Although testing is widely regarded as critical to fighting the Covid-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics--population testing number and testing coverage--to population mortality outcomes and identify a benchmark for testing adequacy with respect to population mortality and capture of potential disease burden. This ecological study aggregated publicly available data through April 12 on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. All OECD countries and Taiwan were included in this population-based study as a proxy for countries with highly developed economic and healthcare infrastructure. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate, and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. Testing coverage, but not population testing number, was highly correlated with population mortality (rs= -0.79, P=5.975e-09 vs rs =- 0.3, P=0.05) and case fatality rate (rs= -0.67, P=9.067e-06 vs rs = -0.21, P=0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality, whereas above 45, increased testing did not yield significant incremental mortality benefit. Testing coverage was better than population testing number in explaining country performance and can be used as an early and sensitive indicator of testing adequacy and disease burden. This may be particularly useful as countries consider re-opening their economies.
Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries and Taiwan