Agent-Based Computational Epidemiological Modeling

The development of computational sciences has fostered major advances in life sciences, but also led to reproducibility and reliability issues, which become a crucial stake when simulations are aimed at assessing control measures, as in epidemiology. A broad use of software development methods is a useful remediation to reduce those problems, but preventive approaches, targeting not only implementation but also model design, are essential to sustainable enhancements. Among them, AI techniques, based on the separation between declarative and procedural concerns, and on knowledge engineering, offer promising solutions. Especially, multilevel multi-agent systems, deeply rooted in that culture, provide a generic way to integrate several epidemiological modeling paradigms within a homogeneous interface. We explain in this paper how this approach is used for building more generic, reliable and sustainable simulations, illustrated by real-case applications in cattle epidemiology.

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A Systematic Approach for Aligning ODE and Agent-Based Models: Application to Epidemiological Modeling

Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B ◽

10.1115/detc2008-49291 ◽

2008 ◽

Author(s):

Michael J. Leamy

Keyword(s):

Autonomous Agents ◽

Systematic Approach ◽

Agent Based Modeling ◽

Agent Based Models ◽

Ode Model ◽

Epidemiological Modeling ◽

Agent Based ◽

Agent Behavior ◽

Time Histories ◽

Good Agreement

Recent researchers active in the field of agent-based modeling have called for the alignment, or ‘docking,’ of models which simulate the same system using different techniques. Addressing this need, the present article details a systematic approach for docking models described by (nonlinear) ordinary differential equations with analogous models employing autonomous agents — i.e., agent-based models (ABMs). In particular, the approach is demonstrated by example for an epidemiological SEIR (Susceptible, Exposed, Infectious, Recovered) ODE model with a newly-developed agent-based model. The ABM is designed such that the assumptions present in the ODE model are matched by the actions of the ABM agents and the model. In addition, less-than-transparent coefficients present in the ODE model are examined via difference equations and then mapped to appropriate agent behavior. The result is very good agreement in comparisons made between ODE and ABM model-generated time-histories — i.e., successful alignment. It is anticipated that the systematic alignment approach described herein should be useful for aligning ODE and ABM models in other fields of study — e.g., Lanchester ODE combat models vice ABM combat models.

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Impact of mobility restriction in COVID-19 superspreading events using agent-based model

PLoS ONE ◽

10.1371/journal.pone.0248708 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248708

Author(s):

L. L. Lima ◽

A. P. F. Atman

Keyword(s):

A Priori ◽

Epidemiological Studies ◽

Health Concern ◽

Agent Based Model ◽

Epidemiological Modeling ◽

Network Nodes ◽

Agent Based ◽

Interesting Approach ◽

The Impact

COVID-19 pandemic is an immediate major public health concern. The search for the understanding of the disease spreading made scientists around the world turn their attention to epidemiological studies. An interesting approach in epidemiological modeling nowadays is to use agent-based models, which allow to consider a heterogeneous population and to evaluate the role of superspreaders in this population. In this work, we implemented an agent-based model using probabilistic cellular automata to simulate SIR (Susceptible-Infected-Recovered) dynamics using COVID-19 infection parameters. Differently to the usual studies, we did not define the superspreaders individuals a priori, we only left the agents to execute a random walk along the sites. When two or more agents share the same site, there is a probability to spread the infection if one of them is infected. To evaluate the spreading, we built the transmission network and measured the degree distribution, betweenness, and closeness centrality. The results displayed for different levels of mobility restriction show that the degree reduces as the mobility reduces, but there is an increase of betweenness and closeness for some network nodes. We identified the superspreaders at the end of the simulation, showing the emerging behavior of the model since these individuals were not initially defined. Simulations also showed that the superspreaders are responsible for most of the infection propagation and the impact of personal protective equipment in the spreading of the infection. We believe that this study can bring important insights for the analysis of the disease dynamics and the role of superspreaders, contributing to the understanding of how to manage mobility during a highly infectious pandemic as COVID-19.

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Total etch dentin bonding systems: scanning electron microscopy of the resin-dentin hybrid layer

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100130092 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1092-1093

Author(s):

Jorge Perdigao

Keyword(s):

Composite Resin ◽

Mechanical Interlocking ◽

Hybrid Layer ◽

Agent Based ◽

Dentin Bonding ◽

Acid Agent ◽

Bond Strengths ◽

Main Component ◽

Bonding Systems ◽

New Generation

In 1955, Buonocore introduced the etching of enamel with phosphoric acid. Bonding to enamel was created by mechanical interlocking of resin tags with enamel prisms. Enamel is an inert tissue whose main component is hydroxyapatite (98% by weight). Conversely, dentin is a wet living tissue crossed by tubules containing cellular extensions of the dental pulp. Dentin consists of 18% of organic material, primarily collagen. Several generations of dentin bonding systems (DBS) have been studied in the last 20 years. The dentin bond strengths associated with these DBS have been constantly lower than the enamel bond strengths. Recently, a new generation of DBS has been described. They are applied in three steps: an acid agent on enamel and dentin (total etch technique), two mixed primers and a bonding agent based on a methacrylate resin. They are supposed to bond composite resin to wet dentin through dentin organic component, forming a peculiar blended structure that is part tooth and part resin: the hybrid layer.

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