scholarly journals A Comparison of Economic Agent-Based Model Calibration Methods

2019 ◽  
Author(s):  
Donovan Platt
Keyword(s):  
Model Calibration ◽  
Economic Agent ◽  
Agent Based Model ◽  
Agent Based ◽  
Calibration Methods

scholarly journals Optimization of Manufacturers Behaviour On the Basis of a Local Economic Agent-Based Model Implementation

2018 ◽  
Vol 51 (32) ◽  
pp. 115-120 ◽  
Author(s):  
Olga M. Zvereva ◽  
Dmitry B. Berg ◽  
Georgy K. Shevchuk ◽  
K.B. Spasov
Keyword(s):  
Economic Agent ◽  
Agent Based Model ◽  
Agent Based

Coral reefs optimization algorithms for agent-based model calibration

2021 ◽  
Vol 100 ◽  
pp. 104170
Author(s):  
Ignacio Moya ◽  
Enrique Bermejo ◽  
Manuel Chica ◽  
Óscar Cordón
Keyword(s):  
Coral Reefs ◽  
Model Calibration ◽  
Optimization Algorithms ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Susceptibility of zero community transmission regimes to new variants of SARS-CoV-2: a modelling study of Queensland

2021 ◽  
Author(s):  
Paula Sanz-Leon ◽  
Nathan J Stevenson ◽  
Robyn Margaret Stuart ◽  
Romesh G Abeysuriya ◽  
James C Pang ◽  
...  
Keyword(s):  
Simulation Study ◽  
Model Calibration ◽  
The State ◽  
Wave Period ◽  
Agent Based Model ◽  
Agent Based ◽  
High Transmission ◽  
Transmission Setting ◽  
Threefold Increase ◽  
Community Transmission

Objectives: To assess the risk of sustained community transmission of SARS-CoV-2/COVID-19 in Queensland (Australia) in the presence of high-transmission variants of the virus. Design: We used an agent-based model Covasim and the demographics, policies, and interventions implemented in the state. Using the calibrated model, we simulated possible epidemic trajectories that could eventuate due to leakage of infected cases with high-transmission variants, during a period of zero community transmission. Setting: Model calibration covered the first-wave period from early March 2020 to May 2020. Predicted epidemic trajectories were simulated from early February 2021 to late March 2021. Participants: None (simulation study). Main outcomes: A calibrated model of COVID-19 epidemiology in Queensland; the conditions that could lead to an outbreak; and how likely that situation is to occur. Results: Simulations showed that one infected agent with the ancestral (A.2.2) variant has a 14% chance of crossing a threshold of sustained community transmission (i.e., > 5 infections per day, more than 3 days in a row), assuming no change in the prevailing preventative and counteracting policies. However, one agent carrying a more infectious variant (e.g., B.1.1.7) has a 43% chance of crossing the same threshold; a threefold increase. Doubling the average number of daily tests results in a decrease of this probability from 43% to 23%. Conclusions: The introduction of even a small number of people infected with high-transmission variants dramatically increases the probability of sustained community transmission in Queensland.

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