AMTraC-19 Source Code: Agent-based Model of Transmission and Control of the COVID-19 pandemic in Australia

The software implements an agent-based model for a fine-grained computational simulation of the COVID-19 pandemic in Australia. This model is calibrated to reproduce several features of COVID-19 transmission, including its age-dependent epidemiological characteristics. The individual-based epidemiological model accounts for mobility (worker and student commuting) patterns and human interactions derived from the Australian census and other national data sources. The high-precision simulation comprises approximately 25 million stochastically generated software agents and traces various scenarios of the COVID-19 pandemic in Australia. The software has been used to evaluate various intervention strategies, including (1) non-pharmaceutical interventions, such as restrictions on international air travel, case isolation, home quarantine, school closures, and stay-at-home restrictions with varying levels of compliance (i.e., "social distancing"), and (2) pharmaceutical interventions, such as pre-pandemic vaccination phase and progressive vaccination rollout.

1. The paper describing the opinion dynamics model and the scenarios investigated with AMTRaC-19 (v9.0):

S. L. Chang, Q. D. Nguyen, C. J. E. Suster, C. M. Jamerlan, R. J. Rockett, V. Sintchenko, T. C. Sorrell, A. Martiniuk, M. Prokopenko, Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure, in submission, 2024; arXiv: https://arxiv.org/pdf/2408.00011

Please cite it, as well as other publications referenced below, when using the software.

2. The paper describing the model and the scenarios investigated with AMTRaC-19 (v8.0):

Q. D. Nguyen, S. L. Chang, C. M. Jamerlan, M. Prokopenko, Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions, Population Health Metrics, 21, 17, 2023.

Please cite it, as well as other publications referenced below, when using the software.

The dataset generated during the systematic comparison is also available on Zenodo:

AMTraC-19 (v8.0) Dataset: Systematic Comparison of the COVID-19 Pandemic Scenarios, https://doi.org/10.5281/zenodo.8067859

3. The paper describing modelling of the Omicron variant and the scenarios investigated with AMTRaC-19 (v7_9):

S. L. Chang, Q. D. Nguyen, A. Martiniuk, V. Sintchenko, T. C. Sorrell, M. Prokopenko, Persistence of the Omicron variant of SARS-CoV-2 in Australia: The impact of fluctuating social distancing, PLOS Global Public Health, 3(4): e0001427, 2023.

The dataset generated during the study of the Omicron variant is also available on Zenodo:

S. L. Chang, Q. D. Nguyen & M. Prokopenko. (2022). AMTraC-19 (v7.9) Dataset: Persistence of the Omicron variant of SARS-CoV-2 in Australia, https://doi.org/10.5281/zenodo.7325756

4. The paper describing the previous model (Delta variant) and the scenarios investigated with AMTRaC-19 (v7_7d):

S. L. Chang, C. Zachreson, O. M. Cliff, M. Prokopenko, Simulating transmission scenarios of the Delta variant of SARS-CoV-2 in Australia, Frontiers in Public Health, 10, 10.3389/fpubh.2022.823043, 2022.

The dataset generated during the study of the Delta variant is also available on Zenodo:

S. L. Chang, O. M. Cliff, C. Zachreson & M. Prokopenko. (2021). AMTraC-19 (v7.7d) Dataset: Simulating transmission scenarios of the Delta variant of SARS-CoV-2 in Australia (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5726241