# data[].attributes.title
Collaborative Research: MODULUS: Stochastic reaction-diffusion equations on metric graphs and spatially-resolved dynamics of virus infection spread

# data[].attributes.abstract
This award supports the development of new mathematical tools and biological experiments that are essential to understanding the mechanisms of virus spread and extinction. A new framework, to enable an integrated experimental-mathematical study, will be developed to control the spatial distribution of the host cell population and to quantify how such spatial structure affects viral evolution and decay. The project has basic research, medical, and public health impact, since the analytical and experimental methods can be extended to elucidate mechanisms of infection spread by viruses of public health importance, including influenza A virus, Zika virus, and coronaviruses. As an interdisciplinary study, the research will cross-train mathematicians, biologists, and engineers, contributing significantly to workforce development. Broader objectives include increased participation and diversity in STEM fields while promoting a broader understanding of science and technology by the public through wide dissemination.      The project goal is to determine both the probability of virus extinction during infection spread and the spreading speed in terms of the spatial structure of host cell populations. A new mathematical framework, stochastic reaction-diffusion equations on metric graphs, will be developed to study the dynamics of virus infections over any network structure. The biological experiments are cutting edge: virus infections will be performed on micro-patterned host cells that enable quantification of population level features of infection spread in any network structure, a key advantage over traditional Petri-dish studies. Analysis of the experimentally informed stochastic equations has the potential to push the frontier of current knowledge about the role of space and stochasticity in population dynamics. This new framework motivates problems that cut across several mathematical disciplines (probability, partial differential equations and mathematical biology) and that are of interest to a large group of applied mathematicians and applied scientists. These problems include (i) What is the probability of extinction of virus and the propagation speed in terms of geometric properties of the metric graph, such as the branching structure and the edge lengths of the graph? (ii) What is the probability of coexistence of virus and defective interfering particles during co-infection spread, and the effect of the underlying spatial structure on this probability? The project brings new probabilistic tools and perspectives to solve these problems and to generate mechanistic insights about virus infection spread.     This award is being co-funded by the MPS Division of Mathematical Sciences (DMS) through the Mathematical Biology Program and by the Division of Molecular and Cellular Biosciences (MCB) through the Systems and Synthetic Biology and the Cellular Dynamics and Function Cluster.    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.

# data[].attributes.title
STTR Phase I: Room Temperature Stable, Dry Powder Particle-Based Vaccines Against Influenza

# data[].attributes.funder_divisions[]
Technology, Innovation and Partnerships (TIP)

# data[].attributes.abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to demonstrate room-temperature-stable, dry powder inhalable influenza vaccines represent as an innovative, next generation technology to promote the health and welfare of the American public by eliminating the existing pain points of current influenza vaccines. The global influenza vaccine market size is projected to increase to $17.77 billion by 2032. Therefore, the demand for innovative vaccines against seasonal respiratory viruses remains a high priority. These dry powder vaccines introduce a transformative innovation – induction of durable protective immunity that targets both the upper and lower airways via nasal delivery and removing the cold chain due to room-temperature shelf stability, thereby lowering vaccine costs and wastage. This outcome can result in cost savings of up to 80%. The economic and social benefits of this vaccine technology will lead to achieving and maintaining a significant market share of the flu vaccine market. Additionally, this technology’s plug-and-play capability allows swapping pathogen-specific proteins and creating new inhalable room-temperature-stable vaccines for other respiratory pathogens. Altogether, this advance will significantly lower storage costs while improving our nation’s strategic preparedness in stockpiling vaccines against circulating disease, emerging threats, or biowarfare agents.    This Small Business Technology Transfer (STTR) Phase I project will demonstrate the feasibility of producing a novel room-temperature-stable, dry-powder inhalable influenza vaccine and using a new scalable process to manufacture the vaccine. Current flu shots do not provide lung-specific immune responses and require refrigerated storage. This project’s value proposition is to replace current needle-in-the-arm, partially effective flu shots with next-generation vaccines and delivery methods. This project enables the risk-reducing R&D needed to advance a dry powder vaccine manufacturing technology called Payload Reduction and Encapsulation Technology (PRET). The goal is to demonstrate feasibility of this manufacturing method by showing dry powder influenza vaccines synthesized by PRET result in reproducible dry powder vaccine characteristics, high vaccine yields, protection against influenza infection, and room-temperature shelf stability. There are three objectives that will be pursued to demonstrate this: 1) feasibility of achieving initial pilot-scale production and characterization of dry powder influenza vaccines using PRET; 2) dry powder influenza vaccine efficacy compared to traditional flu vaccines; and 3) production of influenza particle-based vaccines using scaled-up engineering runs and evaluation of room-temperature shelf-life. The new paradigm represented by room-temperature-stable, dry powder vaccines has the potential to transform the vaccine-delivery landscape and enhance the nation’s pandemic preparedness.    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.

# data[].attributes.title
Strengthening Rural STEM Education: An Evidence-Based Framework for Increasing Student Success

# data[].attributes.abstract
With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Institutional Transformation project aims to develop and implement a comprehensive model for transforming STEM education at a rural institution serving local communities. The project will address academic achievement gaps in STEM fields by fostering strong STEM identities at both institutional and student levels. This work is especially timely as rural, community-based institutions face unique challenges in retaining STEM students, particularly following the COVID-19 pandemic's disproportionate impact on college-level preparedness. The project will transform institutional culture through structured dialogue between leadership and STEM stakeholders, professional development for administration, and increased leadership engagement in student-centered STEM events. Through this dual approach of institutional transformation and evidence-based teaching practices, the project will contribute new understanding of how community-based institutions can effectively support all students while preparing them for the global STEM workforce. Through innovative programming and teaching practices, this work will create a model for other institutions across the United States to follow.     The project will pursue two complementary objectives: i) enhancing STEM identity in institutional leadership to transform student support networks, and ii) developing innovative experiential learning opportunities across STEM disciplines. Two primary research questions will guide this work: how backgrounds and experiences found in community-based institutions influence STEM identity development, and what knowledge transfer approaches effectively help students develop STEM identities in varied educational contexts. The project will employ multiple research methods including Photovoice documentation during international experiences, reflective student journaling, traditional storytelling approaches during research fellowships, and semi-structured interviews with institutional leaders. Specific interventions include Undergraduate Research Fellowships fostering mentored research experiences and the global interconnectedness of STEM, and comprehensive academic support systems with early intervention strategies. The project will advance the field by generating new knowledge about institutional transformation in rural higher education settings, particularly regarding the relationship between institutional STEM identity and student success. Expected broader impacts include developing a model for mutual exchange between institutional leadership and students that can inform STEM policy development at other institutions, creating a guide for building community-based programs that benefit both students and their surrounding communities in both regional and international settings, and increasing the number of STEM graduates prepared for the workforce. Results will be disseminated through publications in undergraduate education journals, conference presentations, and through the NSF HSI Program Network Resource Centers and Hubs. The HSI Program aims to enhance undergraduate STEM education and build capacity at HSIs. Projects supported by the HSI Program will also generate new knowledge on how to achieve these aims.    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.

# data[].attributes.title
Integrating Soft Skills with Technical Skills to Produce Next-Generation Cybersecurity Technicians

# data[].attributes.abstract
This project aims to serve the national interest by producing more qualified technicians to meet workforce demands in cybersecurity. Keeping computers and information systems secure is a critical need and a major challenge in business, industry, and government. The growth of cyber-threats has created a need for many more workers who have the knowledge and skills to protect both existing and emerging technologies. Research and feedback from employers indicate that although graduates of cybersecurity programs are generally well-prepared technically, their soft skills remain underdeveloped. (This issue was exacerbated by primarily virtual interactions and remote work during the COVID-19 pandemic.) To address this gap, the investigators intend to integrate the targeted development of soft skills into core cybersecurity courses through structured team-based activities, simulations, and competition-style challenges.    The project will focus on five competencies that cybersecurity professionals need in the workplace: communication, critical thinking, problem-solving, continuous learning, and attention to detail. The Business & Industry Leadership Team (BILT) that advises the college's cybersecurity program prioritized these soft skills for attention. The project team will directly embed them into course activities, assignments, and assessments. Specifically, the investigators aim to revise four existing cybersecurity courses -- Introduction to Cyber Crime, Introduction to Protocol Analysis, Security Administration, and Ethical Hacking with Python I -- to include mini-modules and challenge-based team assignments focusing on soft skills. Each course will focus on one or two of the five targeted soft skills, ensuring that each one is addressed in-depth within a technical context. Examples include group-based incident response briefings to strengthen communication and professionalism; packet analysis and network troubleshooting activities completed in teams to promote teamwork and problem-solving; and adaptive policy response scenarios that encourage flexibility and resilience. Each course will include clear learning outcomes, soft skill rubrics, and feedback mechanisms to assess both technical and interpersonal development. In addition, the investigators aim to establish a student cybersecurity competition team as a co-curricular activity and to bring elements of cyber-competition into the classroom for all students. Those activities will include in-class simulations modeled on capture-the-flag or red team/blue team competitions; structured team challenges with rotating roles to develop communication and adaptability; and opportunities for reflection and instructor feedback following simulations or live drills. By embedding a focused set of soft skills into core technical coursework and grounding students' experience in competition-style, gamified team activities, the redesigned cybersecurity program will provide a coherent, high-impact approach to cybersecurity education that aligns with workforce needs and promotes student success. This project is funded by the Advanced Technological Education program, which focuses on the education of technicians for the advanced-technology fields that drive the nation's economy.    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.

# data[].attributes.title
The geography of H5N1 avian influenza in the United States: Human-environment ecosystem drivers of transmission and viral evolution

# data[].attributes.awardee_organization.name
University of North Carolina at Chapel Hill

# data[].attributes.abstract
This project investigates how avian influenza (bird flu) spreads and undergoes genetic changes and identifies the key factors driving these genetic changes and spread. It elicits the spatial and genetic patterns of avian influenza in birds, mammals, and humans, aiming to assess the pandemic potential of this virus, which has had a 50% mortality rate in people infected during the past 30 years. Understanding the risk of spillover to humans requires a comprehensive understanding of the influenza ecosystem, an interconnected network of factors involving humans, animals, and the environment. The findings are being organized into a database for public access to support translation of what is learned from the project to practice by informing and optimizing measures to mitigate both the economic impacts on the agricultural sector, a core sector of the bioeconomy, and the public health risks posed by emerging influenza variants.      This study aims to understand the genetic evolution of avian influenza, particularly a highly pathogenic H5N1 virus lineage over time and identify the ecological factors that drive human infections and viral change. Central to the study is a systematic analysis and characterization of the spatiotemporal distributions of viral genotypes and their genetic divergence from precursor avian influenza viruses. It leverages advanced geospatial modeling, machine learning, and geospatial artificial intelligence (GeoAI) techniques to identify key viral traits, such as transmission potential and virulence, and to elucidate geographic ecosystem factors that influence the spread and evolution of the virus. The study generates a publicly available database that integrates information on more than 20,000 avian influenza viruses with associated human-animal-environment ecosystem variables. This database subserves translational support for research and private-sector preparedness.    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.

# data[].attributes.title
Collaborative Research: eMB: The immunological signature of a changing world: mathematical models to infer historical patterns of infectious disease

# data[].attributes.funder_divisions[]
Mathematical and Physical Sciences (MPS)

# data[].attributes.abstract
Spillover of infectious diseases from wildlife to humans and livestock is a pervasive risk to the health and welfare of human populations around the world. Effective management of this risk is facilitated by early detection of changes in the frequency of spillover events.  This research will develop new mathematical models and statistical methods that allow changes in the rate of spillover to be detected from the fossil record of past infection that remains imprinted on human and animal immune systems. The general methodology developed by this project will be rigorously tested using simulated data and applied to Rift Valley fever virus, a pathogen that poses a high risk of global expansion with potentially devastating consequences for human health and agriculture. Work on this project will train students in cutting edge mathematical and statistical methods and support an international workshop where software developed by the project will be introduced and instruction on its use provided.       Predicting how zoonotic infectious diseases change over time is a fundamentally important challenge with few general mathematical solutions. Central to addressing this problem is disentangling historical changes in the rate or “force” of spillover from background biological processes, such as age-specific infection and wanning immunity, which can cloak or mimic the signal of temporal change. Existing statistical methods to infer historical changes in the force of spillover for zoonotic pathogens rely on piecemeal solutions tailored to specific scenarios, ignore interacting background processes, use only single immunological markers, and have failed to rigorously evaluate parameter identifiability. To fill this gap, this project will develop a general mathematical framework describing the probability that an individual is in a specific multivariate immune state as a function of age and time using a coupled system of partial differential equations (PDEs). Approximate and numerical solutions to this system of PDEs will enable a Bayesian statistical framework for inferring recent historical changes in the force of spillover in the presence of alternative biological processes. Testing this statistical framework using extensive, biologically realistic simulated datasets will allow the identifiability of historical change in force of spillover to be evaluated. Application of this methodology to Rift Valley fever virus, a pathogen with significant pandemic potential, will determine whether increasing case counts in East Africa result from fundamental shifts in disease epidemiology or from increased disease surveillance.    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.

# data[].attributes.title
Collaborative Research: eMB: The immunological signature of a changing world: mathematical models to infer historical patterns of infectious disease

# data[].attributes.funder_divisions[]
Mathematical and Physical Sciences (MPS)

# data[].attributes.abstract
Spillover of infectious diseases from wildlife to humans and livestock is a pervasive risk to the health and welfare of human populations around the world. Effective management of this risk is facilitated by early detection of changes in the frequency of spillover events.  This research will develop new mathematical models and statistical methods that allow changes in the rate of spillover to be detected from the fossil record of past infection that remains imprinted on human and animal immune systems. The general methodology developed by this project will be rigorously tested using simulated data and applied to Rift Valley fever virus, a pathogen that poses a high risk of global expansion with potentially devastating consequences for human health and agriculture. Work on this project will train students in cutting edge mathematical and statistical methods and support an international workshop where software developed by the project will be introduced and instruction on its use provided.       Predicting how zoonotic infectious diseases change over time is a fundamentally important challenge with few general mathematical solutions. Central to addressing this problem is disentangling historical changes in the rate or “force” of spillover from background biological processes, such as age-specific infection and wanning immunity, which can cloak or mimic the signal of temporal change. Existing statistical methods to infer historical changes in the force of spillover for zoonotic pathogens rely on piecemeal solutions tailored to specific scenarios, ignore interacting background processes, use only single immunological markers, and have failed to rigorously evaluate parameter identifiability. To fill this gap, this project will develop a general mathematical framework describing the probability that an individual is in a specific multivariate immune state as a function of age and time using a coupled system of partial differential equations (PDEs). Approximate and numerical solutions to this system of PDEs will enable a Bayesian statistical framework for inferring recent historical changes in the force of spillover in the presence of alternative biological processes. Testing this statistical framework using extensive, biologically realistic simulated datasets will allow the identifiability of historical change in force of spillover to be evaluated. Application of this methodology to Rift Valley fever virus, a pathogen with significant pandemic potential, will determine whether increasing case counts in East Africa result from fundamental shifts in disease epidemiology or from increased disease surveillance.    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.

# data[].attributes.title
Collaborative Research: SaTC: EDU: A Socially-Distant Cloud-Based Hardware Security Educational Platform

# data[].attributes.abstract
The main goal of this project is to develop and deliver remote experiments utilizing cloud-based resources aimed at educating a broad audience of students and practitioners in hardware security. In the post-COVID era, it is imperative to develop online education platforms for remote training of both students and the workforce in the field of Hardware Security. Recent advances in this field and FPGA-based cloud servers have enabled an opportunity to move related experiments to an online format that only requires a standard computer and internet connection by the students. Teaching “hardware” security in a socially distanced format poses significant challenges. Essential experiments for teaching key concepts in hardware security necessitate multiple evaluation boards and physical equipment such as voltage supplies, oscilloscopes, multimeters, and function generators. To adapt these experiments for an online platform, the project will explore innovative methods to execute or emulate them using the cloud ecosystem. This project addresses a critical gap by developing a fully online hardware security training module accessible to students and professionals worldwide.     This project proposes various comprehensive experiments testing different notions in hardware security. The framework will be designed for both undergraduate and graduate students in the electrical engineering, computer engineering, and computer science departments, leveraging courses developed by the PIs in their respective institutions. The proposed infrastructure includes preparing detailed experiments for instructors with walkthrough documents and organizing student assignments for independent completion. This setup supports not only teaching but also facilitates independent research upon assignment completion. Supplemented with video instructions, these experiments will constitute a comprehensive training module, equipping participants with the necessary skills and knowledge to address complex challenges in this emerging domain, thereby instilling preparedness and confidence.     This award is co-funded by the NSF Improving Undergraduate STEM Education (IUSE: EDU) Program. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is further supported by the Secure and Trustworthy Cyberspace (SaTC) program, which funds proposals that address cybersecurity and privacy, and in this case, cybersecurity education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.    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.

# data[].attributes.title
Collaborative Research: Belmont Forum Collaborative Research: BIOrepositories build Adaptive and Resilient Capacity (BioARC)

# data[].attributes.abstract
This award provides support to U.S. researchers participating in a project competitively selected by a 55-country initiative on global change research through the Belmont Forum. The Belmont Forum is a consortium of research funding organizations focused on support for transdisciplinary approaches to global environmental change challenges and opportunities. It aims to accelerate delivery of the international research most urgently needed to remove critical barriers to sustainability by aligning and mobilizing international resources. Each partner country provides funding for their researchers within a consortium to alleviate the need for funds to cross international borders. This approach facilitates effective leveraging of national resources to support excellent research on topics of global relevance best tackled through a multinational approach, recognizing that global challenges need global solutions.    Working together in this Collaborative Research Action, the partner agencies have provided support to foster global transdisciplinary research teams of natural, health and social scientists and stakeholders from across the globe to improve understanding of climate, environment and health pathways to protect and promote health. The projects will provide crucial new understanding into the health implications arising from the impacts of climate change and variability on; 1) decision-science approaches to adaptation and implementation, 2) food, environment, and biological security and 3) risks to ecosystems and populations. This award provides support for the U.S. researchers to cooperate in consortia that consist of partners from at least three of the participating countries to increase our knowledge of the complex linkages and pathways between the climate, environment and health to help solve complex challenges that face societies.    The BioARC project seeks to develop an interdisciplinary network of scientists, health professionals, and stakeholders to build the missing physical, human, and material infrastructure to stop pandemics at their source. These various forms of infrastructure will be centered on the development of multiple in-country biorepositories spread throughout The Americas, where pathogens with pandemic potential (e.g., Zika, Andes Virus) and neglected tropical diseases (e.g., Dengue, Chagas, and hookworm infection) have previously emerged and spread. This new infrastructure will provide the critical spatial, temporal, and taxonomic sampling and associated informatics necessary to understand the role of environmental drivers in host-pathogen dynamics, enabling a more proactive and predictive approach to pathogen emergence.  This project directly addresses a critical challenge to pandemic preparedness.  COVID-19 directly illustrated the high costs of pandemics to human wellbeing and the persistent gaps in our approach to preventing pathogen emergence. As humans and wildlife increasingly share space, opportunities for spillovers grow. Additionally, environmental stresses can cause wildlife to shed pathogens more readily as stress induced by things like habitat loss, heat exposure, or food scarcity decreases immune functionality that would typically keep pathogen shedding low.  The project will focus on improving biorepository infrastructure including equipment and databases.  The project team will develop training modules on museum science, fieldwork, molecular genetics, informatics, geospatial data analysis, science communication, and interdisciplinary network development.  The project will develop best practices for biorepositories and relational databases for pathogens, interdisciplinary workflows for wildlife pathogen surveillance, communication across One Health disciplines, and strategies for biorepository decision-maker coordination. The goal of developing best practices is to enable the standardization of procedures for similar efforts locally and globally, and to form the foundation for an early-warning system for zoonotic diseases that will improve U.S. national security and build the U.S. workforce.  The project will reduce costs of outbreak response by creating the capacity and data to establish baselines for wildlife pathogen dynamics, detecting deviations from these baselines, informing models, and enabling timely biosecurity decisions. The project will develop a robust, enduring system to safeguard human and animal populations from infectious diseases.    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.

# data[].attributes.title
Collaborative Research: Belmont Forum Collaborative Research: BIOrepositories build Adaptive and Resilient Capacity (BioARC)

# data[].attributes.abstract
This award provides support to U.S. researchers participating in a project competitively selected by a 55-country initiative on global change research through the Belmont Forum. The Belmont Forum is a consortium of research funding organizations focused on support for transdisciplinary approaches to global environmental change challenges and opportunities. It aims to accelerate delivery of the international research most urgently needed to remove critical barriers to sustainability by aligning and mobilizing international resources. Each partner country provides funding for their researchers within a consortium to alleviate the need for funds to cross international borders. This approach facilitates effective leveraging of national resources to support excellent research on topics of global relevance best tackled through a multinational approach, recognizing that global challenges need global solutions.    Working together in this Collaborative Research Action, the partner agencies have provided support to foster global transdisciplinary research teams of natural, health and social scientists and stakeholders from across the globe to improve understanding of climate, environment and health pathways to protect and promote health. The projects will provide crucial new understanding into the health implications arising from the impacts of climate change and variability on; 1) decision-science approaches to adaptation and implementation, 2) food, environment, and biological security and 3) risks to ecosystems and populations. This award provides support for the U.S. researchers to cooperate in consortia that consist of partners from at least three of the participating countries to increase our knowledge of the complex linkages and pathways between the climate, environment and health to help solve complex challenges that face societies.    The BioARC project seeks to develop an interdisciplinary network of scientists, health professionals, and stakeholders to build the missing physical, human, and material infrastructure to stop pandemics at their source. These various forms of infrastructure will be centered on the development of multiple in-country biorepositories spread throughout The Americas, where pathogens with pandemic potential (e.g., Zika, Andes Virus) and neglected tropical diseases (e.g., Dengue, Chagas, and hookworm infection) have previously emerged and spread. This new infrastructure will provide the critical spatial, temporal, and taxonomic sampling and associated informatics necessary to understand the role of environmental drivers in host-pathogen dynamics, enabling a more proactive and predictive approach to pathogen emergence.  This project directly addresses a critical challenge to pandemic preparedness.  COVID-19 directly illustrated the high costs of pandemics to human wellbeing and the persistent gaps in our approach to preventing pathogen emergence. As humans and wildlife increasingly share space, opportunities for spillovers grow. Additionally, environmental stresses can cause wildlife to shed pathogens more readily as stress induced by things like habitat loss, heat exposure, or food scarcity decreases immune functionality that would typically keep pathogen shedding low.  The project will focus on improving biorepository infrastructure including equipment and databases.  The project team will develop training modules on museum science, fieldwork, molecular genetics, informatics, geospatial data analysis, science communication, and interdisciplinary network development.  The project will develop best practices for biorepositories and relational databases for pathogens, interdisciplinary workflows for wildlife pathogen surveillance, communication across One Health disciplines, and strategies for biorepository decision-maker coordination. The goal of developing best practices is to enable the standardization of procedures for similar efforts locally and globally, and to form the foundation for an early-warning system for zoonotic diseases that will improve U.S. national security and build the U.S. workforce.  The project will reduce costs of outbreak response by creating the capacity and data to establish baselines for wildlife pathogen dynamics, detecting deviations from these baselines, informing models, and enabling timely biosecurity decisions. The project will develop a robust, enduring system to safeguard human and animal populations from infectious diseases.    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.