The Impact of Cocirculating Pathogens on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/Coronavirus Disease 2019 Surveillance: How Concurrent Epidemics May Introduce Bias and Decrease the Observed SARS-CoV-2 Percentage Positivity

Clinical Performance of the BD Respiratory Viral Panel for BD MAX™ System in Detecting SARS-CoV-2, Influenza A and B, and Respiratory Syncytial Virus

Using a nasopharyngeal (NP) or anterior nasal (NS) swab from prospectively collected or retrospective specimens, we assessed the clinical performance of the BD Respiratory Viral Panel (BD RVP) for BD MAX System against FDA-cleared or authorized comparators. Across prospective and retrospective specimens, positive percent agreement (PPA) was ≥ 98.4% for SARS-CoV-2, ≥ 96.7% for influenza (flu) A, ≥ 91.7% for respiratory syncytial virus (RSV), and 100% for flu B (retrospective only) while negative percent agreement (NPA) was ≥ 97.7% across all targets, leading to the assay FDA clearance. A head-to-head comparison of NS versus NP results with BD RVP was also performed; PPA was ≥ 90% and NPA ≥ 98.2% for SARS-CoV-2, flu A and RSV. These findings confirm that the BD MAX RVP assay performs well for detection and differentiation of the three viruses in NP and NS specimens, with strong interrater agreements for NS versus NP comparisons.

Outcomes of SARS-CoV-2 and Seasonal Viruses Among 2 Million Adults Hospitalized for Severe Acute Respiratory Infection During the COVID-19 Pandemic in Brazil

BACKGROUND

The outbreak of the COVID-19 pandemic has had a profound impact on the circulation of seasonal respiratory viruses. This study aimed to compare the outcomes of SARS-CoV-2 and seasonal viruses in adults hospitalized with severe acute respiratory infection during the COVID-19 pandemic.

METHODS

This population-based cohort study included patients aged >18 years hospitalized for severe acute respiratory infection in Brazil between February 2020 and February 2023. The primary outcome was in-hospital mortality. A competing risk analysis was used to account for competing events.

RESULTS

In total, 2 159 171 patients were included in the study. SARS-CoV-2 was the predominant virus (98.7%). Among patients testing positive, the cumulative incidence of in-hospital mortality was 33.1% for SARS-CoV-2, 31.5% for adenovirus, 21.0% for respiratory syncytial virus, 18.7% for influenza, and 18.6% for other viruses. SARS-CoV-2 accounted for 99.3% of the deaths. Older age, male sex, comorbidities, hospitalization in the northern region, and oxygen saturation <95% were the common risk factors for death among all viruses.

CONCLUSIONS

In this large cohort study, individuals infected with SARS-CoV-2 or adenovirus had the highest risk of mortality. Irrespective of the virus type, older age, male sex, comorbidities, hospitalization in vulnerable regions, and low oxygen saturation were associated with an increased risk of fatality.

Seasonality and Co-Detection of Respiratory Viral Infections Among Hospitalised Patients Admitted With Acute Respiratory Illness-Valencia Region, Spain, 2010-2021

BACKGROUND

Respiratory viruses are known to represent a high burden in winter, yet the seasonality of many viruses remains poorly understood. Better knowledge of co-circulation and interaction between viruses is critical to prevention and management. We use > 10-year active surveillance in the Valencia Region to assess seasonality and co-circulation.

METHODS

Over 2010-2021, samples from patients hospitalised for acute respiratory illness were analysed using multiplex real-time PCR to test for 9 viruses: influenza, respiratory syncytial virus (RSV), parainfluenza virus (PIV), rhino/enteroviruses (HRV/ENV), metapneumovirus (MPV), bocavirus, adenovirus, SARS-CoV-2 and non-SARS coronaviruses (HCoV). Winter seasonal patterns of incidence were examined. Instances of co-detection of multiple viruses in a sample were analysed and compared with expected values under a crude model of independent circulation.

RESULTS

Most viruses exhibited consistent patterns between years. Specifically, RSV and influenza seasons were clearly defined, peaking in December-February, as did HCoV and SARS-CoV-2. MPV, PIV and HRV/ENV showed less clear seasonality, with circulation outside the observed period. All viruses circulated in January, suggesting any pair had opportunity for co-infection. Multiple viruses were found in 4% of patients, with more common co-detection in children under 5 (9%) than older ages. Influenza co-detection was generally observed infrequently relative to expectation, while RSV co-detections were more common, particularly among young children.

CONCLUSIONS

We identify characteristic patterns of viruses associated with acute respiratory hospitalisation during winter. Simultaneous circulation permits extensive co-detection of viruses, particularly in young children. However, virus combinations appear to differ in their rates of co-detection, meriting further study.

Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report

In July 2023, the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic. This report summarizes the rich discussions that occurred during the workshop. The workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data, social media, and wastewater monitoring. Significant advancements were noted in the development of predictive models, with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease trends. The role of open collaboration between various stakeholders in modelling was stressed, advocating for the continuation of such partnerships beyond the pandemic. A major gap identified was the absence of a common international framework for data sharing, which is crucial for global pandemic preparedness. Overall, the workshop underscored the need for robust, adaptable modelling frameworks and the integration of different data sources and collaboration across sectors, as key elements in enhancing future pandemic response and preparedness.

The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps

Despite the availability of effective vaccines, the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that cocirculation with other pathogens and resulting multiepidemics (of, for example, COVID-19 and influenza) may become increasingly frequent. To better forecast and control the risk of such multiepidemics, it is essential to elucidate the potential interactions of SARS-CoV-2 with other pathogens; these interactions, however, remain poorly defined. Here, we aimed to review the current body of evidence about SARS-CoV-2 interactions. Our review is structured in four parts. To study pathogen interactions in a systematic and comprehensive way, we first developed a general framework to capture their major components: sign (either negative for antagonistic interactions or positive for synergistic interactions), strength (i.e., magnitude of the interaction), symmetry (describing whether the interaction depends on the order of infection of interacting pathogens), duration (describing whether the interaction is short-lived or long-lived), and mechanism (e.g., whether interaction modifies susceptibility to infection, transmissibility of infection, or severity of disease). Second, we reviewed the experimental evidence from animal models about SARS-CoV-2 interactions. Of the 14 studies identified, 11 focused on the outcomes of coinfection with nonattenuated influenza A viruses (IAVs), and 3 with other pathogens. The 11 studies on IAV used different designs and animal models (ferrets, hamsters, and mice) but generally demonstrated that coinfection increased disease severity compared with either monoinfection. By contrast, the effect of coinfection on the viral load of either virus was variable and inconsistent across studies. Third, we reviewed the epidemiological evidence about SARS-CoV-2 interactions in human populations. Although numerous studies were identified, only a few were specifically designed to infer interaction, and many were prone to multiple biases, including confounding. Nevertheless, their results suggested that influenza and pneumococcal conjugate vaccinations were associated with a reduced risk of SARS-CoV-2 infection. Finally, fourth, we formulated simple transmission models of SARS-CoV-2 cocirculation with an epidemic viral pathogen or an endemic bacterial pathogen, showing how they can naturally incorporate the proposed framework. More generally, we argue that such models, when designed with an integrative and multidisciplinary perspective, will be invaluable tools to resolve the substantial uncertainties that remain about SARS-CoV-2 interactions.