Scientists and policymakers need to compare the incidence of Covid-19 across territories or periods with various levels of testing. Benchmarking based on the increase in total cases or case fatality rates is one way of comparing the evolution of the pandemic across countries or territories and could inform policy decisions about strategies to control coronavirus transmission. However, comparing cases and fatality rates across regions is challenging due to heterogeneity in testing and health systems. We show two complementary ways of benchmarking across territories and in time. First, we used multivariate regressions to estimate the test-elasticity of Covid-19 case incidence. Cases grow less than proportionally with testing when assessing weekly changes or looking across states in the USA. They tend to be proportional or even more than proportional when comparing the month-to-month evolution of an average country in the pandemic. Our results were robust to various model specifications. Second, we decomposed the growth in cases into test growth and positive test ratio growth to intuitively visualize the components of case growth. We hope these results can help support evidence-based decisions by public officials and help the public discussion when comparing across territories and in time.
【저자키워드】 public health, viral infection, Infectious diseases, Diseases, Diagnosis, Health policy, Preventive medicine, 【초록키워드】 Evolution, coronavirus, pandemic, health systems, Transmission, heterogeneity, Region, Case fatality rate, incidence, USA, change, Regression, complementary, Support, Benchmarking, growth, average, help, Fatality rate, Positive test, scientist, component, second, country, robust, less, increase in, 【제목키워드】 pandemic, USA, Benchmarking, heterogeneous, country,