Seasonal coronaviruses and establishing the context for COVID-19 emergence

Seasonal coronaviruses and establishing the context for COVID-19 emergence. Spencer EA, Jefferson T, Heneghan C

Published on June 16, 2020

Reference Nickbakhsh S, Ho A, Marques DFP et al. Epidemiology of seasonal coronaviruses: Establishing the context for COVID-19 emergence. J Infect Dis. 2020;jiaa185. 2020
Study type
Country Scotland, UK
Setting Primary and secondary healthcare services
Funding Details Medical Research Council, UK
Transmission mode Seasonality
Exposures Seasonal coronaviruses: CoV-229E, CoV-NL63, CoV-OC43 and CoV-HKU1

Bottom Line

Seasonal coronaviruses were detected in 4% of patients with respiratory illness who were tested at primary/secondary healthcare settings.

Evidence Summary

Seasonal coronaviruses on average peaking between January and March.

  • Prior to the pandemic influenza in 2009, 229E peaked biennially, but subsequently exhibited longer inter-peak periods.
  • The timing of the peak prevalence of OC43 and NL63 for most seasons is synchronous.
  • 229E was more distinctive in its temporal pattern.

Low levels of 229E in 2007 coincided with high levels of OC43 and NL63, whereas the high prevalence of 229E in 2010 coincided with low levels of OC43 and NL63.

Graph of seasonal coronavirus infections

Source: J Infect Dis, jiaa185,

What did they do?

The study examined who is affected by seasonal coronaviruses (sCoVs) and other co-circulating viruses, and when (not SARS-CoV-2, which has emerged since these diagnostic data were collected).  Since endemic circulating coronaviruses may share similar modes of transmission with SARS-CoV, this study might give information relevant to the COVID-19 pandemic.

Routine diagnostic data for episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017 was analysed. 107,174 clinical respiratory samples from 64,948 individual patients were available; after aggregating by illness episode and retaining only the first observed episode to remove patient-level clustering, 56,276 patient observations were available for analysis.

Associations between three coronaviruses types and age, sex, primary vs secondary healthcare setting, time period according to 3 major influenza outbreaks in the UK 2005 to 2017, and season were investigated.  In the conclusions, the authors discussed the implications for COVID-19. This study does not include information from the COVID-19 pandemic or SARS-CoV-2.

Study reliability

This is a moderately large dataset and the reported associations with covariables are  reasonably precise.

Clearly defined setting Demographic characteristics described Follow-up length was sufficient Transmission outcomes assessed Main biases are taken into consideration
Unclear No Yes No Unclear

What else should I consider?

The authors point out that their findings highlight the importance of considering co-circulating viruses in the differential diagnosis of COVID-19. Epidemiological knowledge of seasonal coronaviruses is often lacking due to its absence n in routine diagnostic testing. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across the different coronaviruses and with SARS-CoV-2, as well as the role of viral coinfection in COVID-19 disease severity.

See also “Coronavirus occurrence and transmission over 8 years in the HIVE cohort of households in Michigan” in J Infect Dis, jiaa161.

About the authors

Carl Heneghan

Carl Heneghan

Carl is Professor of EBM & Director of CEBM at the University of Oxford. He is also a GP and tweets @carlheneghan. He has an active interest in discovering the truth behind health research findings

Elizabeth Spencer

Elizabeth Spencer

Dr Elizabeth Spencer; MMedSci, PhD. Epidemiologist, Nuffield Department for Primary Care Health Sciences, University of Oxford.

Tom Jefferson

Tom Jefferson

Tom Jefferson is a senior associate tutor and honorary research fellow, Centre for Evidence-Based Medicine, University of Oxford.