Evaluating the association between climatic events and sheep condemnations in the United States using cluster analysis and spatio-temporal modeling
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1
Center for Animal Disease Modeling and Surveillance, School of Veterinary Medicine, University of California, Davis, United States
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2
Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, United States
Introduction:
Rising global temperatures have been associated with increases in extreme weather events, including heat waves, floods, droughts, and intense storms (1-5). Climate model projections forecast an ongoing increase in the frequency and intensity of these events (5). Climate change and these extreme weather events are associated with negative impacts on animal and human health through direct and indirect mechanisms (1-3). Direct effects of climate change on animal health include injury and death that occur during extreme weather events such as floods, storms, and wildfires, as well as health impacts that result from thermal stress. Indirect effects of climate change include amplification of vectors, pathogen development and range, impacts on crop yield and quality, and animal and human migrations that may impact contact rates, disease distribution, access to healthcare, and producer livelihood (1,2,6). Higher risk of parasitic infections, especially of flukes, have been associated with increasing temperature and precipitation (7). These risks are especially important for livestock on pasture. Infectious disease risk may compound over years of mild, wet, winters, that allow over-wintering of parasite and vector species (7).
Much of the work done on the effects of climate change on animal health has focused on cattle, and production outcomes (8-11). We believe that small ruminants can be even more sensitive to adverse climatic events, particularly if we consider that mitigation measures are implemented less frequently in small ruminants than in cattle. This study seeks to evaluate the association of climatic factors with sheep health outcomes in the United States using data collected on sheep condemnations at USDA FSIS inspected commercial slaughterhouses.
Methods:
Spatio-temporal analysis was performed at the scale of United States climate divisions and at yearly level. These are defined by the National Oceanic and Atmospheric Association (NOAA), and divide each state into regions of similar climate (12). Space-time cluster analysis under a discrete Poisson model was performed using SaTScan to identify high rate clusters in the period from 2005-2016 (13).
Regression modeling was used to assess the association of sheep condemnations with climate variables including average temperature (°F), maximum temperature (°F), minimum temperature (°F), total annual precipitation (inches), cooling degree days, heating degree days, minimum Palmer Drought Severity Index (PDSI), and maximum PDSI (12). For each condemnation cause, a model was generated selecting those variables with the best predictive ability for the rate of condemnation by disease for each climate division.
Results and Discussion:
The top causes of sheep condemnation from 2005-2016 were caseous lymphadenitis, cysticercosis, icterus, pneumonia and abscess/pyemia, respectively. Caseous lymphadenitis, cysticercosis, and pneumonia had annual variability and strong seasonal trends that suggested a possible climatic association with disease occurrence.
Caseous lymphadenitis is a zoonotic, infectious disease caused by the gram-positive intracellular coccobacillus Corynebacterium pseudotuberculosis (14). The disease is present worldwide, and is considered a disease of major importance for small ruminant producers in the United States. The disease is maintained onsite due to contamination of the environment. C. pseudotuberculosis survives well in the environment, surviving for up to 8 months in the soil. Moisture, organic material and shade enhance survivability (14). Within this dataset, caseous lymphadenitis had the highest number of condemnations in 2012, and demonstrated a seasonality peaking in October.
Ovine cysticercosis, also known as Cysticercus ovis or sheep measles, is caused by the cystic form of the dog tapeworm Taenia ovis (15,16). Sheep become infected after consuming hay or grass contaminated with tapeworm eggs passed in dog feces. While infection does not have major growth or health impacts on the sheep, it is associated with major economic losses due to carcass condemnation and trimming at slaughter (15). Eggs can survive for days to months in the environment, favoring cooler and moister climates. Within this dataset, the highest number of cysticercosis condemnations occurred in 2012, with seasonality peaking in early spring.
In sheep, pneumonia can be caused by a variety of bacterial, viral and parasitic causes (17). Many of the causative organisms are commensals. Susceptibility can be increased due to overcrowding, poor sanitation, high dust, high humidity, and stress (17). The highest number of pneumonia cases were observed in 2005 and 2012, with a seasonality peaking in late summer into early fall.
Model results support spatial-time clustering of sheep condemnations by cause across the United States. For caseous lymphadenitis, eight significant clusters were identified. The clusters spanned between 2-6 years, and were restricted to single climate divisions. The climate divisions were distributed across the United States. Cysticercosis had four significant clusters ranging from 4-6 years, also each within a single climate division. Pneumonia had four significant clusters, ranging from 2-6 years. Three of the clusters were a single climate division, but one cluster encompassed four climate zones covering most of California. There were two climate zones, one in New York and one in Colorado, that had significant clusters for all three diseases, with overlapping but non-identical time spans. This may suggest production sites with poor management in these areas.
We have identified climate zones in which multiple diseases contribute to high rates of condemnations that can be targeted for education and risk-based interventions. Regression modeling has allowed us to identify the climate variables with the strongest association with these disease outcomes, providing targets for management and mitigation strategies. Outcomes will be useful to quantify the impact of climatic events in sheep health and welfare, as well as to better inform livestock producers so they can implement mitigation strategies, particularly in those areas and time periods more affected by extreme weather events.
Acknowledgements
This study has been conducted with the support of the USDA-Formula Fund project #CALV-AH-392.
References
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Keywords:
Space-time cluster analysis,
Climate Change,
Regression modeling,
Condemnation,
Sheep,
Caseous lymphadenitis,
Cysticercosis
Conference:
GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.
Presentation Type:
Student oral presentation
Topic:
Spatial methods for environmental & exposure epidemiology and climate change
Citation:
O'Hara
KC,
Rowe
JD,
Pires
AF and
Martínez-López
B
(2019). Evaluating the association between climatic events and sheep condemnations in the United States using cluster analysis and spatio-temporal modeling.
Front. Vet. Sci.
Conference Abstract:
GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data.
doi: 10.3389/conf.fvets.2019.05.00071
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Received:
28 Aug 2019;
Published Online:
27 Sep 2019.
*
Correspondence:
Mx. Kathleen C O'Hara, Center for Animal Disease Modeling and Surveillance, School of Veterinary Medicine, University of California, Davis, Davis, California, CA 95616-5270, United States, kcohara@ucdavis.edu
Mx. Beatriz Martínez-López, Center for Animal Disease Modeling and Surveillance, School of Veterinary Medicine, University of California, Davis, Davis, California, CA 95616-5270, United States, beamartinezlopez@ucdavis.edu