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Syndromic Surveillance for Zoonotic Diseases

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Syndromic Surveillance for Zoonotic Diseases USING PRE-DIAGNOSTIC DATA FROM VETERINARY LABORATORIES TO DETECT DISEASE OUTBREAKS IN COMPANION ANIMALS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Loren Eldon Shaffer, MPH ***** The Ohio State University 2007 Dissertation Committee: Approved by Professor William J.A. Saville, Advisor Professor Julie Funk Professor Päivi Rajala-Schultz ______________________________________ Advisor Professor Michael M. Wagner Graduate Program in Veterinary Preventive Medicine Professor Thomas E. Wittum ABSTRACT Emerging infectious diseases and the threat of bioterrorism have fostered a desire for improved timeliness of outbreak detection. Traditional disease reporting is reliant on confirmed diagnoses, often involving laboratory analysis that may require days to complete. Most emerging infectious and bioweapon pathogens are zoonotic organisms. Detection of zoonotic outbreaks has often relied on the identification of human cases. We investigated how data from veterinary diagnostic laboratories (VDLs) might contribute to earlier outbreak detection efforts in Ohio. We began by determining the representation of animal species in the data and evaluating the representation of human households. Companion animals comprised 98.1% of the total number of specimens submitted to a commercial, nation-wide VDL from clinics in Ohio in one year. Using estimates derived from a survey of pet owners, we determined that these data represented approximately 6.6% of Ohio households. The value of microbiology test orders was determined by quantifying the representation and potential gain in timeliness from two VDL datasets. We also investigated the potential to determine estimated count values from historical records and detect significant increases in these values using statistical-based detection methods. The data represented specimens from mostly companion animals (85.0% and 74.3%) followed by horses (8.2% and 17.2%). We determined a potential gain of timeliness in outbreak ii detection of three to five days. We developed baselines of microorganism incidence and total microbiology orders from the datasets and detected some of the clusters of pathogen-specific isolates by analyzing the weekly totals of all microbiology orders. We demonstrated how someone might use these data in a prospective system to detect outbreaks of disease earlier than traditional methods. Case reviews from a pilot system indicated the potential benefit to public health as well as veterinary community. We concluded from these investigations that: 1) data from VDLs do possess certain qualities that validate their value for syndromic surveillance, 2) these data may be especially useful for surveillance in companion animals, and 3) earlier detection of certain disease outbreaks may be possible from a prospective system using VDL data. iii Dedicated to my wife Kelly for her support, partnership, and patience; and to our children Taylor, Alex, Hunter, and Nate. May their dreams become their reality. iv ACKNOWLEDGMENTS I wish to thank all of my advisors for their support, interest, and guidance during my program. To Drs. Julie Funk, Päivi Rajala-Schultz, and Tom Wittum, I greatly appreciate the insights and advice regarding veterinary issues that were outside of my experience. My deepest appreciation is extended to Dr. William Saville, for his guidance and mentorship in academic, political, and common sense matters. Thank you, Dr. Saville, for your humble nature and curiosity that provided me the opportunity to explore something new to us both. I am also much indebted to Dr. Mike Wagner for his willingness to share his insights on public health surveillance, informatics, and the interactions that are necessary on many fronts to make things work. I am thankful for your honest and straightforward approach. My thanks are also extended to Dr. Bob Campbell for his support of my decision to enter this program while working for him full-time. Your confidence in me did not go unnoticed and your words of encouragement seemed to come at just the right time. I also offer my appreciation to Dr. Richard Bednarski, Bobbi Schmidt, and Fred Marker at The Ohio State University Veterinary Teaching Hospital for providing me some of the data resources critical to this research. Thanks also to Dr. Bill Wallen, Dr. Dave Fisher, Dr. Jocelyn Johnsrude, Gary Watson, Robert Ledford, and Bill Davis at IDEXX Laboratories, Inc. not only for providing me access to data resources but v especially for helping me to learn what to ask for and how to understand it. Dr. Garrick Wallstrom at the RODS Laboratory and Steve DeFrancesco and Kevin Hutchison, both formerly of the RODS Laboratory, are also much due my gratitude for assisting me with both IT and statistical support and advice. For all those others not listed specifically that helped me during these years I am no less grateful. Your support and help came in many different forms. I am thankful for it all. Lastly, I would humbly offer my gratitude to Rick and Pat Thrall. Although you acquired me as a son-in-law, you both accepted me as if I was your own. My own parents long since passed, I appreciate having you as my “Dad” and “Mom.” The pride you often expressed helped me many times to maintain my motivation. vi VITA August 15, 1962 …………………………Born – Lancaster, Ohio 2003 …………………………………….. MPH, The Ohio State University 2000 - 2003 …………………………….. Preventive Medicine Officer United States Army Reserve Special Operations Command 2003 - 2004 …………………………….. Emergency Preparedness Manager Franklin County Board of Health Columbus, Ohio 2004 - present ………………………….. Early Event Surveillance Supervisor Ohio Department of Health Columbus, Ohio PUBLICATIONS 1. L. E. Shaffer, “Syndromic Surveillance.” The Ohio Department of Health Infectious Disease Quarterly. 2005; 2(2): 1-4. 2. M. W. Wagner, L.E. Shaffer, and R. Shephard, “Biosurveillance Systems.” in Handbook of Biosurveillance. Elsevier Press, New York, NY, 2006. 3. R. Aryl, R. Shephard, and L. E. Shaffer, “Animal Health.” in Handbook of Biosurveillance. Elsevier Press, New York, NY, 2006. 4. L. E. Shaffer, S. A. Rowe, and D. E. Reed, “Early Detection of Influenza-like Illness: Developing a Multi-Variate Approach.” (Abstract) Advances in Disease Surveillance. 2007; 2(65): 67. 5. L. E. Shaffer, J. A. Funk, P. Rajala-Schultz, M. M. Wagner, T. E. Wittum, W. J. A. Saville. “Evaluation of Veterinary Diagnostic Laboratories as a Possible Data Source for Prospective Outbreak Surveillance.” (Abstract) Advances in Disease Surveillance. 2007; 2(66): 119. vii 6. L. E. Shaffer, J. A. Funk, P. Rajala-Schultz, G. Wallstrom, M. M. Wagner, T. E. Wittum, W. J. A. Saville. “Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory.” Lecture Notes in Computer Science. 2007; 4506:1-10. 7. L. E. Shaffer, J. A. Funk, P. Rajala-Schultz, M. M. Wagner, T. E. Wittum, W. J. A. Saville. “Evaluation of Microbiology Orders from Two Veterinary Diagnostic Laboratories as Potential Data Source for Early Outbreak Detection.” Advances in Disease Surveillance. 2007; forthcoming. 8. L. E. Shaffer, J. A. Funk, P. Rajala-Schultz, M. M. Wagner, T. E. Wittum, W. J. A. Saville. “Clinical Rotation of Senior Veterinary Students as a Confounder for Outbreak Detection Using Microbiology Orders in a Veterinary Teaching Hospital.” Journal of Veterinary Medical Education. Under review. 9. L. E. Shaffer, J. A. Funk, P. Rajala-Schultz, M. M. Wagner, T. E. Wittum, W. J. A. Saville. “Contributing to a One-Medicine Approach: Cross-Species Disease Surveillance.” Public Health Reports. 2008; Invited paper in preparation. FIELDS OF STUDY Major Field: Veterinary Preventive Medicine viii TABLE OF CONTENTS Page Abstract ……………………………………………………………………….…………..ii Dedication ………………………………………………………………………………..iv Acknowledgments ………………………………………………………………………..v Vita ……………………………………………………………………………………...vii List of Tables …………………………………………………………………………....xii List of Figures …………………………………………………………………………..xiv Chapters: 1. Introduction …………………………………………………………………….....1 2. Literature Review ……………………………………………….………………...7 2.1 Bioterrorism ………………………………………………….……………….7 2.2 Emerging Infectious Diseases .………….…………………………………….8 2.3 Deficiencies in Detecting Outbreaks ………………………………………..10 2.4 Syndromic Surveillance ……………………………………….…………….13 2.4.1 Improving the Timeliness of Detection …………………………...16 2.4.2 Detection Methods ………..……………………………………….17 2.4.3 Limitations ………………………………………………………...19 2.5 “One-Medicine” and Animals as Sentinel Indicators ………………....…….21 2.6 Animal-based Syndromic Surveillance Initiatives …………………………..23 2.7 Summary …………………………………………………………………….25 3. Sentinel Surveillance of Human Households Using Companion Animals .….....41 3.1 Abstract ...……………………………………………………………………41 3.2 Introduction ………………………………………………………………….42 ix 3.3 Methods ……………………………………………………………………...43 3.3.1 American Veterinary Medical Association Survey …................….43 3.3.2 Data Sample ……………………………………………………….43 3.3.3 Calculations ………………………………………………………..44 3.4 Results ……………………………………………………………………….46 3.5 Discussion ….………………………………………………………………..46 4. Evaluation of Microbiology Orders from Two Veterinary Diagnostic Laboratories as Potential Data Sources for Early Outbreak Detection ………….53 4.1 Abstract ……………………………………………………………………...53 4.2 Introduction ……………………………………………………………….…54 4.3 Methods ……………………………………………………………………..57 4.3.1 Data Sample ……………………………………………………….57 4.3.2 Statistical Analysis
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