Study population and setting
Authors reviewed the evolving case definitions for COVID-19 in mainland China, and used an exponential growth model to estimate the effect each change in case definition had on the number of reported confirmed cases from January 15 to February 20, 2020 as reported by the National Health Commission. Authors assumed changes in the case definition would result in an increase in the number of cases detected and reported relative to the total number of infections. Authors allowed the growth rate of the epidemic curve to change with each changing case definition, and adjusted for major control measures implemented in Mainland China within a statistical model.
Summary of Main Findings
Authors focused on the first five case definitions for COVID-19, each with less stringent clinical, laboratory, and/or contact criteria than the previous version (i.e., each newer version had increased sensitivity). With the exception of one case definition change that only updated definitions for severity classification, each subsequent case definition change, 2.8-7.1 times more cases were identified than would have been if the previous case definition had been used. Had the fifth version of the case definition (final in these analyses) been used throughout the outbreak, authors estimated that the number of confirmed cases by February 20, 2020 would have been over four times the number actually reported. Before January 23, 2020, authors estimated that 92% of cases went undetected by using earlier case definition versions. Overall, authors found that if changing case definitions were not accounted for, then the growth rate of the COVID-19 epidemic would be overestimated and the doubling time (i.e., time it takes for the number of cases to double) would have been underestimated (indicating faster and greater overall growth of the epidemic).
Authors estimated the epidemic growth rate for Wuhan, Hubei province alone and the rest of mainland China (excluding Wuhan) separately, which allowed them to account for regional differences in parameters such as epidemic timing and transmissibility. Authors attempted to appropriately account for uncertainty in model parameters such as growth rates and doubling time.
Authors used a statistical model that relied on exponential growth and decay only, and did not account for more complex epidemiological parameters that may have affected transmission (e.g., social distancing interventions). Authors were also unable to access information on incidence by illness onset after February 20, 2020 and were therefore unable to evaluate the effects of changes in case definition to epidemic growth after version 5.
This study demonstrates the real-world implications for evolving case definitions during an epidemic, and the importance of accounting for these changes when estimating epidemiological parameters. Results of this study suggest large and rapid epidemic growth may be artifacts of public health interventions, such as expansions in testing.
This review was posted on: 17 June 2020