and Chemical Synthesis (SYN).

Participating Program description:

Chemical Measurement and Imaging (CMI): The Chemical Measurement and Imaging Program supports work advancing new measurement science enabling capabilities likely to be of use to the chemistry community. New approaches and/or improved understanding of important existing approaches are supported. Envisioned applications - including health-related applications - can contribute to the broader impacts but should not be the primary focus. Adaptation and/or optimization of existing methods for specific applications should be directed elsewhere.

Chemistry of Life Processes (CLP): The Chemistry of Life Processes Program supports fundamental research at the interface of chemistry and biology that advances the understanding of the molecular underpinnings of life processes. These processes include those involved in the emergence and transmission of infectious diseases and in disease detection, diagnostics, and therapeutics. For example, new chemical probes and characterization strategies can be applied to the study of the structure and dynamics of viral RNA and of proteins and enzymes required for viral infectivity and replication, which in turn can provide target sites for new therapeutics.

Chemical Synthesis (SYN): The Chemical Synthesis (SYN) program in the Division of Chemistry encourages submission of proposals that target the synthesis of novel bioactive molecules, including metalloantibiotics, with potential for applications in infectious disease research. Such projects may involve the development of new methodology for the assembly of chemical structures for selective biorecognition, utilization of chemoenzymatic approaches for elaboration of bioactive compounds, and design of organic compounds and/ormetalloantibiotics that target specific cell membranes. Collaborative proposals with multiple PIs that partner fundamental chemical synthesis with programs in infectious disease research are especially encouraged.

The Mathematical Biology program in the Division of Mathematical Sciences (DMS) supports many research projects closely related to EID including mathematical modeling the development of innovative mathematical frameworks of emerging and reemerging infectious diseases. Some of these projects involve close collaborations of mathematicians with epidemiologists, immunologists, public health professionals and policymakers. Specific research topics range from short-term forecast of disease outbreaks to fundamental understanding of long-term behavior of pathogen evolution and disease characteristics. Other topics include cell-pathogen interactions at within-host level to host-pathogen dynamics and transmission at population and community levels. Additionally, some projects involve coupling of biological processes at multiple temporal and spatial scales, using mathematical/statistical/computational tools and theories with various modeling approaches most appropriate for addressing the biological questions. Also, recent projects include potentially transformative research concerning the incorporation of human social, behavioral, and economic processes into mathematical epidemiological models.

Other programs within DMS, including Statistics and Computational Mathematics, also support research projects pertaining to EID.

DMS is involved in the EEID (Ecology and Evolution of Infectious Diseases) program and plans to co-fund research projects that include strong mathematical components for addressing important questions related to modeling of infectious diseases. The joint DMS/NIGMS initiative also supports research related to infectious diseases that may lead to a more general understanding of the underlying problems and have broader applicability (as opposed to applications to a specific disease).

The programs mentioned above focus on individual or small group research projects. A new solicitation in which DMS plays a key role, National Institute for Theory and Mathematics in Biology (NITMB), aims at larger and more interdisciplinary research activities. One of the topics for this solicitation is Infectious Pathogens: Immunology and Transmission. The research topics include modeling the evolutionary outcomes of host-pathogen interactions as dynamically coupled immunological and epidemiological processes. This is a grand challenge, particularly when models incorporate heterogeneities in attributes such as pathogen virulence, host defense mechanisms, and human intervention. New mathematical theory and modeling approaches are needed for exploring emergent properties of infectious pathogens, uncovering principles in immunology, and predicting effects on pathogen transmission dynamics, especially in the presence of multiple scales of time, space, and biological processes within changing environments.

• Ecology and Evolution of Infectious Diseases (EEID)


• Incorporating Human Behavior in Epidemiological Models (IHBEM)

• Integrative Activities administers NSF-wide programs such as Science and Technology Centers, Major Research Instrumentation, Mid-scale Research Infrastructure - Track 1, and Historically Black Colleges and Universities - Excellence in Research

• The Established Program to Stimulate Competitive Research (EPSCoR) Section enhances research competitiveness of targeted jurisdictions (states, territories, commonwealth) by strengthening STEM capacity

• The Evaluation and Assessment Capability (EAC) Section, which provides centralized support and resources for data collection, analytics, and the design of evaluation studies and surveys. These activities enable NSF to more consistently evaluate the impacts of its investments, to make more data-driven decisions, and to establish a culture of evidence-based planning and policymaking.

• Ecology and Evolution of Infectious Diseases (EEID)


• Predictive Intelligence for Pandemic Prevention Phase I: Development Grants (PIPP Phase I)


• Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)


• Incorporating Human Behavior in Epidemiological Models (IHBEM)

• Dynamics of Integrated Socio-Environmental Systems (DISES)


• Ecology and Evolution of Infectious Diseases (EEID)


• Plant-Biotic Interactions


• Symbiosis, Infection, and Immunity


• Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)


• Predictive Intelligence for Pandemic Prevention (PIPP)


• Incorporating Human Behavior in Epidemiological Models (IHBEM)