A spatially explicit, agent-based model for simulating movements of cattle grazing corn residues

2016 ◽  
Keyword(s):  
Cattle Grazing ◽  
Spatially Explicit ◽  
Agent Based Model ◽  
Agent Based ◽  
Corn Residues

scholarly journals An agent-based model of cattle grazing toxic Geyer's larkspur

PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0194450 ◽  
Author(s):  
Kevin E. Jablonski ◽  
Randall B. Boone ◽  
Paul J. Meiman
Keyword(s):  
Cattle Grazing ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Understanding transmission and control of the pork tapeworm with CystiAgent: a spatially explicit agent-based model

2020 ◽  
Author(s):  
Ian Wright Pray ◽  
Wayne Wakeland ◽  
William Pan ◽  
William E. Lambert ◽  
Hector H. Garcia ◽  
...  
Keyword(s):  
Taenia Solium ◽  
Model Performance ◽  
Rank Correlation ◽  
Public Health Problem ◽  
Sensitivity Analyses ◽  
Transmission Model ◽  
Spatially Explicit ◽  
Model Parameters ◽  
Agent Based Model ◽  
Agent Based

Abstract Background The pork tapeworm ( Taenia solium ) is a serious public health problem in rural low-resource areas of Latin America, Africa, and Asia, where the associated conditions of nuerocysticercosis (NCC) and porcine cysticercosis cause substantial health and economic harms. An accurate and validated transmission model for T. solium would serve as an important new tool for control and elimination, as it would allow for comparison of available intervention strategies, and prioritization of the most effective strategies for control and elimination efforts. Methods We developed a spatially-explicit agent-based model (ABM) for T. solium (“CystiAgent”) that differs from prior T. solium models by including a spatial framework and behavioral parameters such as pig roaming, open human defecation, and human travel. In this article, we introduce the structure and function of the model, describe the data sources used to parameterize the model, and apply sensitivity analyses (Latin hypercube sampling–partial rank correlation coefficient (LHS-PRCC)) to evaluate model parameters. Results LHS-PRCC analysis of CystiAgent found that the parameters with the greatest impact on model uncertainty were the roaming range of pigs, the infectious duration of human taeniasis, use of latrines, and the set of “tuning” parameters defining the probabilities of infection in humans and pigs given exposure to T. solium. Conclusions CystiAgent is a novel ABM that has the ability to model spatial and behavioral features of T. solium transmission not available in other models. There is a small set of impactful model parameters that contribute uncertainty to the model and may impact the accuracy of model projections. Field and laboratory studies to better understand these key components of transmission may help reduce uncertainty, while current applications of CystiAgent may consider calibration of these parameters to improve model performance. These results will ultimately allow for improved interpretation of model validation results, and usage of the model to compare available control and elimination strategies for T. solium .

How accurate are estimates of flower visitation rates by pollinators? Lessons from a spatially explicit agent-based model

2020 ◽  
Vol 57 ◽  
pp. 101077
Author(s):  
Mário Santos ◽  
Reinaldo Cajaiba ◽  
Darinka Gonzalez ◽  
Pedro Leote ◽  
Daniel Ferreira ◽  
...  
Keyword(s):  
Spatially Explicit ◽  
Agent Based Model ◽  
Agent Based ◽  
Flower Visitation ◽  
Visitation Rates

A spatially explicit agent-based model of the interactions between jaguar populations and their habitats

2015 ◽  
Vol 306 ◽  
pp. 268-277 ◽  
Author(s):  
A. Watkins ◽  
J. Noble ◽  
R.J. Foster ◽  
B.J. Harmsen ◽  
C.P. Doncaster
Keyword(s):  
Spatially Explicit ◽  
Agent Based Model ◽  
Agent Based
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