CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
MIOvPOPsurveillance is set up to simulate harvest-based chronic wasting disease (CWD) surveillance of white-tailed deer (Odocoileus virginianus) populations in select Michigan Counties. New regions can be readily added, also the model can be readily adapted for other disease systems and used for informed-decision making during planning and implementation stages of disease surveillance in wildlife and free-ranging species.
This model describes the tranmission of HIV by means of unprotected anal intercourse in a population of men-who-have-sex-with-men.
The model is parameterized based on field data from a cohort study conducted in Atlanta Georgia.
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.
The Mission San Diego model is an epidemiological model designed to test hypotheses related to the spread of the 1805-1806 measles epidemic among indigenous residents of Mission San Diego during the early mission period in Alta California. The model community is based on the population of the Mission San Diego community, as listed in the parish documents (baptismal, marriage, and death records). Model agents are placed on a map-like grid that consists of houses, the mission church, a women’s dormitory (monjeria) adjacent to the church, a communal kitchen, priest’s quarters, and agricultural fields. They engage in daily activities that reflect known ethnographic patterns of behavior at the mission. A pathogen is introduced into the community and then it spreads throughout the population as a consequence of individual agent movements and interactions.
The St Anthony flu model is an epidemiological model designed to test hypotheses related to the spread of the 1918 influenza pandemic among residents of a small fishing community in Newfoundland and Labrador. The 1921 census data from Newfoundland and Labrador are used to ensure a realistic model population; the community of St. Anthony, NL, located on the tip of the Northern Peninsula of the island of Newfoundland is the specific population modeled. Model agents are placed on a map-like grid that consists of houses, two churches, a school, an orphanage, a hospital, and several boats. They engage in daily activities that reflect known ethnographic patterns of behavior in St. Anthony and other similar communities. A pathogen is introduced into the community and then it spreads throughout the population as a consequence of individual agent movements and interactions.
Leptospirosis is a neglected, bacterial zoonosis with worldwide distribution, primarily a disease of poverty. More than 200 pathogenic serovars of Leptospira bacteria exist, and a variety of species may act as reservoirs for these serovars. Human infection is the result of direct or indirect contact with Leptospira bacteria in the urine of infected animal hosts, primarily livestock, dogs, and rodents. There is increasing evidence that dogs and dog-adapted serovar Canicola play an important role in the burden of leptospirosis in humans in marginalized urban communities. What is needed is a more thorough understanding of the transmission dynamics of Leptospira in these marginalized urban communities, specifically the relative importance of dogs and rodents in the transmission of Leptospira to humans. This understanding will be vital for identifying meaningful intervention strategies.
One of the main objectives of MHMSLeptoDy is to elucidate transmission dynamics of host-adapted Leptospira strains in multi-host system. The model can also be used to evaluate alternate interventions aimed at reducing human infection risk in small-scale communities like urban slums.
We compare three model estimates for the time and treatment requirements to eliminate HCV among HIV-positive MSM in Victoria, Australia: a compartmental model; an ABM parametrized by surveillance data; and an ABM with a more heterogeneous population.
This is a model of root disease spread between trees in the landscape. The disease spreads via two transmission processes: (a) root contact/root graft transmission between adjacent trees and (b) insect vectors that carry spores between trees. Full details can be found in the “Info” tab in the model and in the readme file in the GitHub repository.
The purpose of the model is to simulate the spatial dynamics of potato late blight to analyse whether resistant varieties can be used effectively for sustainable disease control. The model represents an agricultural landscape with potato fields and data of a Dutch agricultural region is used as input for the model. We simulated potato production, disease spread and pathogen evolution during the growing season (April to September) for 36 years. Since late blight development and crop growth is weather dependent, measured weather data is used as model input. A susceptible and late blight resistant potato variety are distinguished. The resistant variety has a potentially lower yield but cannot get infected with the disease. However, during the growing season virulent spores can emerge as a result of mutations during spore production. This new virulent strain is able to infect the resistant fields, resulting in resistance breakdown. The model shows how disease severity, resistance durability and potato yield are affected by the fraction of fields across a landscape with a disease-resistant potato variety.
The purpose of the presented ABM is to explore how system resilience is affected by external disturbances and internal dynamics by using the stylized model of an agricultural land use system.
We explore land system resilience with a stylized land use model in which agents’ land use activities are affected by external shocks, agent interactions, and endogenous feedbacks. External shocks are designed as yield loss in crops, which is ubiquitous in almost every land use system where perturbations can occur due to e.g. extreme weather conditions or diseases. Agent interactions are designed as the transfer of buffer capacity from farmers who can and are willing to provide help to other farmers within their social network. For endogenous feedbacks, we consider land use as an economic activity which is regulated by markets — an increase in crop production results in lower price (a negative feedback) and an agglomeration of a land use results in lower production costs for the land use type (a positive feedback).