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Impact of changing case definitions for COVID-19 on the epidemic curve and transmission parameters in mainland China

Tsang, T. K.; Wu, P.; Yun Lin, Y. L.; Lau, E.; Leung, G. M.; Cowling, B. J.

2020-03-27 epidemiology
10.1101/2020.03.23.20041319
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BackgroundWhen a new infectious disease emerges, appropriate case definitions are important for clinical diagnosis and also for public health surveillance. Tracking case numbers over time allows us to determine speed of spread and the effectiveness of interventions. Changing case definitions during an epidemic can affect these inferences. MethodsWe examined changes in the case definition for COVID-19 in mainland China during the first epidemic wave. We used simple models assuming exponential growth and then exponential decay to estimate how changes in the case definitions affected the numbers of cases reported each day. We then inferred how the epidemic curve would have appeared if the same case definition had been used throughout the epidemic. FindingsFrom January through to early March 2020, seven versions of the case definition for COVID-19 were issued by the National Health Commission in China. As of February 20, there were 55,508 confirmed cases reported in mainland China. We estimated that when the case definitions were changed from version 1 to 2, version 2 to 4 and version 4 to 5, the proportion of infections being detected as cases were increased by 7.1-fold (95% credible interval (CI): 4.8, 10.9), 2.8-fold (95% CI: 1.9, 4.2) and 4.2-fold (95% CI: 2.6, 7.3) respectively. If the fifth version of the case definition had been applied throughout the outbreak, we estimated that by February 20 there would have been 232,000 (95% CI: 161,000, 359,000) confirmed cases. InterpretationThe case definition was initially narrow, but was gradually broadened to allow detection of more cases as knowledge increased, particularly milder cases and those without epidemiological links to Wuhan or other known cases. This should be taken into account when making inferences on epidemic growth rates and doubling times, and therefore on the reproductive number, to avoid bias. FundingCommissioned grant from the Health and Medical Research Fund, Food and Health Bureau, Government of the Hong Kong Special Administrative Region.

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