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Temporal-spatial heterogeneity in animal-environment contact: implications for the exposure and transmission of pathogens.

Chen S, Sanderson MW, White BJ, Amrine DE, Lanzas C - Sci Rep (2013)

Bottom Line: The generated contact structure varied across days and among animals.The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment.Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, Knoxville, TN 37996 (USA).

ABSTRACT
Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

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Related in: MedlinePlus

Time series of mean prevalence under different conditions.Solid black line: mean prevalence; dashed red line: 25% and 75% quantiles. Four figures represent condition C1, C2, C3, and H1. Details of these conditions are listed in table 3.
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f2: Time series of mean prevalence under different conditions.Solid black line: mean prevalence; dashed red line: 25% and 75% quantiles. Four figures represent condition C1, C2, C3, and H1. Details of these conditions are listed in table 3.

Mentions: In Figure 2, we showed the time series of prevalence obtained by simulating the agent-based model for different conditions (C1 to C3 as heterogeneous conditions, and H1 as homogeneous condition) and summarized the predicted maximum prevalence and its corresponding occurrence day in Table 2. The overall shapes of prevalence dynamics under these conditions were similar; however, peak prevalence differed substantially (Table 3). Condition C2 and C3 represent different potential mitigation approaches. C2 focused on the high concentration area (water) with reduced bacteria concentration only in the water source, while C3 further reduced bacteria concentration in the grain bunk and hay bunk, as well. In C2, we reduced the maximum prevalence by approximately 6%. In C3, a further reduction to 1/10 of the bacteria concentration for the grain bunk and hay bunk (with already lowered bacteria concentration in water as C2) resulted in about a 12.7% reduction of prevalence. Finally, if we lower the bacteria concentration in water to 104 CFU/m2 (which is a homogeneous pen with 104 CFU/m2 bacteria concentration everywhere), we would have less than 70% maximum prevalence. All these conditions (C2, C3, and H1) focus only on controlling bacterial concentration in the water, grain bunk, and hay bunk, and the results show that targeting these specific areas can be useful to control bacteria colonization and infection in the pen.


Temporal-spatial heterogeneity in animal-environment contact: implications for the exposure and transmission of pathogens.

Chen S, Sanderson MW, White BJ, Amrine DE, Lanzas C - Sci Rep (2013)

Time series of mean prevalence under different conditions.Solid black line: mean prevalence; dashed red line: 25% and 75% quantiles. Four figures represent condition C1, C2, C3, and H1. Details of these conditions are listed in table 3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814814&req=5

f2: Time series of mean prevalence under different conditions.Solid black line: mean prevalence; dashed red line: 25% and 75% quantiles. Four figures represent condition C1, C2, C3, and H1. Details of these conditions are listed in table 3.
Mentions: In Figure 2, we showed the time series of prevalence obtained by simulating the agent-based model for different conditions (C1 to C3 as heterogeneous conditions, and H1 as homogeneous condition) and summarized the predicted maximum prevalence and its corresponding occurrence day in Table 2. The overall shapes of prevalence dynamics under these conditions were similar; however, peak prevalence differed substantially (Table 3). Condition C2 and C3 represent different potential mitigation approaches. C2 focused on the high concentration area (water) with reduced bacteria concentration only in the water source, while C3 further reduced bacteria concentration in the grain bunk and hay bunk, as well. In C2, we reduced the maximum prevalence by approximately 6%. In C3, a further reduction to 1/10 of the bacteria concentration for the grain bunk and hay bunk (with already lowered bacteria concentration in water as C2) resulted in about a 12.7% reduction of prevalence. Finally, if we lower the bacteria concentration in water to 104 CFU/m2 (which is a homogeneous pen with 104 CFU/m2 bacteria concentration everywhere), we would have less than 70% maximum prevalence. All these conditions (C2, C3, and H1) focus only on controlling bacterial concentration in the water, grain bunk, and hay bunk, and the results show that targeting these specific areas can be useful to control bacteria colonization and infection in the pen.

Bottom Line: The generated contact structure varied across days and among animals.The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment.Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, Knoxville, TN 37996 (USA).

ABSTRACT
Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

Show MeSH
Related in: MedlinePlus