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

The copyright holder for this preprint . https://doi.org/10.1101/2020.03. 24.20043018 doi: medRxiv preprint / There are some limitations to the study. The true explanation for the age distribution could be a combination of age-specific susceptibility and clinical fraction, although some recent studies indicate children are infected at similar 24 , or slightly lower rates 39 than adults, and children are not commonly spared from other coronavirus infections 40, 41 . It is not possible to simultaneously estimate both effects from available data, so we were unable to validate a mixture model. While information drawn from the early stages of the epidemic are subject to uncertainty, age-specific information is drawn from several regions and countries, and clinical studies support the hypothesis presented here. We assumed that clinical cases are reported at a fixed fraction throughout the time period, although there may have been changes in reporting. We assumed that subclinical infections were less infectious than clinical infections but were not able to estimate how infectious subclinical infections were, instead testing the sensitivity of our findings to this parameter. We have used mixing matrices from the same country, but not the same location as the fitted data. We used contact matrices that combined physical and conversational contacts. We therefore implicitly assume that they are a good reflection of contact relevant for the transmission of SARS-CoV-2. If fomite, or faecal-oral routes of transmission are important in transmission, these contact matrices may not be representative of transmission risk.