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ABSTRACT: In the last half century, significant attention has been given to animal diseases; however, our understanding of disease processes and how to manage them at the livestock-wildlife interface remains limited. In this study, we conduct a systematic review of the scientific literature to evaluate the status of diseases at the livestock-wildlife interface in the United States. Specifically, the goals of the literature review were three fold: first to evaluate domestic animal diseases currently found in the United States where wildlife may play a role; second to identify critical issues faced in managing these diseases at the livestock-wildlife interface; and third to identify potential technical and policy strategies for addressing these issues. We found that of the 86 avian, ruminant, swine, poultry, and lagomorph diseases that are reportable to the World Organization for Animal Health (OIE), 53 are present in the United States; 42 (79%) of these have a putative wildlife component associated with the transmission, maintenance, or life cycle of the pathogen; and 21 (40%) are known to be zoonotic. At least six of these reportable diseases-bovine tuberculosis, paratuberculosis, brucellosis, avian influenza, rabies, and cattle fever tick (vector control)-have a wildlife reservoir that is a recognized impediment to eradication in domestic populations. The complex nature of these systems highlights the need to understand the role of wildlife in the epidemiology, transmission, and maintenance of infectious diseases of livestock. Successful management or eradication of these diseases will require the development of cross-discipline and institutional collaborations. Despite social and policy challenges, there remain opportunities to develop new collaborations and new technologies to mitigate the risks posed at the livestock-wildlife interface.
Preventive Veterinary Medicine 12/2012; · 2.05 Impact Factor
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ABSTRACT: Outbreaks of avian influenza in North American poultry have been linked to wild waterfowl. A first step towards understanding where and when avian influenza viruses might emerge from North American waterfowl is to identify environmental and demographic determinants of infection in their populations. Laboratory studies indicate water temperature as one determinant of environmental viral persistence and we explored this hypothesis at the landscape scale. We also hypothesized that the interval apparent prevalence in ducks within a local watershed during the overwintering season would influence infection probabilities during the following breeding season within the same local watershed. Using avian influenza virus surveillance data collected from 19,965 wild waterfowl across the contiguous United States between October 2006 and September 2009 We fit Logistic regression models relating the infection status of individual birds sampled on their breeding grounds to demographic characteristics, temperature, and interval apparent prevalence during the preceding overwintering season at the local watershed scale. We found strong support for sex, age, and species differences in the probability an individual duck tested positive for avian influenza virus. In addition, we found that for every seven days the local minimum temperature fell below zero, the chance an individual would test positive for avian influenza virus increased by 5.9 percent. We also found a twelve percent increase in the chance an individual would test positive during the breeding season for every ten percent increase in the interval apparent prevalence during the prior overwintering season. These results suggest that viral deposition in water and sub-freezing temperatures during the overwintering season may act as determinants of individual level infection risk during the subsequent breeding season. Our findings have implications for future surveillance activities in waterfowl and domestic poultry populations. Further study is needed to identify how these drivers might interact with other host-specific infection determinants, such as species phylogeny, immunological status, and behavioral characteristics.
PLoS ONE 01/2012; 7(3):e32729. · 4.09 Impact Factor
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ABSTRACT: In 2008, the Indonesian Government implemented a revised village-level Participatory Disease Surveillance and Response (PDSR) program to gain a better understanding of both the magnitude and spatial distribution of H5N1 highly pathogenic avian influenza (HPAI) outbreaks in backyard poultry. To date, there has been considerable collection of data, but limited publically available analysis. This study utilizes data collected by the PDSR program between April 2008 and September 2010 for Java, Bali and the Lampung Province of Sumatra. The analysis employs hierarchical Bayesian occurrence models to quantify spatial and temporal dynamics in backyard HPAI infection reports at the District level in 90 day time periods, and relates the probability of HPAI occurrence to PDSR-reported village HPAI infection status and human and poultry density. The probability of infection in a District was assumed to be dependent on the status of the District in the previous 90 day time period, and described by either a colonization probability (the probability of HPAI infection in a District given there had not been infection in the previous 90 day time period) or a persistence probability (the probability of HPAI infection being maintained in the District from the previous to current 90 day period). Results suggest that the number of surveillance activities in a district had little relationship to outbreak occurrence probabilities, but human and poultry densities were found to have non-linear relationships to outbreak occurrence probabilities. We found significant spatial dependency among neighboring districts, indicating that there are latent spatial processes that are not captured by the covariates available for this study, but which nonetheless impact outbreak dynamics. The results of this work may help improve understanding of the seasonal nature of H5N1 in poultry and the potential role of poultry density in enabling endemicity to occur, as well as to assist the Government of Indonesia target scarce resources to regions and time periods when outbreaks of HPAI in poultry are most likely to occur.
Preventive Veterinary Medicine 09/2011; 102(3):206-17. · 2.05 Impact Factor
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ABSTRACT: Rabies is an acute viral infection that is typically fatal. Most rabies modeling has focused on disease dynamics and control within terrestrial mammals (e.g., raccoons and foxes). As such, rabies in bats has been largely neglected until recently. Because bats have been implicated as natural reservoirs for several emerging zoonotic viruses, including SARS-like corona viruses, henipaviruses, and lyssaviruses, understanding how pathogens are maintained within a population becomes vital. Unfortunately, little is known about maintenance mechanisms for any pathogen in bat populations. We present a mathematical model parameterized with unique data from an extensive study of rabies in a Colorado population of big brown bats (Eptesicus fuscus) to elucidate general maintenance mechanisms. We propose that life history patterns of many species of temperate-zone bats, coupled with sufficiently long incubation periods, allows for rabies virus maintenance. Seasonal variability in bat mortality rates, specifically low mortality during hibernation, allows long-term bat population viability. Within viable bat populations, sufficiently long incubation periods allow enough infected individuals to enter hibernation and survive until the following year, and hence avoid an epizootic fadeout of rabies virus. We hypothesize that the slowing effects of hibernation on metabolic and viral activity maintains infected individuals and their pathogens until susceptibles from the annual birth pulse become infected and continue the cycle. This research provides a context to explore similar host ecology and viral dynamics that may explain seasonal patterns and maintenance of other bat-borne diseases.
Proceedings of the National Academy of Sciences 06/2011; 108(25):10208-13. · 9.68 Impact Factor
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ABSTRACT: Environmental factors-especially soil properties-have been suggested as potentially important in the transmission of infectious prion diseases. Because binding to montmorillonite (an aluminosilicate clay mineral) or clay-enriched soils had been shown to enhance experimental prion transmissibility, we hypothesized that prion transmission among mule deer might also be enhanced in ranges with relatively high soil clay content. In this study, we report apparent influences of soil clay content on the odds of prion infection in free-ranging deer. Analysis of data from prion-infected deer herds in northern Colorado, USA, revealed that a 1% increase in the clay-sized particle content in soils within the approximate home range of an individual deer increased its odds of infection by up to 8.9%. Our findings suggest that soil clay content and related environmental properties deserve greater attention in assessing risks of prion disease outbreaks and prospects for their control in both natural and production settings.
Nature Communications 02/2011; 2:200. · 7.40 Impact Factor
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ABSTRACT: Determining if outbreak data collected by regional or international organizations can reflect patterns observed in more detailed data collected by national veterinary services is a necessary first step if global databases are to be used for making inference about determinants of disease maintenance and spread and for emergency planning and response. We compared two data sources that capture spatial and temporal information about H5N1 highly pathogenic avian influenza outbreaks reported since 2004 in four countries: Bangladesh, Egypt, Turkey, and Vietnam. One data source consisted of reports collected as part of each country's national veterinary services surveillance program, while the other data source included reports collected using the Emergency Prevention System for Priority Animal and Plant Pests and Diseases (EMPRES-i) global animal health information system. We computed Spearman rank-order correlation statistics to compare spatial and temporal outbreak distributions, and applied a space-time permutation test to check for consistency between the two data sources. Although EMPRES-i typically captured fewer outbreaks than detailed national reporting data, the overall similarity in space and time, particularly after 2006, reflect the ability of the EMPRES-i system to portray disease patterns comparable to those observed in national data sets. Specifically, we show that the two datasets exhibit higher positive correlations in outbreak timing and reported locations after 2006 when compared to December 2003 through 2006. Strengthening the capacity of global systems to acquire data from national and regional databases will improve global analysis efforts and increase the ability of such systems to rapidly alert countries and the international community of potential disease threats.
Preventive Veterinary Medicine 04/2010; 95(3-4):175-85. · 2.05 Impact Factor
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Paul F. Doherty,
Colleen T. Webb,
Jennifer A. Hoeting,
Andrew A. Merton,
Ryan S. Miller, Matthew L. Farnsworth,
B Alan,
Robert G. McLean,
Toni J. Piaggio,
Gordon C. Reese,
Michele M. Gilbert,
Amy J. Davis,
Kenneth R. Wilson
01/2009; Colorado State University.
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Seth C. Britch,
Kenneth J. Linthicum,
Barry R. Miller,
John T. Roehrig,
Pierre E. Rollin,
Chester G. Moore,
Christy A. Tedrow,
Assaf Anyamba,
Judy Akina,
Kristine E. Bennett, [......],
Jeffrey Root,
Jack C. Rhyan,
Daniel A. Strickman,
Steven J. Sweeney,
Sherrilyn H. Wainwright,
Todd Weaver,
William C. Wilson,
Franco Basile,
Scott N. Miller,
Li Zou
Emerging Infectious Diseases. 01/2007; 13.
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ABSTRACT: Observed spatial patterns in natural systems may result from processes acting across multiple spatial and temporal scales. Although spatially explicit data on processes that generate ecological patterns, such as the distribution of disease over a landscape, are frequently unavailable, information about the scales over which processes operate can be used to understand the link between pattern and process. Our goal was to identify scales of mule deer (Odocoileus hemionus) movement and mixing that exerted the greatest influence on the spatial pattern of chronic wasting disease (CWD) in northcentral Colorado, USA. We hypothesized that three scales of mixing (individual, winter subpopulation, or summer subpopulation) might control spatial variation in disease prevalence. We developed a fully Bayesian hierarchical model to compare the strength of evidence for each mixing scale. We found strong evidence that the finest mixing scale corresponded best to the spatial distribution of CWD infection. There was also evidence that land ownership and habitat use play a role in exacerbating the disease, along with the known effects of sex and age. Our analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight when process data are sparse or unavailable.
Ecological Applications 07/2006; 16(3):1026-36. · 5.10 Impact Factor
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ABSTRACT: The authors present findings from two landscape epidemiology studies of chronic wasting disease (CWD) in northern Colorado mule deer (Odocoileus hemionus). First, the effects of human land use on disease prevalence were explored by formulating a set of models estimating CWD prevalence in relation to differences in human land use, sex and geographic location. Prevalence was higher in developed areas and among male deer suggesting that anthropogenic influences (changes in land use), differences in exposure risk between sexes and landscape-scaled heterogeneity are associated with CWD prevalence. The second study focused on identifying scales of mule deer movement and mixing that had the greatest influence on the spatial pattern of CWD in north-central Colorado. The authors hypothesised that three scales of mixing - individual, winter subpopulation and summer subpopulation - might control spatial variation in disease prevalence. A fully Bayesian hierarchical model was developed to compare the strength of evidence for each mixing scale. Strong evidence was found indicating that the finest mixing scale corresponded best to the observed spatial distribution of CWD prevalence. This analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight into the epidemiology of wildlife diseases when process data are sparse or unavailable.
Veterinaria italiana 43(3):581-93. · 0.67 Impact Factor
