Unreliability in Simulations of COVID-19 Cases and Deaths Based on Transmission Models

Abstract

AbstractTwo papers authored by the same research group were published in academic journals in October 2023, both of which simulate counterfactual COVID-19 cases and deaths using transmission models. One paper estimates that the COVID-19 cases and deaths from Feb 17 to Nov 30, 2021 in Japan would have been as many as 63.3 million and 364 thousand respectively had the vaccination not been implemented, where the 95% confidence interval is claimed to be less than 1% of the estimated value. It also claims that the cases and deaths could have been reduced by 54% and 48% respectively had the vaccination been implemented 14 days earlier. The other paper estimates that the number of cases in early 2022, Tokyo would have been larger than the number of populations in the age group under 49 in the absence of the vaccination program. In this paper, we reexamine the results given by these papers to find that the simulation results do not explain the real-world data in Japan including prefectures with early/late vaccination schedules. The cause of discrepancy is identified as low reliability of model parameters that immensely affect the simulation results of case and death counts. Leaders of public healthcare are required to discern the reliability and credibility of simulation studies and to prepare for variety of possible scenarios when reliable predictions are not available.