Exploring Synthetic Mass Action Models

Maler, Oded; Halász, Ádám; Lebeltel, Olivier; Maler, Ouri

doi:10.1007/978-3-319-27656-4_6

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…The choice of geometry presupposes that agents move across a common landscape at all times, and no agents enter or leave it. This simplification of the geographical landscape, while in general unrealistic, is not uncommon [93, 9] and provides two advantages: a) it naturally matches intuitions behind interactive particle systems driven by mass action principles [75] such as in the SIR model and b) when translated into code, no boundary checks need to be performed by the agents. Lattice sites are connected, from the perspective of an agent, by a Moore neighborhood in an effort to reduce the effect of discretization artifacts [64].…”

Section: Building a Multi-objective Model For Covid-19: The Agent-basmentioning

confidence: 99%

The Epidemiology Workbench: a Tool for Communities to Strategize in Response to COVID-19 and other Infectious Diseases

Núñez-Corrales

Jakobsson

2020

Preprint

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COVID-19 poses a dramatic challenge to health, community life, and the economy of communities across the world. While the properties of the virus are similar from place to place, the impact has been dramatically different from place to place, due to such factors as population density, mobility, age distribution, etc. Thus, optimum testing and social distancing strategies may also be different from place to place. The Epidemiology Workbench provides access to an agent-based model in which demographic, geographic, and public health information a community together with a social distancing and testing strategy may be input, and a range of possible outcomes computed, to inform local authorities on coping strategies. The model is adaptable to other infectious diseases, and to other strains of coronavirus. The tool is illustrated by scenarios for the cities of Urbana and Champaign, Illinois, the home of the University of Illinois at Urbana-Champaign. Our calculations suggest that massive testing is the most effective strategy to combat the likely increase in local cases due to mass ingress of a student population carrying a higher viral load than that currently present in the community.

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Section: Building a Multi-objective Model For Covid-19: The Agent-basmentioning

confidence: 99%