The improvement in Victoria’s second wave of COVID-19 cases could be well captured in our transmission model through a combination of time-varying processes that included: testing rates, population mobility, use of face coverings, and physical distancing.
Trauer JM, Lydeamore MJ, Dalton GW, Pilcher D, Meehan MT, McBryde ES, Cheng AC, Sutton B, Ragonnet R.

Objective:

During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria’s second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage.

Findings:

Victoria’s second wave is known to have had particularly dramatic effects on residents of aged care facilities and health care workers, which we did not explicitly capture except by varying parameters relating to disease severity. The concentration of cases in aged care was likely the main factor requiring us to inflate the international estimate for the infection fatality rate for those aged 75 years and over. Our results suggest a markedly higher IFR in this group than that estimated from other settings, but is consistent with the high raw case-fatality rate of 4.3% in the data used for fitting (801 deaths, 18,459 notifications). This highlights the importance of risk factors and comorbid conditions on the estimated IFR, which likely underpin some of the dramatic increases in IFR with increasing age and are particularly concentrated in residents of aged care facilities. For these reasons, we emphasise that our forward projections of a lesser public health response assumed that the IFR for the oldest age group returned to the uninflated international estimate. Our inflation of the age-specific estimates of the risk of hospitalisation given symptomatic COVID-19 are also consistent with a more severe epidemic, although hospital admission is driven by factors other than disease severity. These include infection control and workforce capacity with staff isolation requirements in residential aged care facilities, which were particularly important to this epidemic wave.

View full paper here
First published: Nov 1, 2021
Department of Epidemiology and Preventive Medicine
The Monash University's Department of Epidemiology and Preventive Medicine in the School of Public Health and Preventive Medicine has initially focused on TB epidemiology and control, but recently shifted its focus to include a strong interest in the COVID-19 pandemic. The focus comprises the use of methodological approaches in the areas of deterministic and stochastic modelling, agent-based simulations, applied mathematics, Bayesian inference, statistics, epidemiology, health economics, computer science and data visualisation.