We compare the health and economic costs of early and delayed mandated suppression and the unmitigated spread of ‘first-wave’ COVID-19 infections in Australia in 2020.
We constructed an epidemiological model of COVID-19 infections in Australia that has five compartments: Susceptible, Infected, Quarantined, Recovered, and Mortality, using recorded data for Q, R, and M. We estimated parameters and tested the model to actual recorded data from March 1st to April 20th, 2020, and test the model on recorded data thereafter. Five parameters were estimated: the infectious period, the period over which an individual can spread the virus (which can occur before developing symptoms) to ceasing to spread the virus because of quarantine, recovery, or death; the basic reproduction number and the reduction in community transmission after the Australian government introduced each of the three principal suppression measures, i.e., March 19th -21st, March 22nd–28th, and after March 28th, all lagged before coming into effect by the appropriate number of days. We fitted the number of recorded cases projected by the model to the number of observed cases using a non-linear least squares technique that estimated the parameters by minimizing the sum of the squared distance between the projected and actual values. To determine impacts on patient welfare, we estimated hospital and ICU costs and used both a Value of a Statistical Life Year (VSLY) measure and an age-adjusted Value of Statistical Life (a-VSL). Economy costs from lockdowns were also estimated in terms of losses in regional incomes and the loss of overseas tourist revenue.
Using a fit-for-purpose SIQRM-compartment model for susceptible, infected, quarantined, recovered and mortalities on active cases, that we fitted from recorded data, a value of a statistical life year (VSLY) and an age-adjusted value of statistical life (A-VSL), we find that the economic costs of unmitigated suppression are multiples more than for early mandated suppression of COVID-19. We also find that using an equivalent VSLY welfare loss from fatalities to estimated GDP losses, drawn from survey data and our own estimates of the impact of suppression measures on the economy, means that for early suppression not to be the preferred strategy requires that Australia would have to incur more than 12,500–30,000 deaths, depending on the fatality rate with unmitigated spread, to the economy costs of early mandated suppression.
We find that early rather than delayed mandated suppression imposes much lower economy and health costs and conclude that in high-income countries, like Australia, a ‘go early, go hard’ strategy to suppress COVID-19 results in the lowest estimated public health and economy costs.