Age-dependent effects in the transmission and control of COVID-19 epidemics

Nicholas G Davies; Petra Klepac; Yang Liu; Kiesha Prem; Mark Jit; Rosalind M Eggo

Using the best fitting and most biologically plausible hypothesis, hypothesis 3 -age-varying clinical fraction -we estimated the age-specific clinical fraction for 32 settings across six countries by using the stationary distribution of the next generation matrix to reproduce the locally-reported age distribution of cases compiled from a variety of sources (Fig 2a) . We used setting-specific demographics, measured contact matrices where possible, and synthetic contact matrices otherwise 27 . The age-dependent clinical proportion was markedly lower in younger age groups in all regions (Fig 2b) , with 20% of infections in children under 10 resulting in clinical cases, rising to over 70% in adults over 70 in the consensus age distribution estimated across all regions. To determine whether this distribution was capable of reproducing epidemic dynamics, we fitted our dynamic model to the incidence of clinical cases in Beijing, Shanghai, South Korea and Italy ( Fig 2c ) . The consensus age-specific clinical fraction was largely capable of reproducing the age distribution of cases, although there are some outliers, for example the 20-30 age group in South Korea. This could be the result of clustered transmission within a church group in this country 4 . The predicted age distribution of cases for Italy is also less skewed towards older adults than reported cases show, suggesting potential differences in age-specific testing in Italy 28 . Locally-estimated age-varying clinical fraction captured these patterns more precisely (Fig. 2c ) . Estimating age-specific symptomatic rate from age-specific case counts for 6 countries. (a) Age-specific reported cases from 13 provinces of China, 12 regions of Italy, Japan, Singapore, South Korea, and Ontario, Canada. Hollow bars are data and colour is model fit with 95% HDI. (b) Fitted mean and 95% HDI for the age distribution in clinical fraction for all countries. (c) Fitted incidence of confirmed cases and resulting age distribution of cases using either the consensus (grey) or country-specific (colour) age-specific clinical fraction from b.