Objectives: To evaluate the risk of a new wave of coronavirus disease 2019 (COVID-19) in a setting with ongoing low transmission, high mobility, and an effective test-and-trace system, under different assumptions about mask uptake.
Design: We used a stochastic agent-based microsimulation model to create multiple simulations of possible epidemic trajectories that could eventuate over a five-week period following prolonged low levels of community transmission.
Setting: We calibrated the model to the epidemiological and policy environment in New South Wales, Australia, at the end of August 2020.
Participants: None
Intervention: From September 1, 2020, we ran the stochastic model with the same initial conditions (i.e., those prevailing at August 31, 2020), and analyzed the outputs of the model to determine the probability of exceeding a given number of new diagnoses and active cases within five weeks, under three assumptions about future mask usage: a baseline scenario of 30% uptake, a scenario assuming no mask usage, and a scenario assuming mandatory mask usage with near-universal uptake (95%).
Main outcome measure: Probability of exceeding a given number of new diagnoses and active cases within five weeks.
Results: The policy environment at the end of August is sufficient to slow the rate of epidemic growth, but may not stop the epidemic from growing: we estimate a 20% chance that NSW will be diagnosing at least 50 new cases per day within five weeks from the date of this analysis. Mandatory mask usage would reduce this to 6-9%.
Conclusions: Mandating the use of masks in community settings would significantly reduce the risk of epidemic resurgence.
An effective Hamiltonian approach for Donor-Bridge-Acceptor electronic transitions: Exploring the role of bath memory
