Cameron Zachreson
Biographic Data
| ID | 7741805 |
|---|---|
| NAME | Cameron Zachreson |
| GIVEN NAMES | Cameron |
| FAMILY NAME | Zachreson |
| SIGNATURE | ZACHRESON C |
| AFFILIATIONS | The University of Sydney |
| ORCID | 0000-0002-0578-4049 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
A Microsimulation Model of Behaviour Change Calibrated to Reversal Learning Data
Behaviour change lies at the heart of many observable collective phenomena such as the transmission and control of infectious diseases, adoption of public health policies, and migration of animals to new habitats.Representing the process of individual behaviour change in computer simulations of these phenomena remains an open challenge.Often, computational models use phenomenological implementations with limited support from behavioural data.With…
Simulating Transmission Scenarios of the Delta Variant of Sars-CoV-2 in Australia
An outbreak of the Delta (B.1.617.2) variant of SARS-CoV-2 that began around mid-June 2021 in Sydney, Australia, quickly developed into a nation-wide epidemic. The ongoing epidemic is of major concern as the Delta variant is more infectious than previous variants that circulated in Australia in 2020. Using a re-calibrated agent-based model, we explored a feasible range of non-pharmaceutical interventions, including case isolation, home quarantine…
Modelling transmission and control of the Covid-19 pandemic in Australia
There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, …
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Modelling transmission and control of the Covid-19 pandemic in Australia
There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, …
Simulating Transmission Scenarios of the Delta Variant of Sars-CoV-2 in Australia
An outbreak of the Delta (B.1.617.2) variant of SARS-CoV-2 that began around mid-June 2021 in Sydney, Australia, quickly developed into a nation-wide epidemic. The ongoing epidemic is of major concern as the Delta variant is more infectious than previous variants that circulated in Australia in 2020. Using a re-calibrated agent-based model, we explored a feasible range of non-pharmaceutical interventions, including case isolation, home quarantine…
A Microsimulation Model of Behaviour Change Calibrated to Reversal Learning Data
Behaviour change lies at the heart of many observable collective phenomena such as the transmission and control of infectious diseases, adoption of public health policies, and migration of animals to new habitats.Representing the process of individual behaviour change in computer simulations of these phenomena remains an open challenge.Often, computational models use phenomenological implementations with limited support from behavioural data.With…
Computer Science (2 works) · COVID-19 epidemiological studies (2 works) · Economics (2 works) · Pandemic (2 works) · Social distance (2 works) · Biology (1 work) · Control (management) (1 work) · Coronavirus disease 2019 (COVID-19) (1 work) · COVID-19 and Mental Health (1 work) · demographic modeling and climate adaptation (1 work)