scholarly journals An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment

2020 ◽  
Vol 270 ◽  
pp. 110905 ◽  
Author(s):  
Aaron J. Neill ◽  
Doerthe Tetzlaff ◽  
Norval J.C. Strachan ◽  
Rupert L. Hough ◽  
Lisa M. Avery ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Indicator Organisms ◽  
Agent Based Model ◽  
Agent Based ◽  
Spatio Temporal ◽  
Transfer Mechanisms

scholarly journals Temporal dynamics of viral load and false negative rate influence the levels of testing necessary to combat COVID-19 spread

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Katherine F. Jarvis ◽  
Joshua B. Kelley
Keyword(s):  
Viral Load ◽  
Temporal Dynamics ◽  
Reproduction Number ◽  
False Negative ◽  
False Negative Rate ◽  
Agent Based Model ◽  
Agent Based ◽  
Viral Spread ◽  
Negative Rate

AbstractColleges and other organizations are considering testing plans to return to operation as the COVID-19 pandemic continues. Pre-symptomatic spread and high false negative rates for testing may make it difficult to stop viral spread. Here, we develop a stochastic agent-based model of COVID-19 in a university sized population, considering the dynamics of both viral load and false negative rate of tests on the ability of testing to combat viral spread. Reported dynamics of SARS-CoV-2 can lead to an apparent false negative rate from ~ 17 to ~ 48%. Nonuniform distributions of viral load and false negative rate lead to higher requirements for frequency and fraction of population tested in order to bring the apparent Reproduction number (Rt) below 1. Thus, it is important to consider non-uniform dynamics of viral spread and false negative rate in order to model effective testing plans.

scholarly journals Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model

2021 ◽  
Vol 10 (2) ◽  
pp. 88
Author(s):  
Dana Kaziyeva ◽  
Martin Loidl ◽  
Gudrun Wallentin
Keyword(s):  
Regional Scale ◽  
Evidence Base ◽  
Wide Field ◽  
Traffic Patterns ◽  
Agent Based Model ◽  
Validation Data ◽  
Agent Based ◽  
Mobility Behavior ◽  
Spatio Temporal ◽  
Models Validation

Transport planning strategies regard cycling promotion as a suitable means for tackling problems connected with motorized traffic such as limited space, congestion, and pollution. However, the evidence base for optimizing cycling promotion is weak in most cases, and information on bicycle patterns at a sufficient resolution is largely lacking. In this paper, we propose agent-based modeling to simulate bicycle traffic flows at a regional scale level for an entire day. The feasibility of the model is demonstrated in a use case in the Salzburg region, Austria. The simulation results in distinct spatio-temporal bicycle traffic patterns at high spatial (road segments) and temporal (minute) resolution. Scenario analysis positively assesses the model’s level of complexity, where the demographically parametrized behavior of cyclists outperforms stochastic null models. Validation with reference data from three sources shows a high correlation between simulated and observed bicycle traffic, where the predictive power is primarily related to the quality of the input and validation data. In conclusion, the implemented agent-based model successfully simulates bicycle patterns of 186,000 inhabitants within a reasonable time. This spatially explicit approach of modeling individual mobility behavior opens new opportunities for evidence-based planning and decision making in the wide field of cycling promotion

scholarly journals A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

Systems ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 53 ◽  
Author(s):  
Jumadi ◽  
Steve Carver ◽  
Duncan Quincey
Keyword(s):  
Conceptual Design ◽  
Agent Based Model ◽  
Agent Based ◽  
Spatio Temporal

scholarly journals Coalescent models for developmental biology and the spatio-temporal dynamics of growing tissues

2016 ◽  
Vol 13 (117) ◽  
pp. 20160112 ◽  
Author(s):  
Patrick Smadbeck ◽  
Michael P. H. Stumpf
Keyword(s):  
Developmental Biology ◽  
Large Scale ◽  
Cell Tracking ◽  
Temporal Dynamics ◽  
Growth Models ◽  
Lineage Tracing ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Spatio Temporal ◽  
Large Scale Simulations

Development is a process that needs to be tightly coordinated in both space and time. Cell tracking and lineage tracing have become important experimental techniques in developmental biology and allow us to map the fate of cells and their progeny. A generic feature of developing and homeostatic tissues that these analyses have revealed is that relatively few cells give rise to the bulk of the cells in a tissue; the lineages of most cells come to an end quickly. Computational and theoretical biologists/physicists have, in response, developed a range of modelling approaches, most notably agent-based modelling. These models seem to capture features observed in experiments, but can also become computationally expensive. Here, we develop complementary genealogical models of tissue development that trace the ancestry of cells in a tissue back to their most recent common ancestors. We show that with both bounded and unbounded growth simple, but universal scaling relationships allow us to connect coalescent theory with the fractal growth models extensively used in developmental biology. Using our genealogical perspective, it is possible to study bulk statistical properties of the processes that give rise to tissues of cells, without the need for large-scale simulations.

scholarly journals Integrating human behavior and snake ecology with agent-based models to predict snakebite in high risk landscapes

2021 ◽  
Vol 15 (1) ◽  
pp. e0009047
Author(s):  
Eyal Goldstein ◽  
Joseph J. Erinjery ◽  
Gerardo Martin ◽  
Anuradhani Kasturiratne ◽  
Dileepa Senajith Ediriweera ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Ecological Factors ◽  
Epidemiological Studies ◽  
Decision Makers ◽  
Agent Based ◽  
Snake Species ◽  
Relative Contribution ◽  
As Species ◽  
Spatio Temporal ◽  
The Tropics

Snakebite causes more than 1.8 million envenoming cases annually and is a major cause of death in the tropics especially for poor farmers. While both social and ecological factors influence the chance encounter between snakes and people, the spatio-temporal processes underlying snakebites remain poorly explored. Previous research has focused on statistical correlates between snakebites and ecological, sociological, or environmental factors, but the human and snake behavioral patterns that drive the spatio-temporal process have not yet been integrated into a single model. Here we use a bottom-up simulation approach using agent-based modelling (ABM) parameterized with datasets from Sri Lanka, a snakebite hotspot, to characterise the mechanisms of snakebite and identify risk factors. Spatio-temporal dynamics of snakebite risks are examined through the model incorporating six snake species and three farmer types (rice, tea, and rubber). We find that snakebites are mainly climatically driven, but the risks also depend on farmer types due to working schedules as well as species present in landscapes. Snake species are differentiated by both distribution and by habitat preference, and farmers are differentiated by working patterns that are climatically driven, and the combination of these factors leads to unique encounter rates for different landcover types as well as locations. Validation using epidemiological studies demonstrated that our model can explain observed patterns, including temporal patterns of snakebite incidence, and relative contribution of bites by each snake species. Our predictions can be used to generate hypotheses and inform future studies and decision makers. Additionally, our model is transferable to other locations with high snakebite burden as well.

A Knowledge Driven Agent-Based Semantic Model for Epidemic Surveillance

2015 ◽  
Vol 09 (04) ◽  
pp. 433-457 ◽  
Author(s):  
Madiha Sahar ◽  
Nadra Guizani ◽  
Saleh M. Basalamah ◽  
Muhammad N. Ayyaz ◽  
Maaz Ahmad ◽  
...  
Keyword(s):  
Semantic Analysis ◽  
Temporal Dynamics ◽  
Probabilistic Approach ◽  
Disease Spread ◽  
Semantic Model ◽  
Population Demographics ◽  
Agent Based ◽  
Spread Model ◽  
Spatio Temporal ◽  
Population Interaction

In this paper we propose a probabilistic approach to synthesize an agent-based heterogeneous semantic model depicting population interaction and analyzing the spatio-temporal dynamics of an airborne epidemic, such as influenza, in a metropolitan area. The methodology is generic in nature and can generate a baseline population for cities for which detailed population summary tables are not available. The joint probabilities of population demographics are estimated using the International Public Use Microsimulation Data (IPUMS) sample set. Agents are assigned various activities based on several characteristics. The agent-based model for the city of Lahore, Pakistan is synthesized and a rule based disease spread model of influenza is simulated. The simulation results are visualized to produce semantic analysis for the spatio-temporal dynamics of the epidemic. The results show that the proposed model can be used by officials and medical experts to simulate an outbreak.

scholarly journals An Agent-Based Evaluation of Varying Evacuation Scenarios in Merapi: Simultaneous and Staged

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 317
Author(s):  
Jumadi Jumadi ◽  
Steve J. Carver ◽  
Duncan J. Quincey
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Relative Effectiveness ◽  
Regional Scale ◽  
Traffic Density ◽  
Peak Time ◽  
Agent Based Model ◽  
Merapi Volcano ◽  
Agent Based ◽  
Spatio Temporal

Mass evacuation should be conducted when a disaster threatens within a regional scale. It is reported that 400,000 people were evacuated during the last eruption of Merapi Volcano in 2010. Such a large-scale evacuation can lead to chaos or congestion, unless well managed. Staged evacuation has been investigated as a solution to reducing the degree of chaos during evacuation processes. However, there is a limited conception of how the stages should be ordered in terms of which group should move first and which group should follow. This paper proposes to develop evacuation stage ordering based on the geographical character of the people at risk and examine the ordering scenarios through an agent-based model of evacuation. We use several geographical features, such as proximity to the hazard, road network conditions (accessibility), size of the population, and demographics as the parameters for ranking the order of each population unit in GIS. From this concept, we produced several scenarios of ranking based on different weightings of the parameters. We applied the scenarios in an agent-based model of volcanic evacuation experiment to observe the results. Afterwards, the results were evaluated based on the ability to reduce the risk and spatio-temporal traffic density along road networks compared to the result of simultaneous evacuation to establish the relative effectiveness of the outcome. The result shows that the staged scenario has a better ability to reduce the potential traffic congestion during the peak time of the evacuation compared to the simultaneous strategy. However, the simultaneous strategy has better performance regarding the speed of reducing the risk. An evaluation of the relative performance of the four varying staged scenarios is also presented and discussed in this paper.

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