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This archive contains the SAFE-ABM computational model developed to evaluate targeted intervention strategies for protecting essential workers during epidemic conditions, accompanying the published article “Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Uncertainty Quantification” in the Journal of Artificial Societies and Social Simulation, 29(4), Article 7 (2026). https://doi.org/10.18564/jasss.6276. SAFE-ABM is an agent-based model that simulates disease transmission through structured interactions across households, workplaces, and schools, while incorporating stochastic disease progression and uncertainty in transmission, recovery, and mortality parameters.
The model evaluates five intervention scenarios: Scenario 1, no restrictions; Scenario 2, school-from-home; Scenario 3, essential-workers-only movement; Scenario 4, rotational shifts among essential workers with quarantine of symptomatic active workers; and Scenario 5, rotational shifts among essential workers without quarantine. The archive includes scenario-specific simulation scripts, comparison-analysis scripts, saved derived outputs, README documentation, software requirements, and reproducibility notes.
The included comparison scripts reproduce the main numerical summaries and manuscript outputs, including median epidemic trajectories, predictive-uncertainty plots, cumulative recovery and death summaries, inflection-point summaries, Welch-test comparisons, and mutual-information sensitivity rankings. Saved derived outputs are included so that the main figures and tables can be reproduced without rerunning all large-scale simulations.
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LUXE is a land-use change model featuring different levels of land market implementation. It integrates utility measures, budget constraints, competitive bidding, and market interactions to model land-use change in exurban environment.
This is a gender differentiation model in terms of reputations, prestige and self-esteem (presented in the paper https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236840). The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) considering two groups.
This agent-based model studies how inequalities can be explained by the difference of open-mindness between two groups of interacting agents. We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters. We study an heterogeneous population of two different groups: one more open to influence of others, taking less into account their perceived difference of esteem, called L; a second one less prone to it, called S, who designed the credibility they give to others strongly based on how higher or lower valued than themselves they perceive them.
We show that a mixed population always turns in favor to some agents belonging to the group of less open-minded agents S, and harms the other group: (1) the average group self-opinion or reputation of S is always better than the one of L; (2) the higher rank in terms of reputation are more frequently occupied by the S agents while the L agents occupy more the bottom rank; (3) the properties of the dynamics of differentiation between the two groups are similar to the properties of the glass ceiling effect proposed by Cotter et al (2001).
Our model is hybrid agent-based and equation based model for human air-borne infectious diseases measles. It follows an SEIR (susceptible, exposed,infected, and recovered) type compartmental model with the agents moving be-tween the four state relating to infectiousness. However, the disease model canswitch back and forth between agent-based and equation based depending onthe number of infected agents. Our society model is specific using the datato create a realistic synthetic population for a county in Ireland. The modelincludes transportation with agents moving between their current location anddesired destination using predetermined destinations or destinations selectedusing a gravity model.
FoxNet is an individual-based modelling framework that can be customised to generate high-resolution red fox Vulpes vulpes population models for both northern and southern hemispheres. FoxNet predicts red fox population dynamics, including responses to control and landscape productivity. Model landscapes (up to ~15,000 km^2 and bait layouts can be generated within FoxNet or imported as GIS layers.
If you use FoxNet, please cite:
Hradsky BA, Kelly L, Robley A, Wintle BA (in review). FoxNet: an individual-based modelling framework to support red fox management. Journal of Applied Ecology.
This is a relatively simple foraging-radius model, as described first by Robert Kelly, that allows one to quantify the effect of increased logistical mobility (as represented by increased effective foraging radius, r_e) on the likelihood that 2 randomly placed central place foragers will encounter one another within 5000 time steps.
This model implements a bidirectional coupling between micro-level agent decisions and macro-level system dynamics, with an additional diagnostic layer based on Stafford Beer’s Viable System Model.
Key features:
- Six types of agents (Household, Firm, Bank, Government, Foreign, Innovation)
- Continuous SDM core integrated with Runge-Kutta 4
- Robust GDELT data handling with multi-level fallback
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Industrial location theory has not emphasized environmental concerns, and research on industrial symbiosis has not emphasized workforce housing concerns. This article brings jobs, housing, and environmental considerations together in an agent-based model of industrial
and household location. It shows that four classic outcomes emerge from the interplay of a relatively small number of explanatory factors: the isolated enterprise with commuters; the company town; the economic agglomeration; and the balanced city.
The model is a combination of a spatially explicit, stochastic, agent-based model for wild boars (Sus scrofa L.) and an epidemiological model for the Classical Swine Fever (CSF) virus infecting the wild boars.
The original model (Kramer-Schadt et al. 2009) was used to assess intrinsic (system immanent host-pathogen interaction and host life-history) and extrinsic (spatial extent and density) factors contributing to the long-term persistence of the disease and has further been used to assess the effects of intrinsic dynamics (Lange et al. 2012a) and indirect transmission (Lange et al. 2016) on the disease course. In an applied context, the model was used to test the efficiency of spatiotemporal vaccination regimes (Lange et al. 2012b) as well as the risk of disease spread in the country of Denmark (Alban et al. 2005).
References: See ODD model description.
We propose an agent-based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the bargaining model by Axtell, Epstein and Young.
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