CINCH1 (Covid-19 INfection Control in Hospitals), is a prototype model of physical distancing for infection control among staff in University College London Hospital during the Covid-19 pandemic, developed at the University of Leeds, School of Geography. It models the movement of collections of agents in simple spaces under conflicting motivations of reaching their destination, maintaining physical distance from each other, and walking together with a companion. The model incorporates aspects of the Capability, Opportunity and Motivation of Behaviour (COM-B) Behaviour Change Framework developed at University College London Centre for Behaviour Change, and is aimed at informing decisions about behavioural interventions in hospital and other workplace settings during this and possible future outbreaks of highly contagious diseases. CINCH1 was developed as part of the SAFER (SARS-CoV-2 Acquisition in Frontline Health Care Workers – Evaluation to Inform Response) project
(https://www.ucl.ac.uk/behaviour-change/research/safer-sars-cov-2-acquisition-frontline-health-care-workers-evaluation-inform-response), funded by the UK Medical Research Council. It is written in Python 3.8, and built upon Mesa version 0.8.7 (copyright 2020 Project Mesa Team).

The model measures drivers of effectiveness of risk assessments in risk workshops regarding the correctness and required time. Specifically, we model the limits to information transfer, incomplete discussions, group characteristics, and interaction patterns and investigate their effect on risk assessment in risk workshops.

The model simulates a discussion in the context of a risk workshop with 9 participants. The participants use Bayesian networks to assess a given risk individually and as a group.

The HUMan impact on LANDscapes (HUMLAND) model has been developed to track and quantify the intensity of different impacts on landscapes at the continental level. This agent-based model focuses on determining the most influential factors in the transformation of interglacial vegetation with a specific emphasis on burning organized by hunter-gatherers. HUMLAND integrates various spatial datasets as input and target for the agent-based model results. Additionally, the simulation incorporates recently obtained continental-scale estimations of fire return intervals and the speed of vegetation regrowth. The obtained results include maps of possible scenarios of modified landscapes in the past and quantification of the impact of each agent, including climate, humans, megafauna, and natural fires.

An agent-based model simulating West Nile Virus dynamics in a one host (American robin)-one vector (Culex spp. mosquito) system. ODD improved and code cleaned.

A generalized organizational agent- based model (ABM) containing both formal organizational hierarchy and informal social networks simulates organizational processes that occur over both formal network ties and informal networks.

This model is based on the Narragansett Bay, RI recreational fishery. The two types of agents are piscivorous fish and fishers (shore and boat fishers are separate “breeds”). Each time step represents one week. Open season is weeks 1-26, assuming fishing occurs during half the year. At each weekly time step, fish agents grow, reproduce, and die. Fisher agents decide whether or not to fish based on their current satisfaction level, and those that do go fishing attempt to catch a fish. If they are successful, they decide whether to keep or release the fish. In our publication, this model was linked to an Ecopath with Ecosim food web model where the commercial harvest of forage fish affected the biomass of piscivorous fish - which then became the starting number of piscivorous fish for this ABM. The number of fish caught in a season of this ABM was converted to a fishing pressure and input back into the food web model.

This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.

CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

a computer-based role-playing game simulating the interactions between farming activities, livestock herding and wildlife in a virtual landscape reproducing local socioecological dynamics at the periphery of Hwange National Park (Zimbabwe).

The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.