Epidemiology of Seasonal Coronaviruses: Establishing the Context for the Emergence of Coronavirus Disease 2019

Abstract

Public health preparedness for coronavirus (CoV) disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal CoVs (sCoVs) and other cocirculating viruses in the West of Scotland, United Kingdom. We analyzed routine diagnostic data for >70 000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43, and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently, and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.

Keywords: SARS-CoV-2; Acute respiratory infections; Coinfection; Disease surveillance; Virus-virus interactions.

Figure 1.

Data flow diagram summarizing patient subsets informing each analysis. Samples from 64 948 patients were subjected to molecular tested for respiratory viruses, performed with real-time multiplex reverse-transcription polymerase chain reaction in NHS Greater Glasgow and Clyde, Scotland, United Kingdom, between 1 January 2005 and 30 September 2017. Abbreviation: sCoV, seasonal coronavirus.

Figure 2.

Percentages of viral respiratory infections attributed to human coronaviruses and other common respiratory viruses during each influenza season (October–May) from 2005–2006 until 2016–2017, based on 84 957 episodes of respiratory illness. Influenza includes influenza A and influenza B viruses combined; and “other” includes human adenoviruses, human metapneumovirus, and parainfluenza viruses type 1–4. Note: Years of major pandemic influenza A H1N1 virus circulation (2009–2010 and 2010–2011) must be viewed with caution, owing to high levels of partial testing. Testing for CoV-HKU1was discontinued in 2012. Abbreviations: CoV, human coronaviruses (CoV-229E, CoV-OC43, CoV-NL63, and CoV-HKU1 combined); RSV, respiratory syncytial virus; RV, human rhinovirus.

Figure 3.

Age distributions of general practice (GP; primary care) and hospital (secondary/tertiary care) patients tested and positive for human coronavirus (CoV), (A) and percentages of female patients (B). Note the different y-axis scale for CoV cases in A. Hospital patients include inpatients and outpatients.

Figure 4.

Average age-specific predicted probabilities of human coronavirus (CoV) detections by patient sex and healthcare service setting ( general practice [GP; primary care] or hospital [inpatients and outpatients; secondary or tertiary care]). Data were derived from multivariable logistic regression models incorporating statistical interactions between patient age and healthcare service (see Supplementary Tables 5–7 for model results without statistical interactions).

Figure 5.

Monthly prevalence of seasonal coronaviruses (sCoVs) detected among patients with respiratory illness virologically tested in NHS Greater Glasgow and Clyde, Scotland, United Kingdom, between January 2005 and September 2017. A, CoV-229E. B, CoV-OC43. C, CoV-NL63. D, Comparing all sCoV types.