NATIONAL BIOSURVEILLANCE 

SCIENCE AND TECHNOLOGY 

ROADMAP

Executive Office of the President

National Science and Technology Council

JUNE 2013
NATIONAL BIOSURVEILLANCE 

SCIENCE AND TECHNOLOGY 

ROADMAP
EXECUTIVE OFFICE OF THE PRESIDENT

OFFICE OF SCIENCE AND TECHNOLOGY POLICY

WASHINGTON, D.C. 20502

June 14, 2013

Dear Colleague,

I am pleased to transmit the National Biosurveillance Science and Technology Roadmap, 

which identifies and prioritizes research and development (R&D) needs with the goal of 

giving decision makers at all levels of government more accurate and timely information 

when biological incidents threaten health.

Such incidents—whether the result of natural evolutionary causes, accidental releases or

exposures, or malevolent activities—have the potential to erupt suddenly and evolve quickly.

Surveillance can be key to predicting and even preventing such incidents, and can help 

minimize the impacts of incidents that cannot be prevented.

The Roadmap builds upon the National Strategy for Biosurveillance, published in July 2012,

which recognized that a well-integrated national biosurveillance enterprise can save lives by

providing essential information for better decision making. Drafted by the interagency

Biosurveillance Science and Technology Working Group under the National Science and

Technology Council’s Committee on Homeland and National Security, the Roadmap

identifies R&D priorities to enable the Core Functions of the Strategy.

The Obama Administration is committed to working toward the achievement of these highpriority R&D objectives and to realizing the integrated biosurveillance enterprise called for 

in the Strategy. Success will require coordination across Federal organizations, academia, 

industry, and the international community. The benefit for the health and security of all 

Americans and indeed all the world’s people makes the needed effort extremely worthwhile.
About the National Science and Technology Council

The National Science and Technology Council (NSTC) is the principal means through which the 

Executive Branch coordinates science and technology (S&T) policy across the diverse Federal 

research and development (R&D) enterprise. The NSTC prepares R&D strategies that are 

coordinated across Federal agencies to form investment packages aimed at accomplishing 

multiple national goals. The work of the NSTC is organized under five committees: 

Environment, Natural Resources and Sustainability; Homeland and National Security; Science, 

Technology, Engineering, and Math Education; Science; and Technology. More information is 

available at http://www.whitehouse.gov/ostp/nstc.

About the Office of Science and Technology Policy

The Office of Science and Technology Policy (OSTP) was established by law in 1976. OSTP’s 

responsibilities include advising the President on S&T policy; articulating the President’s S&T

views; and fostering strong partnerships among Federal, state, and local governments, and the 

scientific communities in industry and academia. The Director of OSTP also serves as Assistant 

to the President for S&T and manages the NSTC. More information is available at 

http://www.whitehouse.gov/ostp.

About the Subcommittee on Biological Defense Research and Development (BDRD)

The purpose of the BDRD is to provide all relevant Federal agencies a focused forum for

coordinating and collaborating on defensive research, development, testing, and evaluation

addressing biological threats to national security, including known biological threats

(bacteria/viruses/fungi/toxins) and emerging infectious disease agents that have the potential to

significantly affect the environment, plants, animals, and humans both within the United States

and throughout the globe. The BDRD has five working groups, including biosurveillance, 

biological response and recovery, foreign animal diseases, microbial forensics, and biorisk 

management. This document was developed by the Biosurveillance Science and Technology 

Working Group (BST WG).

Copyright Information

This document is a work of the United States Government and is in the public domain (see 17 

U.S.C. §105). Subject to the stipulations below, it may be distributed and copied with 

acknowledgment to OSTP. Copyrights to graphics included in this document are reserved by the

original copyright holders or their assignees and are used here under the government’s license 

and by permission. Requests to use any images must be made to the provider identified in the 

image credits or to OSTP if no provider is identified. 
Report prepared by

NATIONAL SCIENCE AND TECHNOLOGY COUNCIL

COMMITTEE ON HOMELAND AND NATIONAL SECURITY 

SUBCOMMITTEE ON BIOLOGICAL DEFENSE RESEARCH AND DEVELOPMENT 

BIOSURVEILLANCE SCIENCE AND TECHNOLOGY WORKING GROUP

National Science and Technology Council

Chair Staff

John P. Holdren Pedro I. Espina (through May 31, 2013)

Assistant to the President for Science and Executive Director

Technology and Director, Jayne Morrow (beginning June 1, 2013)

Office of Science and Technology Policy Executive Director 

Committee on Homeland and National Security

Chairs

Patricia A. Falcone Tara O’Toole

Associate Director for National Security Undersecretary of Homeland Security for 

and International Affairs Science and Technology 

Office of Science and Technology Policy Department of Homeland Security

Alan R. Shaffer Staff

Acting Assistant Secretary of Defense for Susan Law

Research and Engineering Executive Secretary

Department of Defense Department of Homeland Security

Subcommittee on Biological Defense Research and Development

Chair Staff

Franca R. Jones Jayne Morrow (through May 31, 2013)

Office of Science and Technology Policy National Institutes of Standards and Technology

Department of Commerce
Biosurveillance Science and Technology Working Group

Co-Chair Co-Chair

Franca R. Jones Jason W. Roos

Office of Science and Technology Policy Joint Program Executive Office for Chemical 

and Biological Defense

Department of Defense

Members

Pat Basu Department of Agriculture 

Cyril Gay Department of Agriculture – Agricultural Research Service 

Russ Bulluck Department of Agriculture – Animal and Plant Health Inspection

Service

Mark Teachman Department of Agriculture – Animal and Plant Health Inspection

Service

Chris Miller Department of Commerce – National Oceanic and Atmospheric 

Administration

Geoff Scott Department of Commerce – National Oceanic and Atmospheric 

Administration

Roger Breeze Department of Defense – Defense Threat Reduction Agency Joint 

Science and Technology Office

Margaret Sobey Department of Defense – Joint Program Executive Office for 

Chemical and Biological Defense

Clay Holloway Department of Defense – Office of the Assistant Secretary of 

Defense for Nuclear, Chemical, and Biological Defense Programs

Robert von Tersch Department of Defense – Office of the Assistant Secretary of 

Defense for Nuclear, Chemical, and Biological Defense Programs

Steve Niehoff Department of Defense – Office of the Secretary of Defense for 

Health Affairs

Glenn Dowling Department of Defense – National Center for Medical Intelligence

Luther Lindler Department of Defense – Armed Forces Health Surveillance 

Center

Kevin Russell Department of Defense – Armed Forces Health Surveillance 

Center

Phil LoBue Department of Health and Human Services – Centers for Disease 

Control and Prevention

Sally Hojvat Department of Health and Human Services – Food and Drug 

Administration

Taha Kass-Hout Department of Health and Human Services – Food and Drug 

Administration

Carole Heilman Department of Health and Human Services – National Institutes of 

Health

Rodney Wallace Department of Health and Human Services – Office of the 

Assistant Secretary for Preparedness and Response – Biomedical 

Advanced Research and Development Authority
Steve Bennett Department of Homeland Security – Office of Health Affairs –

National Biosurveillance Integration Center

Anne Hultgren Department of Homeland Security – Science and Technology 

Directorate

Segaran Pillai Department of Homeland Security – Science and Technology 

Directorate

Kay Briggs Department of the Interior 

Robert Bull Department of Justice – Federal Bureau of Investigation 

Andrew Hebbler Department of State

Brian Nordmann Department of State

Jessica Petrillo Department of State

Debra Gulick Department of State 

Robert Sorenson Department of State

Lynn Slepski Department of Transportation

Shantini Gamage Department of Veterans Affairs

Gary Roselle Department of Veterans Affairs

Peter Jutro Environmental Protection Agency

Sanjiv Shah Environmental Protection Agency

Tom Bates Lawrence Livermore National Laboratory

John Haynes National Aeronautics and Space Administration

David Liskowsky National Aeronautics and Space Administration

Charles Liarakos National Science Foundation

Scott Miller Smithsonian Institution

Dennis Carroll U.S. Agency for International Development
Acronyms and Abbreviations 

APHIS Animal and Plant Health Inspection Service

BDRD Biological Defense Research and Development

BIWAC Biosurveillance Indications and Warning Analytic Community

BSP Biosurveillance Portal

BST WG Biosurveillance Science and Technology Working Group

BSV Biosurveillance

CAPS Cooperative Agricultural Pest Survey

CDC Centers for Disease Control and Prevention

DHS Department of Homeland Security

DoD Department of Defense

DOI Department of the Interior

DTRA Defense Threat Reduction Agency

EIP Emerging Infection Programs

EROS Earth Resources Observation and Science 

ESSENCE Electronic Surveillance System for Early Notification of Community-based 

Epidemics

FDA Food and Drug Administration

HHS U.S. Department of Health and Human Services

HSPD Homeland Security Presidential Directive

ICLN Integrated Consortium of Laboratory Networks

LRN Laboratory Response Network

NAHLN National Animal Health Laboratory Network

NAHMS National Animal Health Monitoring System

NBIC National Biosurveillance Integration Center

NBIS National Biosurveillance Integration System

NCMI National Center for Medical Intelligence 

NEON National Ecological Observatory Network

NGDS Next Generation Diagnostics System

NIH National Institutes of Health

NOAA National Oceanographic and Atmospheric Administration

NPDN National Plant Diagnostic Network

NSF National Science Foundation

NSIV National Swine Influenza Virus Surveillance Program

NSTC National Science and Technology Council

NWHC National Wildlife Health Center

OSTP Office of Science and Technology Policy

PHAA Public Health Actionable Assays

PHEMCE Public Health Emergency Medical Countermeasure Enterprise

POC Point of Care

POCTRN Point of Care Technologies Research Network

PON Point of Need

R&D Research and Development

RAPIDD Research and Policy for Infectious Disease Dynamics

Roadmap Biosurveillance Science and Technology Roadmap

S&T Science and Technology
Strategy National Strategy for Biosurveillance

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey
Table of Contents

Executive Summary........................................................................................................................ 1

Chapter 1......................................................................................................................................... 2

Introduction..................................................................................................................................... 2

Background.............................................................................................................................. 2

Chapter 2......................................................................................................................................... 4

Foundations: Aberration Detection................................................................................................ 4

Key Research Priorities: ................................................................................................................. 4

Background.............................................................................................................................. 4

Current Programs..................................................................................................................... 4

Capability Needs...................................................................................................................... 5

Research Priorities................................................................................................................... 6

Summary and Conclusions...................................................................................................... 7

Chapter 3......................................................................................................................................... 8

Risk Anticipation............................................................................................................................. 8

Key Research Priorities: ................................................................................................................. 8

Background.............................................................................................................................. 8

Current Programs..................................................................................................................... 8

Capability Needs.................................................................................................................... 10

Research Priorities................................................................................................................. 11

Summary and Conclusions.................................................................................................... 12

Chapter 4....................................................................................................................................... 13

Threat Identification and Characterization.................................................................................. 13

Key Research Priorities: ............................................................................................................... 13

Background............................................................................................................................ 13

Current Programs................................................................................................................... 13

Capability Needs.................................................................................................................... 16

Research Priorities................................................................................................................. 17

Summary and Conclusions.................................................................................................... 18

Chapter 5....................................................................................................................................... 19

Information Integration, Analysis, and Sharing ........................................................................... 19
Key Research Priorities: ............................................................................................................... 19

Background............................................................................................................................ 19

Current Programs................................................................................................................... 19

Capability Needs.................................................................................................................... 21

Research Priorities................................................................................................................. 23

Summary and Conclusions.................................................................................................... 24

Conclusion .................................................................................................................................... 25

Appendix A................................................................................................................................. A-1

Appendix B................................................................................................................................. B-1
1

Executive Summary

The National Strategy for Biosurveillance (Strategy), published in July 2012, calls for “a 

coordinated approach that brings together Federal, state, local, and tribal governments; the 

private sector; nongovernmental organizations; and international partners” to enhance existing 

biosurveillance capabilities and, where necessary, develop new ones that provide decision 

makers and responders with the essential information they need to mitigate impacts of threats to 

health and associated economic, societal, and political consequences. The Strategy recognizes 

that a well-integrated national biosurveillance enterprise can saves lives by providing essential 

information for better decision making at all levels.

The interagency Biosurveillance Science and Technology Working Group (BST WG), chartered 

in May 2012, was established under the Subcommittee on Biological Defense Research and 

Development of the National Science and Technology Council’s Committee on Homeland and 

National Security to develop national biosurveillance research and development priorities to 

enable the Core Functions of the Strategy.

The BST WG established four sub-working groups, each focused on addressing a distinct but 

interrelated aspect of biosurveillance science and technology: aberration detection; risk 

anticipation; threat identification and characterization; and information sharing, integration, and 

analysis. Together, the four groups identified the following high-priority research and 

development objectives to be prioritized in this period of limited resources:

• Establish baseline levels of community and ecosystem risks, threats, and health;

• Identify causes of aberrations from normal at the ecosystem, organism, reservoir, vector, 

and host nexus;

• Identify indicators that are associated with potential outbreaks and develop models using 

these indicators to assist in better decision making at all levels;

• Enhance information integration, analysis, and sharing platforms for improved situational 

awareness of biosurveillance information at all levels, including with international 

partners, as appropriate;

• Further develop technological solutions that integrate and analyze electronic health 

information, while protecting private information, to better inform health decision 

making;

• Identify and evaluate the utility of novel sources of biosurveillance information, such as 

social media;

• Improve exposure assessment and diagnostic capability, especially at the point of care, to 

enable accurate and timely collection of information for early detection and situational 

awareness throughout an incident; and

• Improve identification and characterization of known and unknown health threats.

Achievement of these high-priority research and development objectives and realization of the 

integrated biosurveillance enterprise called for in the Strategy will require coordination across 

Federal organizations, academia, industry, and the international community. 
2

Chapter 1

Introduction

“A well-integrated, national biosurveillance enterprise is a national security imperative.”

–National Strategy for Biosurveillance, July 2012

Background

Threats to human, animal, and plant health have the potential for significant economic, social, 

and political consequences. These consequences can be minimized by quick, well-informed 

action; the sooner a threat is detected and understood, the faster a response can be mounted and 

the threat’s effects minimized. The National Strategy for Biosurveillance (Strategy), published in 

July 2012, calls for “a coordinated approach that brings together Federal, state, local, and tribal 

governments; the private sector; nongovernmental organizations; and international partners” to 

enhance existing biosurveillance1 capabilities and, where necessary, develop new ones that 

provide decision makers and responders with the essential information they need to mitigate 

impacts of threats to health—including the health of people, plants, domestic animals, and 

wildlife—and to food security and agriculture.

The Implementation Plan for the National Strategy for Biosurveillance (Implementation Plan) 

identifies and prioritizes actions needed to achieve the goals of the Strategy. One such action is 

the development of “...a research and development (R&D) roadmap that encourages innovation 

and collaboration in priority R&D areas...and addresses key scientific and technological gaps to 

strengthen the biosurveillance enterprise.”

This National Biosurveillance (BSV) Science and Technology (S&T) Roadmap (Roadmap) 

identifies and prioritizes the R&D efforts needed to provide decision makers at all levels with the 

accurate and timely information needed to develop effective responses to incidents that threaten 

health. The R&D objectives in this Roadmap are designed to facilitate the accomplishment of the 

core functions and actions identified in the Strategy and Implementation Plan, respectively.

Consistent with the Strategy and Homeland Security Presidential Directive (HSPD)-21 entitled

Public Health and Medical Preparedness, this Roadmap focuses on S&T for anticipating 

significant health incidents involving naturally occurring, accidental, or manmade threats; 

rapidly and accurately identifying and characterizing incidents that occur; and effectively 

integrating, sharing, and analyzing the information available at each stage. Achieving the S&T 

objectives in this Roadmap will permit better decision making during an incident, resulting in 

improved mitigation, response, and recovery2 that may ultimately save lives and improve health.

This Roadmap also identifies areas of potential department and agency collaboration to better 

leverage existing funding streams.

 1 Biosurveillance is the process of gathering, integrating, interpreting, and communicating essential information 

related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection 

and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better 

decision making at all levels. 2 S&T to enable improved mitigation, response, and recovery is described in a separate S&T Roadmap in production 

by the Biological Response and Recovery Working Group. Development, efficacy, and recommended use of postexposure prophylaxis and/or other medical countermeasures are addressed in the 2012 HHS Public Health 

Emergency Medical Countermeasures Enterprise Strategy and Implementation Plan.
3

Methodology

To create this Roadmap, the BST WG was established under the Subcommittee on Biological 

Defense Research and Development of the National Science and Technology Council’s

Committee on Homeland and National Security. The BST WG established four sub-working 

groups to explore four S&T focus areas in support of the Strategy’s Core Functions:

Aberration detection – Define and prioritize R&D needed to establish the baseline 

condition of the environment and/or human (including vulnerable subpopulations), animal, or 

plant populations that is sufficiently robust to permit rapid identification of aberrant incidents

to drive preparedness and timely, focused investigation.

Risk anticipation – Define and prioritize R&D needed to identify antecedent conditions and 

characterize complex interactions that permit prediction of an impending natural or 

intentional incident and to forecast impacts from such incidents. 

Threat identification and characterization – Define and prioritize R&D needed to ensure 

exposures and health threats are identified rapidly and accurately and can be sufficiently

characterized to provide needed information to decision makers, including responders and

healthcare providers.

Information integration, analysis, and sharing – Define and prioritize R&D needed to 

enable improved integration, sharing, and analysis of BSV data in near real-time and in a 

format that provides essential information to decision makers, including responders and 

healthcare providers.

Each of the four sub-working groups was tasked to develop a baseline of the current state of 

BSV programs relevant to their focus area. This baseline served as a foundation to conduct a gap 

analysis with respect to the Strategy and identify priority S&T needs. Rather than describe all 

ongoing BSV-related programs identified by this process, this Roadmap highlights some 

representative Federal Government activities within each focus area.

Although many of the concepts and gaps described in this Roadmap have application across all 

hazards, this report focuses on biological threats to national security, including known and 

emerging infectious disease agents with potential to significantly affect the health of the 

environment, plants, animals, and humans around the globe, whether naturally occurring or 

released accidentally or intentionally.
4

Chapter 2

Foundations: Aberration Detection

Key Research Priorities:

 Establish baseline levels of community and ecosystem risks, threats, and health

 Enhance methods and tools to rapidly detect aberrations from the baseline

Background

Watching for and detecting aberrations from baseline conditions are the first essential steps to 

assessing and anticipating health risks and threats; identifying and characterizing those threats; 

and integrating, analyzing, and sharing information about the threats, as called for in the 

Strategy. Effective decision making relies on detecting aberrations from baseline conditions 

(e.g., a rapid increase in the number of influenza cases) sufficient to warrant a threat alert and the 

recommendation of precautionary or preventive measures (e.g., attention to hand washing and 

vaccination for influenza or mass prophylaxis for a bioterrorism event).

Aberration detection requires an ability to reliably distinguish a valid signal from background 

noise and qualitatively characterize and interpret the significance of that signal. Of course, in 

order to detect potentially threatening aberrations from “normal conditions” it is necessary to 

know what is “normal”—the baseline state of the environment or of human, animal, or plant 

populations against which aberrations can be measured. Moreover, this capacity must be 

dynamic and context-sensitive; what is normal now or in one circumstance may not be in the 

future or under different circumstances. 

Current approaches to surveillance have variable accuracy and timeliness and in some cases

detect aberrations only quantitatively without the necessary qualitative characterization. Most 

quantitative detections require expert evaluations before action should be taken. For example, 

syndromic surveillance systems may identify illness clusters early (before diagnoses are 

confirmed) and alert public health agencies, but the systems do not necessarily determine the 

cause, thus requiring additional subject-matter expertise to make sense of a given alert and drive 

subsequent action. Qualitative characterization is straightforward if the surveillance data are 

specific (e.g., results from influenza A laboratory tests), but can be quite limited if the data are 

non-specific (e.g., spike in emergency department visits for fever or symptoms that are shared by 

multiple diseases). Given the current prevalence of non-specific surveillance data, the 

development of methods for qualitative characterization is critical. Thus, any efforts to improve

aberration detection should go beyond statistical improvements in detection accuracy to include 

qualitative analysis of aberrations.

Current Programs

Multiple Federal departments and agencies are working toward improved aberration detection, 

with some programs focused in particular on characterization of normal background. These 

efforts include the following:

Human Microbiome Project: The National Institutes of Health’s (NIH) Human Microbiome Project3aims to 

characterize microbial communities found at multiple human body sites (e.g., nasal passages, oral cavities, skin, 

 3 http://commonfund.nih.gov/hmp/
5

gastrointestinal tract, and urogenital tract) and look for correlations between changes in the microbiome and 

human health and disease. Initiatives include developing reference sets of microbial genome sequences;

characterizing through molecular approaches the relationship between changes in the human microbiome and 

human health and disease; development of new technologies and tools for computational analysis; and 

establishment of resource repositories (e.g., reference strains, data, software).

National Ecological Observatory Network (NEON): The National Science Foundation (NSF) is supporting the 

construction and operation of NEON is a continental-scale ecological observation and research platform designed 

to enable the assessment of both the human causes and biological consequences of environmental change. 

NEON will provide data and data products needed to improve our understanding of and ability to forecast the 

impacts of climate change, land use change, and invasive species on ecosystem structure and function –

specifically including biodiversity, biogeochemistry, ecohydrology, and infectious disease. These data and highlevel data products will be available in close to real-time and will provide a regional to continental scale 

environmental baseline and the ability to detect changes from that baseline.

National Wildlife Health Center (NWHC): The Department of the Interior (DOI) U.S. Geological Survey’s (USGS) 

NWHC conducts long-term monitoring and surveillance for wildlife health and disease detection and prevention in 

both aquatic and terrestrial environments. The NWHC provides diagnostic and disease research on wildlife; leads 

diseases investigations; participates in emergency response to medium and large-scale wildlife die-offs; and 

provides education, training, and outreach to wildlife personnel at both national and international levels.

National Animal Health Monitoring System (NAHMS): The U.S. Department of Agriculture’s (USDA) Animal and 

Plant Health Inspection Service (APHIS) NAHMS4 has been in place for over 20 years. The NAHMS Program Unit 

conducts national studies to provide essential information on livestock and poultry health and management to 

decision makers, including producers, researchers, and policymakers. Each animal group is studied at regular 

intervals, providing up-to-date and trend information needed to monitor animal health, support trade decisions, 

assess research and product development needs, answer questions for consumers, and set policy.

Capability Needs

The following capabilities are needed to strengthen aberration detection: 

• Surveillance methodologies that integrate traditional monitoring (i.e., pathogen,

environmental, health) with background data (i.e., meteorological and population 

dynamics) that may influence risk

New modeling and ecological forecasting approaches have the potential to enhance the

effectiveness of current strategies for predicting the likelihood of disease outbreaks and 

determining likely impacts when a threat is detected. For example, Hantavirus is endemic in 

the southwestern United States, where it is carried by deer mice. Research into the factors 

that determine the population dynamics of mice, such as multiyear patterns of rainfall, now 

enable public health agencies to issue warnings in years where the risk of human infection is 

high because of predicted increases in mouse populations. While imperfect, this integrated 

surveillance has the potential to dramatically reduce human infections as well as improve the 

speed of diagnosis and efficacy of treatment. 

• Ability to detect early warning signs of changes occurring at different and changing 

spatial and temporal scales

Automated aberration detection approaches often depend on data extraction and/or 

translation of foreign language reports—endeavors that would be greatly improved by 

 4 http://www.aphis.usda.gov/animal_health/nahms/
6

advances in computer science and, in particular, the field of statistical anomaly detection in 

low signal-to-noise environments. While improvements are made in these areas of basic 

science, BSV could benefit from lessons learned by researchers in other fields that also rely 

on weak-signal extraction, such as sonar and radar detection of submarines and missiles. 

• Advancements in data sharing and integration and communication technologies 

including assessment methods

Equally important to the detection of aberrations is the need to integrate and analyze the 

monitored data and communicate the information to decision makers rapidly and securely. 

For example, early recognition of disease through the examination of data from electronic 

medical records has public health value only if that signal is available to decision makers in 

time to influence a response that can mitigate the impacts of the disease. Cooperation among 

Federal and non-federal stakeholders, including the scientific community and public and 

private healthcare providers, is essential to achieve an efficient and reliable surveillance 

system.

• Education and training to meet anticipated needs for BSV professionals

New and non-traditional data collection and processing techniques have transformed the art 

and science of epidemiologic analysis. That in turn has increased the need for a more 

specialized workforce skilled in the application of these new and emerging capabilities. In 

order to prepare the next generation of scientists and engineers for successful careers as BSV 

professionals, education and training opportunities should be developed.

Research Priorities

Based on the capability needs described above and analysis of current programs, the following 

broad research priorities are proposed, with accompanying specific objectives:

• Establish baseline levels of community and ecosystem risks, threats, and health

o Assess baseline exposures to endemic, occupational, and environmental threats;

o Expand spatial and temporal mapping of endemic and epidemic disease;

o Determine levels of immune (natural and vaccine-derived) protection for various 

populations;

o Understand human behaviors and animal behaviors associated with health and illness and 

demographic trends; and

o Understand pathway issues associated with trade and movement of people (e.g.,

smuggling and unintentional transport of pathogens or pests with plant or animal 

products).

• Enhance methods and tools to rapidly detect aberrations from the baseline

o Develop statistical or mathematical algorithms to quickly and reliably distinguish a valid 

threat signal from background conditions;

o Improve language processing and parsing tools; 

o Differentiate (temporal scale) between changes of immediate concern (e.g., influenza,

foot-and-mouth disease) and those that have a large scale effect but spread more slowly 

(e.g., sudden oak death, fungal infections in bats and bees); 
7

o Assess state-of-the-art in aberration detection methods and tools applied in other sectors 

(e.g., intelligence, financial markets, credit industry) and evaluate how they might be 

leveraged or applied to BSV applications; and

o Improve qualitative characterization of aberrations through targeted education and 

training of the next generation of BSV professionals.

Summary and Conclusions

Continued improvements in high-dimensional analysis of health data, integrated with data 

describing environmental factors, vector distribution, and other factors, can facilitate rapid 

detection and characterization. These approaches have considerable potential for predicting, 

detecting, and characterizing aberrations in a way that could transform how surveillance data and 

related information is presented and used by decision makers. This reality underscores the need 

for an approach that rationally guides efforts to define a complex and dynamic baseline and 

focuses S&T investments on those anomaly detection methods and tools that will be most 

effective in achieving the goals in the Strategy. Similarly, improvements in the integration, 

analysis, and sharing of information among appropriately trained stakeholders can ensure that 

monitored data has the greatest impact on disease mitigation.
8

Chapter 3

Risk Anticipation

Key Research Priorities:

 Sustain R&D aimed at improving understanding of determinants of disease emergence 

and reemergence

 Focus on R&D relating to forecasting technologies and models that consider 

ecological and evolutionary drivers of disease behavior

 Connect non-invasive data-gathering tools to other types of surveillance data to 

improve the ability to detect antecedent conditions and the earliest indications of a 

significant incident 

Background

Globalization and ecological pressures are increasing the risk that a biological incident of 

national significance, such as the emergence of a novel infectious agent and/or a global 

pandemic, will occur. An important component of mitigating the consequences of such an 

incident is to anticipate when and where it may occur, enabling a more timely and well-informed 

response. The earlier a risk is anticipated and an actionable warning is broadcast, the greater the 

likelihood that a health threat can be prevented or its impacts significantly reduced. Risk 

anticipation requires the means to predict when an incident is likely to occur and to forecast its 

potential impacts on a given population. Technologies that help anticipate the risk seek to 

identify, measure, and analyze the many factors that set the conditions for, or directly influence,

emergence of threats.

Emergence of many natural diseases is directly affected by easily measured environmental 

conditions, such as when isolated host environments are encroached upon. However, the 

complex patterns and interactions among hosts, vectors, the pathogens themselves, and the 

environment are not easily elucidated. For example, pathogenic determinants in the microbial 

world develop as a result of myriad biological and ecological pressures. The interaction between 

microbes and human and animal populations is affected by climate, the presence of 

pharmaceuticals, chemical additives and compounds, and social behaviors. Changes caused by 

those interactions occur with varying speed and scope to set the conditions for disease 

emergence. In addition, there remain a number of uncertainties about which pathogenic changes 

act to increase virulence, host range, or other factors. While there are ongoing R&D projects to 

understand these complex interactions, realizing the Strategy’s goals will require strategic 

integration of efforts including near- and long-term S&T investments.

Current Programs

As described in Chapter 2, multiple Federal departments and agencies fund efforts to enhance 

baseline knowledge of genetics, molecular biology, proteomics, ecology, and epidemiology of 

known and emerging threats affecting the ecosystem, humans, animals, and plants to determine 

their relevance to national security and health. Traditionally, research has focused on 

retrospective evaluation to better understand data requirements and identify determinant 

variables from existing outbreaks. In order to prospectively assess current sparse data and 

provide projections of potential disease risks in an anticipatory manner, both pre- and post-
9

incident, research priorities must be better articulated and coordinated among government, 

academia, industry, and non-governmental organizations.

Infectious Disease Emergence and Transmission: The joint NSF/NIH Ecology and Evolution of Infectious Disease

program5 supports efforts to understand the underlying ecological and biological mechanisms that govern 

relationships between human-induced environmental changes and the emergence and transmission of infectious 

disease. Similarly, NIH and the Department of Homeland Security (DHS) support a cooperative program called 

Research and Policy for Infectious Disease Dynamics (RAPIDD)6

. Through an extensive series of workshops, 

working groups, and postdoctoral fellowships designed to address critical challenges, RAPIDD seeks to 

understand which models and modeling approaches will facilitate adequate operational capacity; how models 

relate with one another and with data of various quality and scale; and how the needs of decision makers can be 

characterized and addressed through modeling. RAPIDD focuses on improving the modeling of foreign animal 

diseases and zoonotic infections, aiming to make models more reliable and relevant to policy makers preparing 

for or responding to outbreaks. Finally, the NIH Models of Infectious Disease Agent Study is a transdisciplinary 

consortium of research groups with the mission of developing computational, mathematical, and statistical 

models of infectious disease dynamics and assisting decision makers to prepare for, detect, and respond to 

infectious disease threats. 

Current technologies and tools to recognize and visualize early indicators include remotelysensed imagery, common operating pictures, and disease modeling/forecasting. Federally funded 

modeling research on specific, highly infectious diseases, such as novel respiratory diseases with 

pandemic potential, is currently most useful for mitigation and response. Some success has been 

achieved in computationally assisted methods for predicting disease outbreaks. This success 

remains in the realm of disease risk mapping (e.g., ecological niche modeling), typically of 

vector-borne disease where meteorological and environmental conditions are the principal 

drivers and the diseases recur with some regularity in the same general location (e.g., cholera, 

Rift Valley fever, Hantavirus). In contrast, the current state of science does not allow for accurate

predictions of the emergence of novel diseases or of the reemergence of diseases for which no

regular cycle of emergence is known. Satellite instruments are powerful non-invasive datagathering tools and are currently the most suitable tools to identify environmental and climatic 

precursors to infectious disease outbreaks. Current satellite operations may make it possible to 

identify early (or predictive) indications of biological threats by capturing changes in the 

relationships among human, animal, and plant populations, such as population density, 

interactions and migration, and environmental conditions. Although these efforts present promise 

in the near-term for informing decision making, true predictive capability will require maturation 

of the science behind current modeling methods and continued collaboration among government, 

academia, industry, and non-governmental organizations.

Global Weather and Climate Models: The National Oceanographic and Atmospheric Administration (NOAA) 

National Centers for Environmental Prediction runs global weather and climate models and makes global weather 

and climate forecasts. It leverages its expertise in the use of model and monitoring data to guide informed 

decision-making about human diseases by, for example, investigating the relationship between climate and 

incidence of meningitis. NOAA's Center for Satellite Applications and Research—part of the National 

Environmental Satellite, Data, and Information Service—develops health-related satellite data sets and products

to help inform decisions relating to such diseases as malaria and dengue fever.

 5 http://www.fic.nih.gov/programs/Pages/ecology-infectious-diseases.aspx 6 http://www.fic.nih.gov/about/staff/pages/epidemiology-population.aspx
10

Earth Resources Observation and Science (EROS) Center7: In partnership with the National Aeronautics and 

Space Administration, the USGS’s EROS Center has been the steward and distributor of Landsat satellite data for 

over 40 years. The Landsat series of satellite missions has collected imagery of the Earth's surface since 1972, 

providing the most comprehensive record of the global landmass ever assembled. The EROS mission includes 

developing, implementing, and operating remote-sensing-based land-change monitoring, assessment, and 

prediction capabilities needed to address science objectives at all levels – within the USGS, across the Federal

Government, and around the world. Landsat data are extremely valuable for a range of applications that 

contribute to science, environmental monitoring, and homeland security. 

Federal departments and agencies are also aggressively assessing the role of technologies, such 

as social media, in characterizing disease emergence, reemergence, and nefarious exploitation of 

biological agents. To date, however, these efforts are limited to intelligence data triage, postincident analysis of signal-to-noise relationships, and veracity of reporting with an eye toward 

situational awareness.

National Center for Medical Intelligence (NCMI): The NCMI, a component of the Department of Defense’s (DoD) 

Defense Intelligence Agency, develops structured intelligence warning approaches to disease events of national 

significance (intentionally caused or naturally occurring), leveraging disparate open-source data, intelligence 

derived from National Technical Means, epidemiologic expertise, and intelligence tradecraft to move the 

intelligence warning capability temporally closer to the origins of an incident with the ultimate goal of warning 

prior to the emergence of a disease incident. Based on decades of basic data gathering and disease reporting, 

NCMI aims to expand its capacity to quickly identify abnormal disease occurrences and behavior globally. In 

partnership with the DoD Chemical Biological Defense Program and multiple Federal non-Title-50 partners, NCMI 

is exploring computational modeling, semantic fusion, entity resolution, link analysis, and molecular biological 

techniques that present some degree of promise in achieving a predictive capacity for the intelligence 

community.

PREDICT: PREDICT is a project of the U.S. Agency for International Development’s Emerging Pandemic Threats 

Program that is building global surveillance to detect and prevent spillover of pathogens of pandemic potential 

that can move between wildlife and people. PREDICT has built a broad coalition of international partners to 

discover, detect, and monitor diseases at the wildlife-human interface using a risk-based approach that includes

integrating digital sensing and on-the-ground surveillance at critical points for disease emergence. PREDICT is at 

the cutting-edge of recent technological advances allowing for rapid detection and diagnosis of high-risk viral 

families in all resource settings.

Capability Needs

Predicting the emergence of animal and plant diseases and zoonoses and forecasting the 

outcomes of their occurrence are significant scientific challenges. The principal needs to better 

forecast significant disease events and anticipate their risks include:

• Understanding of antecedent conditions at appropriate spatial and temporal scales

The science of predicting discontinuous change in complex systems is relative immature—a 

challenge exacerbated by a relative paucity of data. In contrast to the physical sciences, in 

which systems and relevant variables can be enumerated and characterized in functionally 

closed systems, biological incidents occur in open systems, making the process of identifying 

and limiting relevant variables a daunting task. 

 7 http://eros.usgs.gov/
11

• Ability to forecast the dynamics of novel disease emergence or the exploitation of

biological agents by adversaries

The ability to forecast impacts of the emergence of a novel disease or an intentionally

released agent begins with having some fundamental understanding of environmental and 

behavioral factors that have predictive influence on an agent’s behavior, including the 

movement of a human or animal population within the environment. Further, rapid 

characterization of the at-risk population, whether by direct knowledge (e.g., census data) or 

remote analysis (e.g., human geography/human terrain analysis), as well as the agent’s 

transmissibility, mode of transmission, and generation time are key contributors to forecast

impact. With respect to deliberate releases of pathogens, physical parameters of dispersal and

the behavior of threat agents when aerosolized under various environmental conditions can

illuminate the likely upper and lower bounds of the initial affected population. Basic 

epidemiology can then inform secondary transmission in the event an agent is contagious.

Research Priorities

Based on the capability needs described above and analysis of current programs, the following 

broad research priorities are proposed, with accompanying specific objectives:

• Sustain R&D efforts aimed at improving understanding of determinants of disease 

emergence and reemergence, including ecological and evolutionary factors that 

promote the ability of organisms to move to new host-species (e.g., swine/avian

influenza to humans) and acquire antimicrobial resistance

o Develop improved molecular approaches (genomics, meta-genomics, proteomics, nondestructive sequencing) to elucidate exposure causes and effects, and 

host/vector/reservoir-specific molecular-level relationships and interactions in the context 

of known and, ultimately, newly emergent biological threats;

o Integrate the vast array of wildlife data (e.g., harmful algal blooms, fish kills, marine 

mammal strandings, migration) and environmental data (e.g., air quality, toxic exposures, 

public health surveys) collected by governmental agencies, academia, and industry, and 

merge these data into geographical and temporal visualization tools; and

o Improve linkage between this basic research and the applied model-development research 

as described below.

• Focus on R&D relating to forecasting technologies and models that consider ecological 

and evolutionary drivers of disease behavior 

o Advance modeling R&D and analytical frameworks for specific classes of incidents (e.g., 

influenza versus cholera versus intentional release scenarios); and

o Improve operational quality through rigorous testing of the reliability and validity of 

models.

• Connect non-invasive data-gathering tools to other types of surveillance data to 

improve the ability to detect antecedent conditions and the earliest indications of a 

significant incident

o Characterize conditions, demographics, and environmental factors that can inform the 

earliest possible warning and projection of impact, as well as points of intervention to 

positively affect projected impacts;
12

o Integrate emerging remote sensing capabilities/analysis (such as biological, chemical, and 

hyperspectral) with fixed, distributed autonomous or semi-autonomous surveillance 

platforms and conventional molecular biological tools to characterize and ultimately 

predict spatially and temporally important environmental variables that influence disease 

emergence within ecosystems, including humans;

o Examine current coverage and capabilities of ground-based, in situ sensors for detecting 

threats, and enhance efficiency or expand, as appropriate and feasible;

o Develop individual exposure assessment technologies, such as pre-symptomatic exposure

biomarkers and individual dosimeters, to more rapidly and accurately detect exposures.

Summary and Conclusions

New foundational science and operational capabilities are needed to develop the ability to predict 

the impacts and risks posed by emerging diseases. Robust characterization of antecedent 

environmental conditions and the molecular dynamics of ecology-reservoir-host-pathogen 

interactions that can drive pathogenesis are essential to attain a true predictive capacity. 

Ultimately, such capabilities should be able to predict whether a health incident anywhere in the 

world will progress to one of regional, national, or international significance.
13

Chapter 4

Threat Identification and Characterization

Key Research Priorities:

 Development of rapid, reliable next generation detection and diagnostic capabilities 

 Development of new tools and methodologies to improve collection, preservation, 

transport, and preparation of clinical and non-diagnostic samples

 Development of instrumentation and large data-set-processing capabilities to rapidly 

identify characteristics of agents

Background

Health is essential to national security. Health threats for human populations pose obvious 

security risks, but diseases in plant and animal populations can also pose serious security risks, 

including disruption of the food supply and commerce, with potentially long-lasting human 

health and economic impacts. Early detection of such threats can support determinations of the 

population exposed, diagnosis and treatment decisions, and containment of the threat. 

Strengthened laboratory and field capabilities are needed to recognize potential health threats as 

early as possible. 

Diagnostic tests provide crucial information to surveillance programs in a variety of operational 

contexts, including U.S. laboratory networks and U.S. reference diagnostic laboratories 

associated with the World Health Organization, the United Nations Food and Agriculture 

Organization, and the World Organization for Animal Health (formerly known as the Office 

International des Epizooties). It is critical that technologies and methodologies to enable rapid 

and accurate identification and characterization of health threats are broadly available and fully 

functional.

Current Programs

A number of programs today contribute to the Nation’s capacity to identify and characterize

health threats. Several representative programs are described below, categorized by some of the 

overarching identification and characterization challenges they address.

• Diagnosis of disease at point of care (POC) and point of need (PON): Infectious disease 

diagnostic testing generally occurs in fixed-site clinical laboratories. Typically, clinicallaboratory-based diagnostic platforms are not cost effective or rugged enough for use in 

POC/PON settings where treatment can be initiated sooner. While several POC/PON tests 

exist for initial patient testing, they are limited by poor sensitivity or specificity and generally 

require a confirmatory clinical laboratory test result prior to treatment. Advanced POC/PON 

testing platforms with sensitivity and specificity similar to those used in clinical laboratories 

are becoming available for limited resource settings; however, they remain high complexity 

tests and continue to require a trained laboratory clinician to ensure reliable results, limiting 

their global adoption.

Point of Care Technologies Research Network (POCTRN): The NIH POCTRN drives the development of 

appropriate POC technologies through collaborative efforts that merge scientific, engineering, and technological 

capabilities with clinical need. The POCTRN is developing technologies for the diagnosis, screening, treatment, 

and monitoring of a variety of diseases. A major goal of POCTRN is higher quality care at reduced cost, with a shift 
14

in focus from specialized care for the treatment of late-stage disease to an emphasis on patient-centered 

approaches and coordinated care teams that promote wellness and effective disease management.

DoD Next Generation Diagnostics System (NGDS): The DoD NGDS is an incrementally acquired family of 

systems intended to provide an enhanced diagnostic capability from the laboratory to the field in support the DoD 

and its U.S. Government partners. Short-term investments will focus on the acquisition of a commercial off-theshelf diagnostic system suitable for use in field and mobile laboratories and development of Food and Drug 

Administration (FDA)-cleared biological agent in vitro diagnostic assays. Long-term efforts will focus on the 

development of far-forward diagnostic capabilities and diagnostics for chemical, biological, radiological, and 

nuclear threats. Common themes throughout all increments of the NGDS program are alignment with 

therapeutics and the pursuit of common materiel solutions for endemic infectious disease diagnostics, and 

environmental sample analysis for public health and biological defense applications.

• Detection of threat agents in non-diagnostic samples using field-based and laboratory 

systems: A number of laboratory and disease-tracking networks are available to perform 

confirmatory testing of suspected disease threats (such as suspicious powders or animal 

droppings) and to detect disease trends in animals and plants. For example, the Centers for 

Disease Control and Prevention’s (CDC) Laboratory Response Network (LRN) is an 

integrated system of state and local public health, Federal, military, and international 

laboratories that operate continuously for laboratory identification of threats associated with 

terrorism and other public health emergencies. Similarly, USDA and USGS reference

laboratories are members of diagnostic laboratory networks such as the National Animal 

Health Laboratory Network8 (NAHLN) and the National Plant Diagnostic Network 

(NPDN)9

, which provide rapid detection and confirmatory diagnoses of known threats to 

plants and animals.

Federally Funded Biological Detection Systems: There are several detection systems currently deployed to 

conduct continuous surveillance for biological threats in non-diagnostic samples by Federal departments and 

agencies and private-sector organizations. Examples include: DHS’ BioWatch Program; DoD’s Installation 

Protection Program and Joint Biological Point Detection System for wide-area detection of aerosol threats; the 

Environmental Protection Agency’s Water Security Initiative to detect contamination of drinking water 

distribution systems; NOAA’s Harmful Algal Bloom forecast network; the U.S. Postal Service Biohazard Detection 

System used to screen mail in U.S. postal facilities across the Nation; and DOI USGS’ Migratory Wild Bird Disease 

Surveillance Program using migratory, genetic, and immunological data to identify likely routes of virus 

introduction, and prioritizing migratory bird species for sampling based on their potential to transmit highly 

pathogenic avian influenza into North America.

Public Health Actionable AssaysTM (PHAA): The PHAA effort sets stringent assay performance evaluation and 

validation requirements for both non-diagnostic samples as well as clinical samples within the LRN member 

laboratories; PHAA ensures clinical samples are compliant with FDA regulations for in vitro diagnostic use. The 

evaluation and performance requirements were determined through an interagency effort. Assays that achieve 

this level of performance provide the high confidence identification results necessary in the public health 

community to inform early decision making.

Cooperative Agricultural Pest Survey (CAPS): USDA’s APHIS leverages efforts by state departments of 

agriculture, universities, and industry partners in annual surveys targeting specific exotic plant pests that threaten 

U.S. agricultural and/or natural settings by funding a network of cooperators that participate in the CAPS program 

and conduct surveys and testing. The NPDN is a strong partner with Federal and state programs to provide a 

distributed nationwide network of public agricultural institutions to quickly detect high consequence pests and 

 8 http://www.aphis.usda.gov/animal_health/nahln/

9 http://www.npdn.org/
15

pathogens using federally validated methods and immediately report them to appropriate responders and 

decision makers. 

National Swine Influenza Virus (NSIV) Surveillance Program: USDA and CDC initiated a swine influenza virus 

surveillance pilot project in 2008 to track the epidemiology and ecology of swine influenza virus in swine and 

human infections. Under this pilot project, when the human pandemic influenza outbreak occurred in April 2009, 

CDC quickly shared human H1N1 virus isolates with USDA, allowing USDA to rapidly develop, validate, and 

deploy to the NAHLN an A(H1N1)pdm09-specific diagnostic polymerase chain reaction assay. The surveillance 

pilot was expanded and then modified into the NSIV surveillance program to (1) monitor genetic evolution of 

swine influenza virus; (2) make swine influenza virus isolates available for research and an objective database for 

genetic analysis of these isolates and related information; and (3) select proper isolates for the development of 

relevant diagnostic reagents and vaccine seed stocks.

• Rapid characterization of emerging and novel threats: Laboratory characterization of a 

novel disease-causing agent involves the collection of high confidence genotypic and 

phenotypic information, such as those related to critical pathogen properties (e.g., phylogeny, 

virulence, growth, morphology, pathogenicity, viability, transmissibility, antibiotic 

susceptibility, and functional genomics); host immune response and early disease markers; 

microbial source identification indicators; and ecological adaptations. Data derived from this 

type of in-depth analysis informs medical countermeasure development and response.

Technologies for Rapid Characterization and Identification: CDC’s Rapid Response & Advanced Technology 

Laboratory, in conjunction with the Biotechnology Core Facility and Office of Public Health Preparedness and 

Response, is facilitating an interagency multi-tiered technology approach for rapid pathogen detection, 

characterization, and identification. Applied R&D supports CDC/DoD collaborative efforts to operationalize 

Biomedical Advanced Research and Development Authority and Defense Threat Reduction Agency (DTRA) 

research investments and development of a systems approach for analysis of clinical samples for identification 

and characterization of known, emerging, and advanced biological threats. This includes genomic and proteomic 

technologies associated with multiplexed screening, microarrays, high-throughput sequencing, and 

bioinformatics analysis. This research also serves as proof of concept to address potential gaps in surveillance to 

detect natural or man-made changes in known agents and discover unknown/unexpected agents due to a reduced 

use of culture-based diagnostics.

• Surge/follow-up capacity for clinical and non-diagnostic sample analysis: Surge capacity 

is the operational capability to detect or diagnose threat agents in a large number of samples 

within a short time frame. The current U.S. surge capacity for emergency detection and 

diagnostic testing of samples generated after a potential incident relies on coordinated 

networking among cooperating laboratory systems. Coordination requires shared knowledge 

about specific laboratory sample preparation and analysis capabilities so that sample routing 

and results reporting can be optimized when surge capacity is required. Follow-up capacity 

relates to the fact that, in addition to technologies for predicting and detecting a disease 

outbreak, there is a need for surveillance methods specialized for use in the aftermath of an 

outbreak to determine the scope of the evolving threat and the level of continued risk to 

susceptible populations. Furthermore, novel surveillance efforts may be needed to certify that 

entities or areas are free of disease or to otherwise confirm exposure status for international 

trading partners or for other purposes. 

Integrated Consortium of Laboratory Networks (ICLN): The ICLN is a DHS-chaired multiagency effort to bring 

together information, operations, and strategies from different laboratory systems for timely response to major 

incidents; participating networks include the CDC LRN, the NAHLN, the NPDN, the Food Emergency Response 

Network, the Environmental Response Laboratory Network, and the DoD Laboratory Network. The ICLN is a 
16

forum to share ideas, collaborate, and build relationships to support a more effective integrated response during 

emergencies (e.g., terrorist attacks, natural disasters, and disease outbreaks). 

Capability Needs

The principal needs to improve the identification and characterization of threats include:

• Improved sensitivity, specificity, and portability of multiplexed technologies capable of 

identifying, with confidence, known and unknown threats in complex samples

Developing capabilities for more rapid, accurate, and comprehensive early identification and 

characterization of emerging or re-emerging pathogens and toxic exposures, especially for 

those of unknown etiology, can reduce morbidity, mortality, transmission, and consequences. 

Moving diagnostic capabilities to POC/PON settings will result in faster initiation of 

treatment, as would developing a capability to identify patients requiring treatment earlier in 

the progression of symptoms. When possible, such technologies should be developed so they 

can be sustainably adopted by healthcare practitioners in low-resource international contexts

and are amenable to adaptation to high-throughput situations. Focusing investments on 

POC/PON tests for which there is an available treatment, or where early identification of the 

disease can impact patient outcomes, will facilitate adoption and increase the return on 

investment.

• Improved sample collection, preservation, transport, and preparation technologies and 

protocols

Current methods to collect, preserve, transport, and prepare clinical and non-diagnostic 

samples must be augmented to ensure presentation of high-quality samples for detection and 

diagnostic tools. This includes work to reduce the need for large sample sizes for testing, 

allowing for retention of as much of the original sample as possible for future evaluation.

• Improved standards for testing and evaluation of detection tools, including the 

development of inclusivity and exclusivity threat-agent panels and validated testing and 

evaluation protocols

Confidence in detection tools is hampered by inconsistent expectations about the use and 

performance of these tools. This inconsistency is the result of varying standards for testing 

and evaluation methodologies and the use of reagents/materials that are not universally 

recognized as reference-quality. Improving test and evaluation standards will result in better 

information for decision makers and higher confidence in and acceptance of results.

• Improved diagnostic technologies and access to signatures, reagents, strains, and 

sequence data, and an informatics and computational capabilities

To support development of diagnostic and detection platforms for known, emerging, reemerging, and unknown pathogens, there is a need for a consortium of repositories with a 

central catalog of signatures, reagents (including libraries of both validated reference strains 

and nearest neighbor strains), and taxonomic and sequence data, as well as the informatics 

and computational capability to support warehousing, curatorial services, querying, and 

modeling of disparate types of relevant data. This repository and capability will provide the 

means for standardized technology development, validation of technology performance, and 

ability to interpret results.
17

• Improved surveillance techniques, data sharing, and interoperability for plants, 

animals, and food

The ability to conduct efficient surveillance of health threats in plants, animals, and food is 

hampered by the lack of cost- and labor-effective methods to inspect a high percentage of 

these items; rapid field detection and diagnosis tools; and identification of pre-symptom or 

latent markers of infection or infestation. Furthermore, there are numerous databases of 

surveillance information in these sectors that are organized by species or industry, which 

contributes to a large technical gap in interoperability and minimal ability to share data from 

multiple disparate data streams, to inform when increased surveillance in a particular 

population is needed (e.g., when a spike in wildlife disease spurs increased surveillance of 

nearby livestock and poultry populations), or to establish a threat baseline to enable detection 

of emerging or re-emerging threats. It is particularly critical to improve foreign disease 

surveillance and data sharing capacity, and to enhance international capabilities to share 

critical disease surveillance data.

Research Priorities

Based on the capability needs described above and analysis of current programs, the following 

broad research priorities are proposed, with accompanying specific objectives:

• Development of rapid, reliable detection and diagnostic capabilities 

o Increase the speed and performance of threat detection, exposure, and disease diagnosis 

to support rapid and effective treatment decisions, contain disease, and mitigate the 

impact of a potential outbreak;

o Move the determination of individual (asymptomatic) exposure and diagnosis of disease 

closer to the POC/PON setting, resulting in rapid initiation of treatment; and

o Enhance global access to POC/PON tests.

• Development of new tools and methodologies to improve collection, preservation, 

transport, and preparation of clinical and non-diagnostic samples, to include 

maintaining sample safety, integrity, and viability/culturability

o Ensure compatibility with nucleic acid, protein, and/or live organism characterization 

methods; 

o Integrate sample preparation technologies within detection or diagnostic tools, where 

possible, and reduce required ancillary equipment; and

o Develop semi- to fully-automated sample collection, preservation, transportation, and 

preparation technologies that are compatible with current and emerging 

detection/diagnostic systems; are of sufficient scalability to support high throughput

applications; and are deliberately developed to be sustainably adopted by healthcare 

practitioners in low-resource international contexts.
18

• Development of instrumentation and large-data-set processing capabilities to rapidly 

identify characteristics of known agents, rapidly detect changes in known agents, 

and/or to discover the existence of unknown agents from samples in clinical or 

environmental matrices

o Examine characterization efforts (genotypic and phenotypic) for human, animal, and 

plant pathogens from high-risk areas around the world to detect emerging infectious 

diseases, and expand as appropriate and feasible;

o Develop comprehensive databases linking pathogenic agents to disease outbreaks, 

location of origin, and other characteristics;

o Establish a consortium of repositories of signatures, reagents, strains, and sequence data, 

and an informatics and computational capability for warehousing, curatorial services, 

querying, and modeling; and

o Develop standardized processes to conduct “what if” analyses of the environmental and 

health impacts of a pathogen prior to patient identification and treatment initiation.

Summary and Conclusions

Currently, the array of accurate, durable, and reliable detection, measurement of exposures, 

diagnostic, and characterization systems and methods is inadequate. This insufficiency can lead 

to early confusion as to the nature, cause, and appropriate treatment of a health threat; reliance on 

expensive laboratory infrastructure for analysis; and a reactive rather than proactive response to 

incidents. Achieving the S&T goals in this area will increase the speed and accuracy of 

detection, exposure assessment, and identification, characterization, and disease diagnosis; 

increase confidence in identifying health threats; and provide situational awareness and critical 

information to support decision making associated with control and prevention, to include 

assessment of the potential economic and health consequences of an incident and rapid and 

effective treatment and control decisions.
19

Chapter 5

Information Integration, Analysis, and Sharing

Key Research Priorities:

 Development/enhancement of systems that improve near-real-time sharing of 

electronic health, diagnostic, and other anomalous health event data

 Development of improved mechanisms to assess data/information sources for relevancy 

to BSV

 Development of multilateral communication mechanisms among various levels of 

government, and the private sector (including healthcare providers, international 

partners, and others)

 Development of a national, interagency BSV data-sharing framework that integrates 

data/information from disparate sources

 Integration of all source data (intelligence, law enforcement, environmental, socioeconomic, and health information)

 Formalization of a means to effectively communicate uncertainty in BSV data used for 

decision making

Background

The overarching goal of the U.S. BSV enterprise is the ability to make informed decisions 

earlier, enabled by analysis of near-real-time information and integration of numerous existing 

efforts at varying stages of development or deployment. Data sharing and integration, as 

described in HSPD-21, suggests “...international connectivity where appropriate, that is 

predicated on state, regional, and community level capabilities and creates a networked system to 

allow for two-way information flow between and among Federal, state, and local government 

public health authorities and clinical healthcare providers.” A robust global system to coordinate 

the integration and analysis of information does not currently exist. Improved integration and 

analysis of information from multilateral capabilities would provide the Nation and international 

community with a powerful capability for early warning of an emerging incident and situational 

awareness while the incident is being characterized. The architecture for this framework would 

be inherently complex and its operationalization will require long-term R&D efforts and 

international collaborations.

Current Programs

Many novel and promising BSV programs have been developed for information sharing, 

integration, and analysis at the Federal, state, and local levels in recent years. In 2010, the 

Government Accountability Office summarized more than 100 Federal data sources and systems 

that could contribute to a national BSV enterprise.

10 Two efforts planned or currently underway 

to identify these systems include an expansion of CDC’s previous internal efforts to capture nonCDC information systems as part of a proposed Federal BSV Registry and an effort funded by 

 10 http://www.gao.gov/assets/310/306362.pdf
20

DTRA as part of its BSV program to identify, categorize, and assess the value of potential data 

streams relevant to BSV systems for DoD.

Extensive efforts have been made by numerous national and regional entities to use existing 

human electronic health records for syndromic surveillance, exemplified nationally by DoD’s

Electronic Surveillance System for Early Notification of Community-based Epidemics 

(ESSENCE) and the CDC BioSense system, and regionally by systems such as the Pennsylvania 

Real-time Outbreak and Disease Surveillance system and the National Collaborative for BioPreparedness. These systems leverage existing health data (e.g., administrative patient discharge 

coding data, laboratory data, and emergency department chief complaints) from participating 

sources for automated, near-real-time transfer and analysis of information for early detection of 

anomalous health events. These types of systems have demonstrated some success for situational 

awareness during an event, but their ability to provide reliable and timely early warning is yet to 

be established.

BioSense 2.0: BioSense 2.0 is a CDC chartered, community-guided public health surveillance system that provides 

the capability to expand the practice of syndromic surveillance at local, state, regional, and national levels. Hosted 

completely in a secure internet cloud computing environment, BioSense 2.0 is capable of rapidly monitoring 

outbreaks and harmful health effects of hazardous agents and tracking them throughout the duration of a public 

health emergency utilizing hospital emergency department record data. BioSense 2.0 provides state and local 

health jurisdictions storage, analysis, and aggregate data sharing capabilities through a syndromic surveillance 

platform. By 2014, BioSense 2.0 is projected to incorporate data from 65% of state and local jurisdictions, plus 

data from other healthcare sources. These data will contribute timely and accurate information to the overall 

situation awareness of local, state, regional, and national public health.

Standards for Biosurveillance Information Exchange: HHS previously sponsored the Healthcare Information 

Technology Standards Panel Biosurveillance Interoperability Specification that defined standards to promote BSV

information exchange among healthcare providers and public health authorities. This effort helped establish a 

detailed data sharing framework for electronic health record information technology systems to encourage use of 

systems that would provide public health information directly to a public health authority.

A number of discipline-specific and surveillance partnerships exist. For example, the NIH’s

Influenza Research Database is an international and domestic collaborative research effort 

between the Centers of Excellence for Influenza Research and Surveillance and 

bioinformatics/genomics research programs with a focus on integrating diverse datasets and 

sharing data with the influenza virus research community. The Department of State implements 

foreign assistance projects in the Middle East and North Africa, South and Southeast Asia, SubSaharan Africa, and other regions, to promote safe, secure, and sustainable bioscience capacity 

that improves disease diagnosis, reporting, and response. International partnerships are critical to 

this work, and the United Kingdom, Canada, the Netherlands, and the Republic of Korea have 

each provided financial contributions to help advance U.S.-led bioengagement activities abroad.

National Biosurveillance Integration System (NBIS): NBIS is a national interagency BSV integration body 

coordinated by the DHS National Biosurveillance Integration Center (NBIC) in accordance with a series of U.S. 

laws and directives (HSPD-9 and -10, Public Law 110-53 Section 1101, Food Safety Modernization Act Section 

205). NBIS member agencies integrate data within their BSV domain and share this information with NBIC after 

the data are analyzed by their subject matter experts. NBIC, in full collaboration with the NBIS, connects, 

correlates, and contextualizes information across domains through the production and dissemination of its 

analytic products. NBIC’s integrating role enhances the Federal government’s ability to provide early warning and 

shared situational awareness. 

Emerging Infections Programs (EIP): The EIP are population-based centers of excellence established through a 

network of state health departments collaborating with academic institutions; local health departments; public 
21

health and clinical laboratories; infection control professionals; and healthcare providers. The EIP network’s 

unique strength and contribution lies in its ability to quickly translate surveillance and research activities into 

informed policy and public health practice and to maintain sufficient flexibility for emergency response as new 

problems arise. Surveillance efforts of the EIP activities generate reliable estimates of the incidence of certain 

infections and provide the foundation for a variety of epidemiologic studies to monitor prevention strategies, 

explore risk factors, validate diagnostics and surveillance methods, and investigate spectrum of disease.

Biosurveillance Indications and Warning Analytic Community (BIWAC): The BIWAC is a self-organized, informal 

BSV information sharing group with participants from multiple U.S. government organizations. The BIWAC 

shares BSV data via unsophisticated web interfaces and has focused on interagency collaboration and relationship 

building.

The DoD Joint Science and Technology Office has initiated an R&D program, called the BSV

“Ecosystem” program, which aims to heavily leverage private-sector innovations in data 

collection and analysis that have not been previously applied to BSV. It is envisioned that data 

from collection and analysis systems will eventually be linked in a cloud-computing construct to 

serve a range of analytical customers; however, a specific architecture has yet to be developed. 

The DoD Joint Program Executive Office for Chemical and Biological Defense is developing a 

BSV communications framework termed BSV Portal (BSP) that aims to provide a single webbased environment that will facilitate collaboration, communication, and information-sharing in 

support of the detection, management, and mitigation of man-made and naturally occurring 

biological events. While the current emphasis of the BSP is focused on a subset of DoD users, it 

is being developed with the capability for a broader user base in the DoD and interagency space 

and may serve as a component of a future national BSV enterprise.

Several Federal departments and agencies and offices have invested in BSV-related R&D, 

including HHS (CDC, NIH), DoD, DHS, NSF, the Department of Commerce (NOAA), and 

USDA. Most current BSV-related investments, however, support existing data integration 

systems to meet the day-to-day information needs of the organization. These existing efforts 

could form the basis for a national-level data integration enterprise with sufficient funds, 

mandates, and long-term plans.

Capability Needs

• Ability to aggregate analyzed health data from different health sources, syndromic 

surveillance systems, and sectors to detect aberrations and discover spatial and 

temporal disease trends

While the potential for leveraging electronic information to augment disease surveillance is 

widely recognized, certain information-sharing criteria and research efforts need to be 

realized to advance this capability. Health data in electronic form have significant value for 

BSV since they provide an opportunity for more timely recognition of clinical signs in 

clusters of humans, animals, and plants that may provide an early indication of an emerging 

health incident. Effectively, appropriately, and securely sharing health event data, including 

parts of electronic patient records and laboratory data, has significant potential to improve 

national awareness of incidents that could progress to impact national security. However, a 

number of data-sourcing challenges exist. For example, data on human health can be 

collected from numerous types of patient management systems, laboratory information 

systems, and insurance systems, but there is a need for comprehensive terminology 

standardization across the spectrum of sources to ease data fusion and analysis while 

protecting the privacy of personal health data. Similarly, many livestock health records
22

(domestic and foreign) are held by private industry and are not standardized from an 

informatics point of view, nor are they broadly accessible. Overall, there is a need for 

increased automated sharing and integration of electronic data from different health systems, 

different syndromic surveillance systems, and different health sectors.

• Ability to determine what data/information sources are relevant to BSV

The BSV community needs a systematic mechanism to categorize, evaluate, and document 

the expected contributions and limitations of data sources useful for local, regional, national, 

or international BSV efforts including early warning, early detection, and situational 

awareness. A few typical examples of data sources include: clinical, syndromic, diagnostic, 

prescription, and over-the-counter drug use; news and social media; school and work 

absenteeism; Internet-based early warning clearinghouses; and aggregated commercial search 

engine query data. Each of those broad categories can include a range of specific data sources

with vastly different performance metrics due to differences in quality, completeness, or 

timeliness attributes, or the methodology used to analyze them. This variation provides a rich 

pool of potentially useful BSV data; however, it also presents challenges, as it can be 

difficult to assess the relative value of each source. Further, these various types of data may 

be subject to differing privacy laws.

• Sustained and appropriate multilateral information sharing 

Producing a national BSV capability requires across-the-board collaboration of subject 

matter experts from different sectors (e.g., human, animal, plant, and environmental health; 

intelligence) at different levels of government, from the private sector, and with international 

partners. Active collaboration and information-sharing for BSV presents a number of 

challenges, especially since stakeholders have varying missions and roles, and the perceived 

requirements for early warning and situational awareness often necessitate novel or 

unconventional uses of preliminary information that cannot always be shared. Mechanisms to 

ensure rapid sharing (both “push” and “pull”) of time-sensitive information aimed at 

supporting local, regional, national, or international decision- making can prove critical to 

achieving health and security goals. Confidentiality issues, the level of granularity to be 

shared among BSV systems, and actions mutually expected to result from shared information 

must be addressed and understood by participants in advance.

• Integration of all existing and emerging BSV efforts and cross-domain information 

sources into a coherent BSV enterprise

One of the biggest challenges to successful national BSV is that, to be effective, information 

needs to be considered simultaneously from vastly disparate domains, including health, law 

enforcement, intelligence, environmental monitoring, remote sensing, international partners, 

and many others. Each domain has its own culture, investigative methodology, and tolerance 

for the timeliness and completeness of information necessary to make decisions and initiate 

response actions. Additionally, there are dozens and possibly hundreds of BSV initiatives and 

pilot projects that have been started at local, state, regional, and national levels. Without a 

universal system for integration of multiple, disparate data sources relevant to BSV, the 

synergistic value of bringing these data together will not be attained.
23

• Standardized methods for determining the uncertainty in BSV data and clearly 

communicating the limits of the data and analytical techniques

For information to be actionable, some assessment and communication of its validity and 

accuracy is needed. BSV data present many analysis challenges because they can be 

inconsistently collected, reported, and analyzed; may contain collection and other types of 

data biases; can be derived from many disparate or incongruent sources; and may have gaps 

in temporal and spatial coverage. Each of these factors can add uncertainty to any analysis. In 

addition, local contextual knowledge is often needed to interpret the significance of any 

statistical deviation. These influences may or may not be known to the data owners and, as 

the data are analyzed by others, re-purposed, or otherwise reach a broader audience, the 

nuances related to specific data uncertainties may not be consistently and appropriately 

communicated. As a result, human expertise, which may be enhanced by technology, is key 

to a successful BSV enterprise. Research related to uncertainty quantification and 

communication is required to ensure decision makers are fully aware of the strengths and 

weakness of inferences that may be made as a result of BSV data analysis.

Research Priorities

Based on the capability needs described above and analysis of current programs, the following 

broad research priorities are proposed, with accompanying specific objectives:

• Development/enhancement of systems that improve near real-time sharing of electronic 

health, diagnostic, and other anomalous health event data

o Develop systems for human, animal, and plant electronic health data with capacity for 

standardizing data elements to allow for potential interoperability of systems and data 

integration, including with international partners as appropriate;

o Define a common “near-real-time” requirement for early incident detection, given the 

varying requirements among sectors; and

o Develop standards to ensure secure, automated data transmission with rule-based sharing 

and role-based authentication.

• Development of improved mechanisms to assess data/information sources for relevancy 

to BSV

o Continue efforts to define and establish mechanisms to assess data/information sources, 

particularly through coordination of DoD, HHS, and DHS efforts and with the rest of 

Federal interagency;

o Develop and use metrics for each category of data source (e.g., sensitivity, specificity, 

timeliness) to assess the utility of tools, training programs, and strategies employed to 

support national and global BSV efforts; and

o Establish a process and test data sets for calibration and system performance comparisons

to assess whether a source is primarily beneficial for earliest possible detection, 

situational awareness, impact forecasting, and/or response efforts.

• Development of multilateral communication mechanisms among various levels of 

government and the private sector (including healthcare providers, international 

partners, and others) to enable timely decision making at all levels
24

o Develop a community-endorsed and championed primary BSV Common Operating 

Picture, leveraging existing capabilities and lessons learned, to collect and share 

information at a national level and display a level of BSV information, including analyst 

insight, necessary to inform operational decision-makers across the government;

o Evaluate ways to establish enduring, analyst-focused trust relationships across sectors 

and domains—and among international partners, organizations, and nongovernmental 

organizations—to facilitate a multi-institutional culture of information sharing; and

o Establish mechanisms to securely transfer finished or unfinished information at different 

levels (e.g., open-source, sensitive, classified) among stakeholders and decision makers

to enhance integration and usability. 

• Development of a national, interagency BSV data-sharing framework that integrates 

data/information from disparate sources to enable early warning and early detection of 

incidents and situational awareness during an incident

o Integrate various existing and emerging BSV efforts and cross-domain information 

sources into a coherent BSV enterprise. This path forward may require a “system-ofsystems” approach that capitalizes on successes and capabilities of the many existing 

systems by linking them in a new national BSV framework that does not currently exist; 

and

o Develop a viable approach for state and local authorities to access a national, interagency 

BSV data-sharing framework, as well as ways to collect their data.

• Integration of all source data (intelligence, law enforcement, environmental, socioeconomic, and health information) to enhance the detection of a disease event and 

facilitate warning and forecasting of impact

• Continue development of automation tools that allow efficient knowledge discovery 

through exploitation of existing large and massive data sets, particularly unstructured 

massive information stores such as PubMed, the National Center for Biotechnology 

Information, and other National Library of Medicine resources; as well as social media; 

online engine searches; and traditional media reporting; and

o Establish an interagency BSV information technology development, information 

management, and knowledge generation coordination initiative.

• Formalization of a means to effectively communicate uncertainty in BSV data used for 

decision making

o Develop standardized methods for determining the uncertainty in BSV data and clearly 

communicating the limits of the data and analytical techniques.

Summary and Conclusions

A major challenge to successful national BSV is that information must be considered 

simultaneously from vastly disparate domains, including health, law enforcement, intelligence, 

and international partners. Sharing of this information is limited, due to real or perceived 

confidentiality and other issues, and is often not possible. Integration of multilateral capabilities 

will enable strengths and resources to be leveraged, providing a powerful capability for early 

warning and situational awareness. Successful implementation of a national BSV enterprise will 

support a more comprehensive national information sharing capability to save lives and reduce 

illness.
25

Conclusion

Meeting the challenge of establishing the national BSV enterprise called for in the Strategy will 

be difficult, but is not insurmountable. Progress has already been made and current programs and 

technologies are making strides toward meeting the Strategy’s goals. Continuing this progress 

will require focusing investments and coordinating efforts across the Federal Government on 

enabling S&T, with participation from academia, industry, and international partners. 

Investing in the goals identified in this Roadmap will increase the speed and accuracy of disease 

detection, identification, characterization, and information sharing and support decision making 

associated with rapid disease control, prevention, and treatment.
A-1

Appendix A

Chapter 4 Glossary

Characterization: Determination of one or more physical, chemical, or biological properties, 

characteristics, and/or identities of a material and/or biological entity. For example, 

characterization tests could include determination of agent strain, viability, or transmissibility.

Clinical laboratory: Facility for the biological, microbiological, serological, chemical, 

immunohematological, biophysical, cytological, pathological, or other examination of clinical 

samples (see below) to provide information for the diagnosis, prevention, or treatment of any 

disease or impairment; or of assessing the health of humans, animals, or plants.

Clinical sample: A discrete, unaltered portion taken from a human, animal, or plant for the 

purpose of examination, study, or analysis to inform diagnosis and treatment. 

Detection: Initial determination of the presence or absence of an agent or target in a given 

matrix; for example, detection of a nucleic acid signature of a known threat in physiological 

tissues, soil samples, or in an aerosol monitoring system.

Diagnosis: Interpretation of diagnostic (see below) result(s) to inform treatment and control 

options.

Diagnostic: Reagents, instruments, and systems intended for use in diagnosis of disease or other 

conditions, including a determination of the state of health, in order to cure, mitigate, treat, or 

prevent disease or its sequelae.

Non-diagnostic sample: Any sample from the environment, food, plants, animals, or humans 

analyzed for surveillance or detection purposes but not used in a treatment decision.

Identification: Determination of specific details about an agent present in a given environment, 

matrix, or clinical sample. For example, identification includes strain classification coupled with 

expressed plasmids and mapped antibiotic resistance genes.

Laboratory: Facility for the biological, microbiological, serological, chemical, 

immunohematological, biophysical, cytological, pathological, or other examination of nondiagnostic samples.

Point-of-need (PON): Analysis performed by non-medical personnel in close proximity to 

sample collection point. For example, field analysis of white powders, use of home pregnancy 

tests, or surveillance for pathogens and pests at ports of entry.

Point-of-care (POC): Analysis of pathogen presence and/or exposure in the health care 

environment immediately surrounding a patient. Examples include bed-side tests in a medical 

unit, ambulance, or mobile transport vehicle, or a physician’s office.

Signature: Unique identifying component of a threat (e.g., for biological samples; nucleic acids, 

proteins, etc.).
B-1

Appendix B

BST WG Sub-working group Membership

Aberration Detection

Taha Kass-Hout – CO-CHAIR

Department of Health and Human Services 

Food and Drug Administration

Charles Liarakos – CO-CHAIR

National Science Foundation

Russ Bulluck

Department of Agriculture

Animal and Plant Health Inspection Service

Randall Levings

Department of Agriculture

Animal and Plant Health Inspection Service

Geoff Scott

Department of Commerce

National Oceanic and Atmospheric Administration

Julie Pavlin

Department of Defense

Armed Forces Health Surveillance Center

Chris Kiley

Department of Defense

Defense Threat Reduction Agency

Joint Science and Technology Office

Scott Remine

Department of Defense

Joint Program Executive Office for Chemical and 

Biological Defense

Seth Foldy

Department of Health and Human Services 

Centers for Disease Control and Prevention 

Carole Heilman

Department of Health and Human Services 

National Institutes of Health

Nancy Jones

Department of Health and Human Services

National Institutes of Health

Patricia Strickler-Dinglasan

Department of Health and Human Services 

National Institutes of Health

Samantha Gibbs

Department of the Interior

U.S. Fish and Wildlife Center

Adam Kramer

Department of the Interior

National Park Service

Jonathan Sleeman

Department of the Interior

U.S. Geological Survey

National Wildlife Health Center
B-2

Risk Anticipation

Geoff Scott – CO-CHAIR

Department of Commerce

National Oceanic and Atmospheric Administration

Glenn Dowling – CO-CHAIR

Department of Defense

National Center for Medical Intelligence

Adia Bogossian

Department of Agriculture

Animal and Plant Health Inspection Service

Ron Sequeira

Department of Agriculture

Animal and Plant Health Inspection Service

Andrew Wilds

Department of Agriculture

Animal and Plant Health Inspection Service

Jan Carson

Department of Commerce

National Oceanic and Atmospheric Administration

Felix Kogan

Department of Commerce

National Oceanic and Atmospheric Administration

Chris Miller

Department of Commerce

National Oceanic and Atmospheric Administration

Madeline Thomson

Department of Commerce

National Oceanic and Atmospheric Administration

Thiaw Wassila

Department of Commerce

National Oceanic and Atmospheric Administration

Christopher Perdue

Department of Defense

Armed Forces Health Surveillance Center

Roger Breeze

Department of Defense

Defense Threat Reduction Agency

Joint Science and Technology Office

Erica Carroll

Department of Defense

Defense Threat Reduction Agency

Joint Science and Technology Office

Bob Huffman

Department of Defense

Joint Program Executive Office for Chemical and 

Biological Defense

Dylan George

Department of Defense

National Center for Medical Intelligence

Nathaniel Hupert

Department of Health and Human Services 

Centers for Disease Control and Prevention 

Carole Heilman

Department of Health and Human Services 

National Institutes of Health

Nancy Jones

Department of Health and Human Services 

National Institutes of Health

Patricia Strickler-Dinglasan

Department of Health and Human Services 

National Institutes of Health

David Wong

Department of the Interior 

National Park Service

Ed Espinoza

Department of the Interior

U.S. Fish and Wildlife Service

John Pearce

Department of the Interior

U.S. Geological Survey

Debra Gulick

Department of State

Gary Resnick

Los Alamos National Laboratory

Helen Cui

Los Alamos National Laboratory
B-3

Threat Identification and Characterization

Anne Hultgren – CO-CHAIR

Department of Homeland Security

Science and Technology Directorate

Clay Holloway – CO-CHAIR

Department of Defense

Office of the Assistant Secretary of Defense for 

Nuclear, Chemical, and Biological Defense 

Programs

Robert von Tersch – CO-CHAIR

Office of the Assistant Secretary of Defense for 

Nuclear, Chemical, and Biological Defense 

Programs

Randall Levings

Department of Agriculture 

Animal and Plant Health Inspection Service

Laurene Levy

Department of Agriculture 

Animal and Plant Health Inspection Service

Mike McIntosh

Department of Agriculture 

Animal and Plant Health Inspection Service

Scott Cross

Department of Commerce

National Oceanic and Atmospheric Administration

Luther Lindler

Department of Defense

Armed Forces Health Surveillance Center

Eric Van Gieson

Department of Defense

Defense Threat Reduction Agency

Joint Science and Technology Office

Scott Remine

Department of Defense

Joint Program Executive Office for Chemical and 

Biological Defense

Philip LoBue

Department of Health and Human Services

Centers for Disease Control and Prevention

Patricia Strickler-Dinglasan

Department of Health and Human Services 

National Institutes of Health

Richard Kellogg

Department of Health and Human Services

Centers for Disease Control and Prevention

Sally Hojvat

Department of Health and Human Services

Food and Drug Administration

Carole Heilman

Department of Health and Human Services 

National Institutes of Health

Nancy Jones

Department of Health and Human Services 

National Institutes of Health

Jessica Appler

Department of Homeland Security 

Science and Technology Directorate

Sara Newman

Department of the Interior

National Park Service

Jonathan Sleeman

Department of the Interior

U.S. Geological Survey

National Wildlife Health Center

Sanjiv Shah

Environmental Protection Agency
B-4

Information Integration, Analysis, and Sharing

Tom Bates – CO-CHAIR

Lawrence Livermore National Laboratory

Gary Roselle – CO-CHAIR

Department of Veterans Affairs

Shantini Gamage – CO-CHAIR

Department of Veterans Affairs

Lynn Tracey

Department of Agriculture

Animal and Plant Health Inspection Service

Rick Zink

Department of Agriculture

Animal and Plant Health Inspection Service

Scott Cross

Department of Commerce

National Oceanic and Atmospheric Administration

Rohit Chitale

Department of Defense 

Armed Forces Health Surveillance Center

John Hannan

Department of Defense

Defense Threat Reduction Agency Joint Science

and Technology Office

Nancy Nurthen

Department of Defense

Defense Threat Reduction Agency Joint Science

and Technology Office

Deena Disraelly

Department of Defense

Joint Program Executive Office for Chemical and 

Biological Defense

Karen House

Department of Defense

Joint Program Executive Office for Chemical and 

Biological Defense

Jennifer Olson

Department of Health and Human Services

Biomedical Advanced Research and Development 

Authority

William Morrill

Department of Health and Human Services

Centers for Disease Control and Prevention

Carole Heilman

Department of Health and Human Services 

National Institutes of Health

Nancy Jones

Department of Health and Human Services 

National Institutes of Health

Patricia Strickler-Dinglasan

Department of Health and Human Services 

National Institutes of Health

Teresa Quitugua

Department of Homeland Security

Office of Health Affairs

Jessica Appler

Department of Homeland Security 

Science and Technology Directorate

Charlie Stroup

Department of Veterans Affairs

John Quinn

Department of Veterans Affairs

Ray Arthur

Department of Health and Human Services

Centers for Disease Control and Prevention

Molly Brown

National Aeronautics and Space Administration Clyde Manning

Office of the Director of National Intelligence

Chris Decker

Office of the Director of National Intelligence