Retrospective Evaluation of the Effectiveness of COVID-19 Control Strategies Implemented by the Victorian Government in Melbourne—A Proposal for a Standardized Approach to Review and Reappraise Control Measures

Abstract

In evaluating the effectiveness of COVID-19 control measures, we propose a standardized approach to assess the impact of COVID-19 management on flattening the curve by analyzing the case data of Victoria, Australia. Its capital, Melbourne, is considered the most lock-downed city in the world. We used the daily case data from Victoria and their first time derivative and compared the dates when the six lockdowns were imposed with the start and end of the effective period, i.e., the period between the maximum and minimum acceleration. Lockdowns 1, 2 (Level 4 restrictions), 3, and 4 were found to be implemented too late, as they were expected to come into effect at the end or after the effective phase, and they were therefore ineffective. It was determined that Lockdown 2 (Level 3 restrictions) did not initiate the effective phase, and it was therefore ineffective, too. Lockdown 5 was expected to take effect in the second half of the effective phase, but showed no changes in the acceleration curve, and it was therefore also ineffective. Lockdown 6, implemented well before the effective period, did not flatten the curve, and was thus also found to be ineffective. The mask mandate between Lockdown 2 (Level 3 and 4 restrictions) initiated the effective phase (likely along with Lockdown 2, Level 3 restrictions), and was therefore found to effectively flatten the curve. The temporal relationship between the assumed cause (control measure) and the observed effect (flattening of the curve) is thus a crucial parameter for assessing the effect of control measures.