One health in the U.S. military: a review of existing systems and recommendations for the future
Date
2014
Authors
Evans, Rebecca I., author
Salman, Mo, advisor
Lappin, Michael, committee member
Hayne, Stephen, committee member
Peel, Jennifer, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Background: The merging of the former U.S. Army Veterinary Command (VETCOM) with the former U.S. Army Center for Health Promotion and Preventive Medicine (USACHPPM) into the U.S. Army Public Health Command (USAPHC) in 2011 created an opportunity for the military to fully embrace the One Health concept. That same year, the USAPHC began work on a Zoonotic Disease Report (ZDR) aimed at supporting critical zoonotic disease risk assessments by combining zoonotic disease data from human, entomological, laboratory, and animal data sources. The purpose of this dissertation is to facilitate the creation of a military Zoonotic Disease Surveillance program that combines disease data from both military human and animal sources. Methods: Five of the most commonly used human military medical data systems were systematically reviewed using a standardized template based on Centers for Disease Control and Preventive Medicine (CDC) guidelines. The systems were then compared to each other in order to recommend the one(s) best suited for use in the USAPHC ZDR. The first stage of the comparison focused on each system's ability to meet the specific goals and objectives of the ZDR, whereas the second stage applied capture-recapture methodology to data system queries in order to evaluate each system's data quality (completeness). A pilot study was conducted using Lyme borreliosis to investigate the utility of military pet dogs as sentinel surveillance for zoonotic disease in military populations. Canine data came from 3996 surveys collected from 15 military veterinary facilities from 1 November 2012 through 31 October 2013. Surveys simultaneously collected Borrelia burgdorferi (Bb) seroprevalence and canine risk factor data for each participating pet dog. Human data were obtained by querying the Defense Medical Surveillance System for the same 15 military locations and the same time period. The correlation of military pet dog Bb seroprevalence and military human Lyme disease (borreliosis) data was estimated using the Spearman Rank Correlation. The difference between military pet dog data and civilian pet dog data was examined through the use of the chi-squared test for proportions. Multivariable logistic regression was then used to investigate the potential for identified risk factors to impact the observed association. Results: The comparison of human military medical data systems found the Military Health System Management Analysis and Reporting Tool (M2) data system most completely met the specific goals and objects of the ZDR. In addition, completeness calculation showed the M2 data source to be the most complete source of human data; 55% of total captured cases coming from the M2 system alone. The pilot study found a strong positive correlation between military human borreliosis data and military pet dog Bb seroprevalence data by location (rs = 0.821). The study showed reassuring similarities in pet dog seroprevalence by location for the majority of sites, but also showed meaningful differences between two locations, potentially indicating military pet dogs as more appropriate indicators of Lyme disease risk for military populations than civilian pet dog data. Unfortunately, whether canine Bb seroprevalence is influenced by the distribution of identified risk factors could not be determined due to limited study power. Conclusions: Based on this study M2 was recommended as the primary source of military human medical data for use in the Public Health Command Zoonotic Disease Report. In addition, it was recommended that Service member pet dog data be incorporated as a sensitive and convenient measure of zoonotic disease risk in human military populations. The validity of the data, however, should be evaluated further with either larger sample sizes and/or a zoonotic disease with higher prevalence.
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Subject
zoonotic disease
capture-recapture
surveillance