The human respiratory tract hosts a diverse community of cocirculating viruses that are responsible for acute respiratory infections. This shared niche provides the opportunity for virus-virus interactions which have the potential to affect individual infection risks and in turn influence dynamics of infection at population scales. However, quantitative evidence for interactions has lacked suitable data and appropriate analytical tools. Here, we expose and quantify interactions among respiratory viruses using bespoke analyses of infection time series at the population scale and coinfections at the individual host scale. We analyzed diagnostic data from 44,230 cases of respiratory illness that were tested for 11 taxonomically broad groups of respiratory viruses over 9 y. Key to our analyses was accounting for alternative drivers of correlated infection frequency, such as age and seasonal dependencies in infection risk, allowing us to obtain strong support for the existence of negative interactions between influenza and noninfluenza viruses and positive interactions among noninfluenza viruses. In mathematical simulations that mimic 2-pathogen dynamics, we show that transient immune-mediated interference can cause a relatively ubiquitous common cold-like virus to diminish during peak activity of a seasonal virus, supporting the potential role of innate immunity in driving the asynchronous circulation of influenza A and rhinovirus. These findings have important implications for understanding the linked epidemiological dynamics of viral respiratory infections, an important step towards improved accuracy of disease forecasting models and evaluation of disease control interventions. epidemiology | virology | ecology

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.

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Not 1 year has passed since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). Since its emergence, great uncertainty has surrounded the potential for COVID-19 to establish as a seasonally recurrent disease. Many infectious diseases, including endemic human coronaviruses, vary across the year. They show a wide range of seasonal waveforms, timing (phase), and amplitudes, which differ depending on the geographical region. Drivers of such patterns are predominantly studied from an epidemiological perspective with a focus on weather and behavior, but complementary insights emerge from physiological studies of seasonality in animals, including humans. Thus, we take a multidisciplinary approach to integrate knowledge from usually distinct fields. First, we review epidemiological evidence of environmental and behavioral drivers of infectious disease seasonality. Subsequently, we take a chronobiological perspective and discuss within-host changes that may affect susceptibility, morbidity, and mortality from infectious diseases. Based on photoperiodic, circannual, and comparative human data, we not only identify promising future avenues but also highlight the need for further studies in animal models. Our preliminary assessment is that host immune seasonality warrants evaluation alongside weather and human behavior as factors that may contribute to COVID-19 seasonality, and that the relative importance of these drivers requires further investigation. A major challenge to predicting seasonality of infectious diseases are rapid, human-induced changes in the hitherto predictable seasonality of our planet, whose influence we review in a final outlook section. We conclude that a proactive multidisciplinary approach is warranted to predict, mitigate, and prevent seasonal infectious diseases in our complex, changing human-earth system.

Public health preparedness for coronavirus disease 2019 is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal human coronaviruses (sCoVs) and other cocirculating viruses in the West of Scotland, UK. 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.

Identifying drivers of SARS-CoV-2 exposure and quantifying population immunity is crucial to prepare for future epidemics. We performed a serial cross-sectional serosurvey throughout the first pandemic wave among patients from the largest health board in Scotland. Screening of 7480 patient sera showed a weekly seroprevalence ranging from 0.10% to 8.23% in primary and 0.21% to 17.44% in secondary care, respectively. Neutralisation assays showed that around half of individuals who tested positive by ELISA assay, developed highly neutralising antibodies, mainly among secondary care patients. We estimated the individual probability of SARS-CoV-2 exposure and quantified associated risk factors. We show that secondary care patients, males and 45-64-year-olds exhibit a higher probability of being seropositive. The identification of risk factors and the differences in virus neutralisation activity between patient populations provided insights into the patterns of virus exposure during the first pandemic wave and shed light on what to expect in future waves.

HighlightsCross-scale dynamics were investigated for avian influenza in British poultry.Transmission risk is dependent on the assumed within-flock transmission mode.Transmission risk may not scale with transmissibility or flock size.Transmission risk corresponds with between-farm impact for 28% of farms.These results have implications for targeted disease control at the farm-level.

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