Abstract

This study analyzed global data on epidemic control measures and economic conditions in different countries during different mutant strain epidemic periods, including the Alpha, Delta, and Omicron strains. The study estimated the elasticity coefficient through a log-log model, which represents the percent change of the confirmed case number with respect to a percent change in the total number of screening tests in a country for epidemic control. The 7-day rolling data of screening tests and confirmed cases from the Our World in Data database for the pandemic periods of Alpha strain in 2020, Delta strain in 2021, and Omicron strain in 2022, suggest that the magnitude of the elasticity was associated with the economic condition of a country. Compared with the results during either Alpha or Delta pandemic period, the Omicron pandemic has a much higher estimated elasticity coefficient of 1.317 (Alpha: 0.827 and Delta: 0.885). Further examining economic conditions categorized by quartile ranges, the results indicate that the elasticity is statistically significantly lower in countries with gross domestic product (GDP) per capita between $11,354 and $26,651, and in countries with GDP per capita above $26,651 than in countries with GDP per capita below $3,335. These results suggest that countries should consider not only epidemiological measures but also economic conditions when formulating epidemic control strategies. This study highlights the importance of assessing the appropriateness of epidemic control strategies within a country and provides valuable insights into the effectiveness of such strategies, particularly in the context of community screening.

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