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Volume 12, Number 1—January 2006

Conference Summary

Materials Available Online Only

Epidemiologic Applications of Emerging Infectious Disease Modeling To Support US Military Readiness and National Security

Jean-Paul Chretien*Comments to Author , Kenneth J. Linthicum†, Julie A. Pavlin‡, Joel C. Gaydos*, and Joseph L. Malone*
Author affiliations: *Department of Defense Global Emerging Infections Surveillance & Response System (DoD-GEIS), Silver Spring, Maryland, USA; †US Department of Agriculture–Agricultural Research Service Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, Florida, USA; ‡Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA

Suggested citation for this article

Emerging Infectious Disease Modeling: Epidemiologic Applications in the Department of Defense

Silver Spring, MD, USA

August 3, 2005

Advances in epidemiologic modeling offer new opportunities for emerging infectious disease (EID) prediction, detection, and control. Recent applications across diverse fields include simulations of pandemic influenza to evaluate containment strategies (1,2), ecologic niche modeling to identify potential reservoirs for Ebola and Marburg viruses (3), and statistical algorithms for detecting natural outbreaks and bioterrorism in syndromic surveillance systems (4,5). The US Department of Defense (DoD) uses epidemiologic modeling to detect and respond to EIDs that threaten US military personnel, their families, or national security (6). DoD applications include collaborations with other federal agencies, national laboratories, and universities. On August 3, 2005, the DoD–Global Emerging Infections Surveillance and Response System (DoD–GEIS) hosted a symposium to develop plans and recommendations for current and future applications of EID modeling in DoD, including collaborations with nonmilitary organizations.

The symposium was entitled Emerging Infectious Disease Modeling: Epidemiologic Applications in the DoD. It included 45 participants who represented 20 DoD and non-DoD organizations (Appendix). Brief presentations and facilitated discussion focused on 3 areas in which DoD uses EID modeling systems (composed of software and statistical methods): satellite-based measurements of environmental characteristics to predict pathogen niches or disease transmission dynamics (i.e., the remote sensing area), syndromic surveillance systems to rapidly detect natural disease outbreaks or bioterrorism (syndromic surveillance), and simulation of natural outbreaks or bioterrorism to evaluate response preparedness (epidemiologic simulation).

Presentations described relevant DoD and non-DoD work in these areas (presentation files are available on the DoD-GEIS secure website; government organizations and collaborators and academic institutions may request access to the secure site from the DoD-GEIS homepage, http://www.geis.fhp.osd.mil/). During discussion in all 3 areas, participants recommended better coordination and communication between the developers and end-users of modeling systems. Participants suggested expansion of training for modeling system users to facilitate wider and more appropriate use of available systems and formal feedback mechanisms to improve developer appreciation of user needs. The need to specifically define the desired outcomes for a modeling system and to evaluate the performance of the system in achieving the outcomes and cost was also identified.

Participants recommended that consortia composed of DoD and non-DoD groups in each of the 3 areas be developed to share expertise and resources. Participants in the remote sensing discussion noted that DoD and non-DoD funding to support widespread integration of existing modeling systems into epidemiologic surveillance and response networks is limited, despite promising pilot studies (7). Participants suggested that organizations that use remote sensing in DoD collaborate to leverage resources, share expertise, and avoid duplications, and that these organizations develop partnerships with non-DoD organizations that have expertise or convergent goals. Specifically mentioned non-DoD organizations were the Centers for Disease Control and Prevention (CDC), the Department of Homeland Security, the National Oceanographic and Atmospheric Administration, the US Geological Survey, the US Department of Agriculture, academic centers, and state and local public health and agricultural departments.

Syndromic surveillance discussants noted that the proliferation of syndromic surveillance systems (civilian and military) has generated substantial practical experience but that this experience is not adequately captured, distilled, and disseminated. Also, duplicate systems that cover identical populations can provide conflicting interpretations, which results in confusion and dissatisfaction among system users. Participants recommended that operators of the global DoD syndromic surveillance system, the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) (8,9), and developers of future DoD syndromic surveillance systems continue collaborations with CDC, academic centers, healthcare systems, public health departments, and other appropriate organizations with experience in syndromic surveillance to develop "best practices" and solutions to common problems. This conclusion is similar to a consensus position developed at an earlier DoD-GEIS workshop on health indicator surveillance (10). Discussants noted that, besides promoting application of successful strategies, cooperative consortia could improve system compatibility and decrease conflicting information that comes from shared data sources.

In the epidemiologic simulation discussion, representatives of US Northern Command, which conducts epidemic simulation exercises as part of its homeland defense mission, noted that the modeling systems used to support such exercises rely on varied assumptions and methods. These representatives suggested that attaining consensus on essential model parameters and basic assumptions among DoD and non-DoD stakeholders could facilitate more valid comparisons of response strategies across exercises and better cooperation in the event of a bioterrorist attack, which would likely require civilian-military cooperation. Participants also suggested improved collaboration in epidemic response exercises among exercise planners, modelers, and epidemiologists to make scenarios more realistic and to facilitate rapid, accurate projections by exercise participants.

Other recommendations were area-specific (the complete list of recommendations is on the DoD-GEIS secure website). Highlights for the remote sensing area included the following: developing temporal and spatial prediction models in support of US forces at risk for leishmaniasis in Iraq (11) and malaria in Korea (12); evaluating the feasibility of developing prediction models for influenza, which may be subject to environmental influences through direct effects on transmission or indirectly through bird migration patterns; and using environmental characteristics to refine models of expected rates of naturally occurring diseases, which could improve sensitivity and specificity of bioterrorism detection in surveillance systems. Highlights of the syndromic surveillance discussions included the following: exploring novel ways of using geographic information system data; ensuring that data collection procedures observe applicable privacy regulations; improving methods of integrating multiple data streams (e.g., syndromic, laboratory, pharmacy, environmental) to support decisions; and transferring modeling systems developed for ESSENCE and other systems in the United States to syndromic surveillance systems currently operating in resource-poor environments overseas. For epidemiologic simulation, the recommendation was made to identify organizations with demonstrated expertise in model development and operation for collaboration with DoD and civilian organizations that are developing simulation models or conducting exercises.

Discussants suggested that the proposed civilian-military consortia for remote sensing, syndromic surveillance, and epidemiologic simulation described above could identify, prioritize, and develop plans for problems and issues through regular, long-term collaboration. We agree and believe that DoD and non-DoD organizations will benefit from collaboration in preparing for bioterrorism, pandemic influenza, and other EIDs that threaten military and civilian populations alike.

Appendix

Affiliations of participants in symposium Emerging Infectious Disease Modeling: Epidemiologic Applications in the Department of Defense (DoD), August 3, 2005

DoD affiliations

  • Air Force Institute for Operational Health (AFIOH)

  • Armed Forces Medical Intelligence Center (AFMIC)

  • Defense Threat Reduction Agency (DTRA)

  • DoD-Global Emerging Infections Surveillance and Response System (DoD-GEIS)

  • Naval Health Research Center (NHRC)

  • Naval Medical Research Center Detachment (NMRCD) – Peru

  • Office of the Assistant Secretary of Defense (OASD) – Health Affairs

  • Uniformed Services University of Health Sciences (USUHS)

  • US Army Center for Health Promotion and Preventive Medicine (USACHPPM)

  • US Army Medical Research and Materiel Command (USAMRMC)

  • US Northern Command (USNORTHCOM)

  • Walter Reed Army Institute of Research (WRAIR)

Non-DoD affiliations

  • Centers for Disease Control and Prevention (CDC)

  • Harvard Medical School

  • Johns Hopkins Applied Physics Laboratory

  • Johns Hopkins Bloomberg School of Public Health

  • National Aeronautics and Space Administration (NASA)

  • University of Texas Health & Science Center at Houston

  • US Department of Agriculture (USDA)

  • Virginia Bioinformatics Institute at Virginia Tech

Acknowledgment

We thank the symposium participants for thoughtful presentations and discussion and Jennifer Rubenstein, Stephen Gubenia, and Jay Mansfield for administrative planning and support.

References

  1. Longini IM Jr, Nizam A, Xu S, Ungchusak K, Hanshaoworakul W, Cummings DA, Containing pandemic influenza at the source. Science. 2005;309:10838. DOIPubMed
  2. Ferguson NM, Cummings DA, Cauchemez S, Fraser C, Riley S, Meeyai A, Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature. 2005;437:20914. DOIPubMed
  3. Peterson AT, Bauer JT, Mills JN. Ecologic and geographic distribution of filovirus disease. Emerg Infect Dis. 2004;10:407.PubMed
  4. Buckeridge DL, Burkom H, Moore A, Pavlin J, Cutchis P, Hogan W. Evaluation of syndromic surveillance systems: design of an epidemic simulation model. MMWR Morb Mortal Wkly Rep. 2004;53(Suppl):13743.PubMed
  5. Buckeridge DL, Burkom H, Campbell M, Hogan WR, Moore AW. Algorithms for rapid outbreak detection: a research synthesis. J Biomed Inform. 2005;38:99113. DOIPubMed
  6. Presidential Decision Directive NSTC-7. 1996.
  7. Linthicum KJ, Anyamba A, Tucker CJ, Kelley PW, Myers MF, Peters CJ. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya. Science. 1999;285:397400. DOIPubMed
  8. Lombardo JS, Burkom H, Pavlin J. ESSENCE II and the framework for evaluating syndromic surveillance systems. MMWR Morb Mortal Wkly Rep. 2004;53(Suppl):15965.PubMed
  9. Lombardo J, Burkom H, Elbert E, Magruder S, Lewis SH, Loschen W, A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II). J Urban Health. 2003;80(Suppl 1):i3242.PubMed
  10. Pavlin JA, Mostashari F, Kortepeter MG, Hynes NA, Chotani RA, Mikol YB, Innovative surveillance methods for rapid detection of disease outbreaks and bioterrorism: results of an interagency workshop on health indicator surveillance. Am J Public Health. 2003;93:12305. DOIPubMed
  11. Centers for Disease Control and Prevention. Update: cutaneous leishmaniasis in U.S. military personnel—Southwest/Central Asia, 2002–2004. MMWR Morb Mortal Wkly Rep. 2004;53:2645.PubMed
  12. Feighner BH, Pak SI, Novakoski WL, Kelsey LL, Strickman D. Reemergence of Plasmodium vivax malaria in the republic of Korea. Emerg Infect Dis. 1998;4:2957. DOIPubMed

Suggested citation for this article: Chretien JP, Linthicum KJ, Pavlin JA, Gaydos JC, Malone JL. Epidemiologic applications of emerging infectious disease modeling to support US military readiness and national security [conference summary]. Emerg Infect Dis [serial on the Internet]. 2006 Jan [date cited]. http://dx.doi.org/10.3201/eid1201.051214

DOI: 10.3201/eid1201.051214

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Table of Contents – Volume 12, Number 1—January 2006

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Jean-Paul Chretien, Assistant Coordinator, Overseas Research Laboratories, Department of Defense Global Emerging Infections, Surveillance & Response System, Walter Reed Army Institute of Research, 503 Robert Grant Ave, Silver Spring, MD 20910-7500, USA: fax: 301-319-9213





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