Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling

The role of viral interaction in household transmission of symptomatic influenza and respiratory syncytial virus

The role of viral interaction-where one virus enhances or inhibits infection with another virus-in respiratory virus transmission is not well characterized. This study used data from 4029 total participants from 957 households who participated in a prospective household cohort study in Southeast Michigan, U.S.A to examine how viral coinfection and cocirculation may impact transmission of symptomatic influenza and respiratory syncytial virus infections. We utilized multivariable mixed effects regression to estimate transmission risk when index cases were coinfected with multiple viruses and when viruses cocirculated within households. This analysis included 201 coinfections involving influenza A virus, 67 involving influenza B virus, and 181 involving respiratory syncytial virus. We show that exposure to symptomatic coinfected index cases was associated with reduced risk of influenza A virus and respiratory syncytial virus transmission compared to exposure to singly infected cases, while infection with another virus was associated with increased risk of acquisition of these viruses. Exposure to coinfected cases among contacts infected with other viruses was associated with increased risk of influenza B virus acquisition. These results suggest that viral interaction may impact symptomatic transmission of these viruses.

Respiratory virus detections in children presenting to an Australian paediatric referral hospital pre-COVID-19 pandemic, January 2014 to December 2019

Acute respiratory infections cause significant paediatric morbidity, but for pathogens other than influenza, respiratory syncytial virus (RSV), and SARS-CoV-2, systematic monitoring is not commonly performed. This retrospective analysis of six years of routinely collected respiratory pathogen multiplex PCR testing at a major paediatric hospital in New South Wales Australia, describes the epidemiology, year-round seasonality, and co-detection patterns of 15 viral respiratory pathogens. 32,599 respiratory samples from children aged under 16 years were analysed. Most samples were associated with a hospital admission (24,149, 74.1%) and the median age of sampling was 16 months (IQR 5-53). Viruses were detected in 62.9% (20,510) of samples, with single virus detections occurring in 73.5% (15,082) of positive samples. In instances of single virus detection, rhinovirus was most frequent (5125, 40.6%), followed by RSV-B (1394, 9.2%) and RSV-A (1290, 8.6%). Moderate to strong seasonal strength was observed for most viruses with some notable exceptions. Rhinovirus and enterovirus were detected year-round and low seasonal strength was observed for adenovirus and bocavirus. Biennial seasonal patterns were observed for influenza B and parainfluenza virus 2. Co-detections occurred in 5,428 samples, predominantly with two (4284, 79.0%) or three viruses (904, 16.7%). The most common co-detections were rhinovirus-adenovirus (566, 10.4%), rhinovirus-enterovirus (357, 8.3%), and rhinovirus-RSV-B (337, 7.9%). Ongoing pan-pathogen surveillance, integrating both laboratory and clinical data, is necessary to assist in identification of key pathogens and combination of pathogens to support effective preventative public health strategies and reduce the burden of paediatric respiratory infections.

Whole-genome analysis of circulating influenza A virus (H3N2) strains in Shanghai, China from 2005 to 2023

Seasonal influenza A virus subtype H3N2 (A/H3N2) circulates globally and has been linked to higher hospitalization rates and summer outbreaks in temperate regions. Here, A/H3N2 circulation in Shanghai, China was systematically studied using data and materials generated by the Shanghai influenza surveillance network from 2005 to 2023. Time-series analysis of incidence and subtyping data showed that A/H3N2 co-circulated with other (sub)types and dominated in multiple seasonal influenza peaks, preferentially in summer. Whole genomes of 528 representative strains were sequenced, and spatiotemporal phylodynamic analysis using these and GISAID-archived sequences demonstrated that in the years before the COVID-19 pandemic, phylogenetically similar strains were circulating locally and elsewhere. However, clade 1a.1 (within 3C.2a.1b.2a), circulated in and only in Shanghai and domestically in 2022, while the sibling clade 2 predominated in other regions. Interestingly, clade 1a.1 was swiftly and completely replaced by clade 2, mostly 2a.3a.1, at the start of 2023. In hemagglutination inhibition and neutralization assays, sera from healthy donors collected in 2022 displayed higher or similar reactivity against 2a.3a.1 compared to 1a.1. By contrast, transcription and replication competence of 2a.3a.1 in MDCK cells was higher than 1a.1. These results indicated that instead of antigenicity differences enabling evasion of pre-existing immunity, higher replicative capability more likely contributed to 2a.3a.1 viruses achieving dominance in China. In addition to summarizing patterns of A/H3N2 local circulation in Shanghai, this work revealed an unusual episode in A/H3N2 global circulation and evolution dynamics in connection to the COVID-19 pandemic and explored possible mechanistic explanations.

Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for epidemic control

Pathogen-pathogen interactions represent a critical but little-understood feature of infectious disease dynamics. In particular, experimental evidence suggests that influenza virus and respiratory syncytial virus (RSV) compete with each other, such that infection with one confers temporary protection against the other. However, such interactions are challenging to study using common epidemiologic methods. Here, we use a mathematical modeling approach, in conjunction with detailed surveillance data from Hong Kong and Canada, to infer the strength and duration of the interaction between influenza and RSV. Based on our estimates, we further utilize our model to evaluate the potential conflicting effects of live attenuated influenza vaccines (LAIV) on RSV burden. We find evidence of a moderate to strong, negative, bidirectional interaction, such that infection with either virus yields 40-100% protection against infection with the other for one to five months. Assuming that LAIV reduces RSV susceptibility in a similar manner, we predict that the impact of such a vaccine at the population level would likely depend greatly on underlying viral circulation patterns. More broadly, we highlight the utility of mathematical models as a tool to characterize pathogen-pathogen interactions.

Contribution of Other Respiratory Viruses During Influenza Epidemic Activity in Catalonia, Spain, 2008-2020

BACKGROUND

During seasonal influenza activity, circulation of other respiratory viruses (ORVs) may contribute to the increased disease burden that is attributed to influenza without laboratory confirmation. The objective of this study was to characterize and evaluate the magnitude of this contribution over 12 seasons of influenza using the Acute Respiratory Infection Sentinel Surveillance system in Catalonia (PIDIRAC).

METHODS

A retrospective descriptive study of isolations from respiratory samples obtained by the sentinel surveillance network of physicians was carried out from 2008 to 2020 in Catalonia, Spain. Information was collected on demographic variables (age, sex), influenza vaccination status, epidemic activity weeks each season, and influenza laboratory confirmation.

RESULTS

A total of 12,690 samples were collected, with 46% (5831) collected during peak influenza seasonal epidemic activity. In total, 49.6% of the sampled participants were male and 51.1% were aged <15 years. Of these, 73.7% (4298) of samples were positive for at least one respiratory virus; 79.7% (3425 samples) were positive for the influenza virus (IV), with 3067 samples positive for one IV type, 8 samples showing coinfection with two types of IV, and 350 showing coinfection of IV with more than one virus. The distribution of influenza viruses was 64.2% IVA, 35.2% IVB, and 0.1% IVC. Of the other respiratory viruses identified, there was a high proportion of human rhinovirus (32.3%), followed by human adenovirus (24.3%) and respiratory syncytial virus (18; 7%). Four percent were coinfected with two or more viruses other than influenza. The distribution of coinfections with ORVs and influenza by age groups presents a significant difference in proportions for 0-4, 5-14, 15-64 and >64 (21.5%, 10.8%, 8.2% and 7.6%: p < 0.001). A lower ORVs coinfection ratio was observed in the influenza-vaccinated population (11.9% vs. 17.4% OR: 0.64 IC 95% 0.36-1.14).

CONCLUSIONS

During the weeks of seasonal influenza epidemic activity, other respiratory viruses contribute substantially, either individually or through the coinfection of two or more viruses, to the morbidity attributed to influenza viruses as influenza-like illness (ILI). The contribution of these viruses is especially significant in the pediatric and elderly population. Identifying the epidemiology of most clinically relevant respiratory viruses will aid the development of models of infection and allow for the development of targeted treatments, particularly for populations most vulnerable to respiratory viruses-induced diseases.

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.

Are secondary bacterial pneumonia mortalities increased because of insufficient pro-resolving mediators?

Respiratory viral infections, including respiratory syncytial virus (RSV), parainfluenza viruses and type A and B influenza viruses, can have severe outcomes. Bacterial infections frequently follow viral infections, and influenza or other viral epidemics periodically have higher mortalities from secondary bacterial pneumonias. Most secondary bacterial infections can cause lung immunosuppression by fatty acid mediators which activate cellular receptors to manipulate neutrophils, macrophages, natural killer cells, dendritic cells and other lung immune cells. Bacterial infections induce synthesis of inflammatory mediators including prostaglandins and leukotrienes, then eventually also special pro-resolving mediators, including lipoxins, resolvins, protectins and maresins, which normally resolve inflammation and immunosuppression. Concurrent viral and secondary bacterial infections are more dangerous, because viral infections can cause inflammation and immunosuppression before the secondary bacterial infections worsen inflammation and immunosuppression. Plausibly, the higher mortalities of secondary bacterial pneumonias are caused by the overwhelming inflammation and immunosuppression, which the special pro-resolving mediators might not resolve.

Chemical composition combined with network pharmacology and quality markers analysis for the quality evaluation of Qing-fei-da-yuan granules

Qing-fei-da-yuan granules (QFDYGs) had been proved to be an effective TCM prescription for treating coronavirus disease 2019 (COVID-19), which are composed of a variety of TCMs, and characterized by multiple components, multiple targets and overall regulation. It is meaningful to further study the chemical composition and pharmacology of QFDYGs for quality evaluation. However, due to the complexity of the components of QFDYGs, there are no reliable and simple analytical methods for current quality evaluation. In this work, antipyretic activity assessment of QFDYGs in the LPS-induced New Zealand rabbit model was carried out to verify the efficacy firstly. It was proved that QFDYGs can be used to relieve fever to help preventing or controlling the prevalence of influenza and pneumonia. Subsequently, UHPLC-ESI-QTOF-MS/MS combined with network pharmacology, quality markers and fingerprint analysis were used to establish the quality control condition. The chemical compositions were analyzed by UHPLC-ESI-QTOF-MS/MS, and 79 of them were identified, such as arecoline, mangiferin, paeoniflorin, etc. Then, the network pharmacology strategy based on 45 candidate components (CCs) in conjunction with influenza and pneumonia diseases was employed to screen the potential active ingredients. According to the drug-CCs-genes-diseases (D-CCs-G-D) networks, baicalein, honokiol, baicalin, paeoniflorin, saikosaponin A, glycyrrhizic acid and hesperidin were selected as quality markers. And a method for content determination of the 7 quality markers was established by optimizing extraction methods, chromatographic conditions and methodological verification. Finally, the quality of 15 batches of QFDYGs was evaluated by using the 7 quality markers combined with fingerprints and principal component analysis (PCA). The analyzed results showed that baicalin, paeoniflorin, glycyrrhizic acid and hesperidin were the high content and stable quality markers. QFDYGs were characterized by overall consistency and individual ingredient differences among the 15 batches. Our quality evaluation study will provide reference for the further development and research of QFDYGs.

Sentinel Enhanced Dengue Surveillance System - Puerto Rico, 2012-2022

Problem/Condition

Dengue is the most prevalent mosquitoborne viral illness worldwide and is endemic in Puerto Rico. Dengue's clinical spectrum can range from mild, undifferentiated febrile illness to hemorrhagic manifestations, shock, multiorgan failure, and death in severe cases. The disease presentation is nonspecific; therefore, various other illnesses (e.g., arboviral and respiratory pathogens) can cause similar clinical symptoms. Enhanced surveillance is necessary to determine disease prevalence, to characterize the epidemiology of severe disease, and to evaluate diagnostic and treatment practices to improve patient outcomes. The Sentinel Enhanced Dengue Surveillance System (SEDSS) was established to monitor trends of dengue and dengue-like acute febrile illnesses (AFIs), characterize the clinical course of disease, and serve as an early warning system for viral infections with epidemic potential.

Reporting Period

May 2012-December 2022.

Description of System

SEDSS conducts enhanced surveillance for dengue and other relevant AFIs in Puerto Rico. This report includes aggregated data collected from May 2012 through December 2022. SEDSS was launched in May 2012 with patients with AFIs from five health care facilities enrolled. The facilities included two emergency departments in tertiary acute care hospitals in the San Juan-Caguas-Guaynabo metropolitan area and Ponce, two secondary acute care hospitals in Carolina and Guayama, and one outpatient acute care clinic in Ponce. Patients arriving at any SEDSS site were eligible for enrollment if they reported having fever within the past 7 days. During the Zika epidemic (June 2016-June 2018), patients were eligible for enrollment if they had either rash and conjunctivitis, rash and arthralgia, or fever. Eligibility was expanded in April 2020 to include reported cough or shortness of breath within the past 14 days. Blood, urine, nasopharyngeal, and oropharyngeal specimens were collected at enrollment from all participants who consented. Diagnostic testing for dengue virus (DENV) serotypes 1-4, chikungunya virus, Zika virus, influenza A and B viruses, SARS-CoV-2, and five other respiratory viruses was performed by the CDC laboratory in San Juan.

Results

During May 2012-December 2022, a total of 43,608 participants with diagnosed AFI were enrolled in SEDSS; a majority of participants (45.0%) were from Ponce. During the surveillance period, there were 1,432 confirmed or probable cases of dengue, 2,293 confirmed or probable cases of chikungunya, and 1,918 confirmed or probable cases of Zika. The epidemic curves of the three arboviruses indicate dengue is endemic; outbreaks of chikungunya and Zika were sporadic, with case counts peaking in late 2014 and 2016, respectively. The majority of commonly identified respiratory pathogens were influenza A virus (3,756), SARS-CoV-2 (1,586), human adenovirus (1,550), respiratory syncytial virus (1,489), influenza B virus (1,430), and human parainfluenza virus type 1 or 3 (1,401). A total of 5,502 participants had confirmed or probable arbovirus infection, 11,922 had confirmed respiratory virus infection, and 26,503 had AFI without any of the arboviruses or respiratory viruses examined.

Interpretation

Dengue is endemic in Puerto Rico; however, incidence rates varied widely during the reporting period, with the last notable outbreak occurring during 2012-2013. DENV-1 was the predominant virus during the surveillance period; sporadic cases of DENV-4 also were reported. Puerto Rico experienced large outbreaks of chikungunya that peaked in 2014 and of Zika that peaked in 2016; few cases of both viruses have been reported since. Influenza A and respiratory syncytial virus seasonality patterns are distinct, with respiratory syncytial virus incidence typically reaching its annual peak a few weeks before influenza A. The emergence of SARS-CoV-2 led to a reduction in the circulation of other acute respiratory viruses.

Public Health Action

SEDSS is the only site-based enhanced surveillance system designed to gather information on AFI cases in Puerto Rico. This report illustrates that SEDSS can be adapted to detect dengue, Zika, chikungunya, COVID-19, and influenza outbreaks, along with other seasonal acute respiratory viruses, underscoring the importance of recognizing signs and symptoms of relevant diseases and understanding transmission dynamics among these viruses. This report also describes fluctuations in disease incidence, highlighting the value of active surveillance, testing for a panel of acute respiratory viruses, and the importance of flexible and responsive surveillance systems in addressing evolving public health challenges. Various vector control strategies and vaccines are being considered or implemented in Puerto Rico, and data from ongoing trials and SEDSS might be integrated to better understand epidemiologic factors underlying transmission and risk mitigation approaches. Data from SEDSS might guide sampling strategies and implementation of future trials to prevent arbovirus transmission, particularly during the expansion of SEDSS throughout the island to improve geographic representation.

Primary Vocal Cord Aspergillosis Can Involve the Trachea and Bronchus in Previously Healthy Patients: A Case Report

Primary vocal cord aspergillosis is extremely rare in immunocompetent individuals, in whom lesions are mainly confined to the larynx, with the possibility of tracheal and bronchial infection largely ignored. In this article, we present a case of primary vocal cord aspergillosis involving the trachea and bronchus in a previously healthy 55-year-old woman. Our case highlights that vocal cord aspergillosis can involve the trachea and bronchus and that laryngoscopy alone may be insufficient to secure a comprehensive diagnosis in healthy patients presenting with hoarseness, pharyngalgia, and normal chest radiography. Furthermore, influenza B virus infection may be a risk factor for this rare disease.

Intensity and drivers of subtypes interference between seasonal influenza viruses in mainland China: A modeling study

Subtype interference has a significant impact on the epidemiological patterns of seasonal influenza viruses (SIVs). We used attributable risk percent [the absolute value of the ratio of the effective reproduction number (Rₑ) of different subtypes minus one] to quantify interference intensity between A/H1N1 and A/H3N2, as well as B/Victoria and B/Yamagata. The interference intensity between A/H1N1 and A/H3N2 was higher in southern China 0.26 (IQR: 0.11-0.46) than in northern China 0.17 (IQR: 0.07-0.24). Similarly, interference intensity between B/Victoria and B/Yamagata was also higher in southern China 0.14 (IQR: 0.07-0.24) than in norther China 0.10 (IQR: 0.04-0.18). High relative humidity significantly increased subtype interference, with the highest relative risk reaching 20.59 (95% CI: 6.12-69.33) in southern China. Southern China exhibited higher levels of subtype interference, particularly between A/H1N1 and A/H3N2. Higher relative humidity has a more pronounced promoting effect on subtype interference.

Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study

Background

Influenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied.

Method

Here, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons.

Result

Compared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old.

Conclusion

To minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.

The role of viral interference in shaping RSV epidemics following the 2009 H1N1 influenza pandemic

Respiratory syncytial virus (RSV) primarily affects infants, young children, and older adults, with seasonal outbreaks in the United States (US) peaking around December or January. Despite the limited implementation of non-pharmaceutical interventions, disrupted RSV activity was observed in different countries following the 2009 influenza pandemic, suggesting possible viral interference from influenza. Although interactions between the influenza A/H1N1 pandemic virus and RSV have been demonstrated at an individual level, it remains unclear whether the disruption of RSV activity at the population level can be attributed to viral interference. In this work, we first evaluated changes in the timing and intensity of RSV activity across 10 regions of the US in the years following the 2009 influenza pandemic using dynamic time warping. We observed a reduction in RSV activity following the pandemic, which was associated with intensity of influenza activity in the region. We then developed an age-stratified, two-pathogen model to examine various hypotheses regarding viral interference mechanisms. Based on our model estimates, we identified three mechanisms through which influenza infections could interfere with RSV: 1) reducing susceptibility to RSV coinfection; 2) shortening the RSV infectious period in coinfected individuals; and 3) reducing RSV infectivity in coinfection. Our study offers statistical support for the occurrence of atypical RSV seasons following the 2009 influenza pandemic. Our work also offers new insights into the mechanisms of viral interference that contribute to disruptions in RSV epidemics and provides a model-fitting framework that enables the analysis of new surveillance data for studying viral interference at the population level.

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

Multicenter evaluation of the Acaruiter Respiratory Panel for diagnosis of respiratory tract infections in Chinese children

IMPORTANCE

Compared to multiplex PCR assays that are available in the Chinese market, the Acaruiter Respiratory Panel (fluorescent PCR) covers a wider range of pathogens including eight viruses, five bacteria, Mycoplasma pneumoniae and Chlamydia pneumoniae, and has high accuracy and effectiveness in the detection of pathogens. This is the first study to evaluate the performance of the Acaruiter Respiratory Panel. This regent may be a promising assay for comprehensive testing for respiratory pathogens from nasopharyngeal swab specimens in Chinese children.

Transient increased risk of influenza infection following RSV infection in South Africa: findings from the PHIRST study, South Africa, 2016-2018

BACKGROUND

Large-scale prevention of respiratory syncytial virus (RSV) infection may have ecological consequences for co-circulating pathogens, including influenza. We assessed if and for how long RSV infection alters the risk for subsequent influenza infection.

METHODS

We analysed a prospective longitudinal cohort study conducted in South Africa between 2016 and 2018. For participating households, nasopharyngeal samples were taken twice weekly, irrespective of symptoms, across three respiratory virus seasons, and real-time polymerase chain reaction (PCR) was used to identify infection with RSV and/or influenza. We fitted an individual-level hidden Markov transmission model in order to estimate RSV and influenza infection rates and their interdependence.

RESULTS

Of a total of 122,113 samples collected, 1265 (1.0%) were positive for influenza and 1002 (0.8%) positive for RSV, with 15 (0.01%) samples from 12 individuals positive for both influenza and RSV. We observed a 2.25-fold higher incidence of co-infection than expected if assuming infections were unrelated. We estimated that infection with influenza is 2.13 (95% CI 0.97-4.69) times more likely when already infected with, and for a week following, RSV infection, adjusted for age. This equates to 1.4% of influenza infections that may be attributable to RSV in this population. Due to the local seasonality (RSV season precedes the influenza season), we were unable to estimate changes in RSV infection risk following influenza infection.

CONCLUSIONS

We find no evidence to suggest that RSV was associated with a subsequent reduced risk of influenza infection. Instead, we observed an increased risk for influenza infection for a short period after infection. However, the impact on population-level transmission dynamics of this individual-level synergistic effect was not measurable in this setting.

Interactions among acute respiratory viruses in Beijing, Chongqing, Guangzhou, and Shanghai, China, 2009-2019

Background

A viral infection can modify the risk to subsequent viral infections via cross-protective immunity, increased immunopathology, or disease-driven behavioral change. There is limited understanding of virus-virus interactions due to lack of long-term population-level data.

Methods

Our study leverages passive surveillance data of 10 human acute respiratory viruses from Beijing, Chongqing, Guangzhou, and Shanghai collected during 2009 to 2019: influenza A and B viruses; respiratory syncytial virus A and B; human parainfluenza virus (HPIV), adenovirus, metapneumovirus (HMPV), coronavirus, bocavirus (HBoV), and rhinovirus (HRV). We used a multivariate Bayesian hierarchical model to evaluate correlations in monthly prevalence of test-positive samples between virus pairs, adjusting for potential confounders.

Results

Of 101,643 lab-tested patients, 33,650 tested positive for any acute respiratory virus, and 4,113 were co-infected with multiple viruses. After adjusting for intrinsic seasonality, long-term trends and multiple comparisons, Bayesian multivariate modeling found positive correlations for HPIV/HRV in all cities and for HBoV/HRV and HBoV/HMPV in three cities. Models restricted to children further revealed statistically significant associations for another ten pairs in three of the four cities. In contrast, no consistent correlation across cities was found among adults. Most virus-virus interactions exhibited substantial spatial heterogeneity.

Conclusions

There was strong evidence for interactions among common respiratory viruses in highly populated urban settings. Consistent positive interactions across multiple cities were observed in viruses known to typically infect children. Future intervention programs such as development of combination vaccines may consider spatially consistent virus-virus interactions for more effective control.

Deadly interactions: Synergistic manipulations of concurrent pathogen infections potentially enabling future pandemics

Certain mono-infections of influenza viruses and novel coronaviruses, including severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) are significant threats to human health. Concurrent infections by influenza viruses and coronaviruses increases their danger. Influenza viruses have eight manipulations capable of assisting SARS-CoV-2 and other coronaviruses, and several of these manipulations, which are not specific to viruses, can also directly or indirectly boost dangerous secondary bacterial pneumonias. The influenza virus manipulations include: inhibiting transcription factors and cytokine expression; impairing defensive protein expression; increasing RNA viral replication; inhibiting defenses by manipulating cellular sensors and signaling pathways; inhibiting defenses by secreting exosomes; stimulating cholesterol production to increase synthesized virion infectivities; increasing cellular autophagy to assist viral replication; and stimulating glucocorticoid synthesis to suppress innate and adaptive immune defenses by inhibiting cytokine, chemokine, and adhesion molecule production. Teaser: Rapidly spreading multidrug-resistant respiratory bacteria, combined with influenza virus's far-reaching cellular defense manipulations benefiting evolving SARS-CoV-2 or other coronaviruses and/or respiratory bacteria, can enable more severe pandemics or co-pandemics.

Network pharmacology and experimental validation of Maxing Shigan decoction in the treatment of influenza virus-induced ferroptosis

Influenza is an acute viral respiratory infection that has caused high morbidity and mortality worldwide. Influenza A virus (IAV) has been found to activate multiple programmed cell death pathways, including ferroptosis. Ferroptosis is a novel form of programmed cell death in which the accumulation of intracellular iron promotes lipid peroxidation, leading to cell death. However, little is known about how influenza viruses induce ferroptosis in the host cells. In this study, based on network pharmacology, we predicted the mechanism of action of Maxing Shigan decoction (MXSGD) in IAV-induced ferroptosis, and found that this process was related to biological processes, cellular components, molecular function and multiple signaling pathways, where the hypoxia inducible factor-1(HIF-1) signaling pathway plays a significant role. Subsequently, we constructed the mouse lung epithelial (MLE-12) cell model by IAV-infected in vitro cell experiments, and revealed that IAV infection induced cellular ferroptosis that was characterized by mitochondrial damage, increased reactive oxygen species (ROS) release, increased total iron and iron ion contents, decreased expression of ferroptosis marker gene recombinant glutathione peroxidase 4 (GPX4), increased expression of acyl-CoA synthetase long chain family member 4 (ACSL4), and enhanced activation of hypoxia inducible factor-1α (HIF-1α), induced nitric oxide synthase (iNOS) and vascular endothelial growth factor (VEGF) in the HIF-1 signaling pathway. Treatment with MXSGD effectively reduced intracellular viral load, while reducing ROS, total iron and ferrous ion contents, repairing mitochondrial results and inhibiting the expression of cellular ferroptosis and the HIF-1 signaling pathway. Finally, based on animal experiments, it was found that MXSGD effectively alleviated pulmonary congestion, edema and inflammation in IAV-infected mice, and inhibited the expression of ferroptosis-related protein and the HIF-1 signaling pathway in lung tissues.

Increased Fungal Infection Mortality Induced by Concurrent Viral Cellular Manipulations

Certain respiratory fungal pathogen mono-infections can cause high mortality rates. Several viral pathogen mono-infections, including influenza viruses and coronaviruses including SARS-CoV-2, can also cause high mortality rates. Concurrent infections by fungal pathogens and highly manipulative viral pathogens can synergistically interact in the respiratory tract to substantially increase their mortality rates. There are at least five viral manipulations which can assist secondary fungal infections. These viral manipulations include the following: (1) inhibiting transcription factors and cytokine expressions, (2) impairing defensive protein expressions, (3) inhibiting defenses by manipulating cellular sensors and signaling pathways, (4) inhibiting defenses by secreting exosomes, and (5) stimulating glucocorticoid synthesis to suppress immune defenses by inhibiting cytokine, chemokine, and adhesion molecule production. The highest mortality respiratory viral pandemics up to now have had substantially boosted mortalities by inducing secondary bacterial pneumonias. However, numerous animal species besides humans are also carriers of endemic infections by viral and multidrug-resistant fungal pathogens. The vast multi-species scope of endemic infection opportunities make it plausible that the pro-fungal manipulations of a respiratory virus can someday evolve to enable a very high mortality rate viral pandemic inducing multidrug-resistant secondary fungal pathogen infections. Since such pandemics can quickly spread world-wide and outrun existing treatments, it would be worthwhile to develop new antifungal treatments well before such a high mortality event occurs.

Shifting Patterns of Influenza Circulation during the COVID-19 Pandemic, Senegal

Historically low levels of seasonal influenza circulation were reported during the first years of the COVID-19 pandemic and were mainly attributed to implementation of nonpharmaceutical interventions. In tropical regions, influenza's seasonality differs largely, and data on this topic are scarce. We analyzed data from Senegal's sentinel syndromic surveillance network before and after the start of the COVID-19 pandemic to assess changes in influenza circulation. We found that influenza shows year-round circulation in Senegal and has 2 distinct epidemic peaks: during January-March and during the rainy season in August-October. During 2021-2022, the expected January-March influenza peak completely disappeared, corresponding to periods of active SARS-CoV-2 circulation. We noted an unexpected influenza epidemic peak during May-July 2022. The observed reciprocal circulation of SARS-CoV-2 and influenza suggests that factors such as viral interference might be at play and should be further investigated in tropical settings.

Statistical Analysis of Common Respiratory Viruses Reveals the Binary of Virus-Virus Interaction

Respiratory viruses may interfere with each other and affect the epidemic trend of the virus. However, the understanding of the interactions between respiratory viruses at the population level is still very limited. We here conducted a prospective laboratory-based etiological study by enrolling 14,426 patients suffered from acute respiratory infection (ARI) in Beijing, China during 2005 to 2015. All 18 respiratory viruses were simultaneously tested for each nasal and throat swabs collected from enrolled patients using molecular tests. The virus correlations were quantitatively evaluated, and the respiratory viruses could be divided into two panels according to the positive and negative correlations. One included influenza viruses (IFVs) A, B, and respiratory syncytial virus (RSV), while the other included human parainfluenza viruses (HPIVs) 1/3, 2/4, adenovirus (Adv), human metapneumovirus (hMPV), and enterovirus (including rhinovirus, named picoRNA), α and β human coronaviruses (HCoVs). The viruses were positive-correlated in each panel, while negative-correlated between panels. After adjusting the confounding factors by vector autoregressive model, positive interaction between IFV-A and RSV and negative interaction between IFV-A and picoRNA are still be observed. The asynchronous interference of IFV-A significantly delayed the peak of β human coronaviruses epidemic. The binary property of the respiratory virus interactions provides new insights into the viral epidemic dynamics in human population, facilitating the development of infectious disease control and prevention strategies. IMPORTANCE Systematic quantitative assessment of the interactions between different respiratory viruses is pivotal for the prevention of infectious diseases and the development of vaccine strategies. Our data showed stable interactions among respiratory viruses at human population level, which are season irrelevant. Respiratory viruses could be divided into two panels according to their positive and negative correlations. One included influenza virus and respiratory syncytial virus, while the other included other common respiratory viruses. It showed negative correlations between the two panels. The asynchronous interference between influenza virus and β human coronaviruses significantly delayed the peak of β human coronaviruses epidemic. The binary property of the viruses indicated transient immunity induced by one kind of virus would play role on subsequent infection, which provides important data for the development of epidemic surveillance strategies.

Time series analyses based on the joint lagged effect analysis of pollution and meteorological factors of hemorrhagic fever with renal syndrome and the construction of prediction model

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-related zoonotic disease induced by hantavirus. Previous studies have identified the influence of meteorological factors on the onset of HFRS, but few studies have focused on the stratified analysis of the lagged effects and interactions of pollution and meteorological factors on HFRS.

METHODS

We collected meteorological, contaminant and epidemiological data on cases of HFRS in Shenyang from 2005-2019. A seasonal autoregressive integrated moving average (SARIMA) model was used to predict the incidence of HFRS and compared with Holt-Winters three-parameter exponential smoothing model. A distributed lag nonlinear model (DLNM) with a maximum lag period of 16 weeks was applied to assess the lag, stratification and extreme effects of pollution and meteorological factors on HFRS cases, followed by a generalized additive model (GAM) to explore the interaction of SO2 and two other meteorological factors on HFRS cases.

RESULTS

The SARIMA monthly model has better fit and forecasting power than its own quarterly model and the Holt-Winters model, with an optimal model of (1,1,0) (2,1,0)12. Overall, environmental factors including humidity, wind speed and SO2 were correlated with the onset of HFRS and there was a non-linear exposure-lag-response association. Extremely high SO2 increased the risk of HFRS incidence, with the maximum RR values: 2.583 (95%CI:1.145,5.827). Extremely low windy and low SO2 played a significant protective role on HFRS infection, with the minimum RR values: 0.487 (95%CI:0.260,0.912) and 0.577 (95%CI:0.370,0.898), respectively. Interaction indicated that the risk of HFRS infection reached its highest when increasing daily SO2 and decreasing humidity.

CONCLUSIONS

The SARIMA model may help to enhance the forecast of monthly HFRS incidence based on a long-range dataset. Our study had shown that environmental factors such as humidity and SO2 have a delayed effect on the occurrence of HFRS and that the effect of humidity can be influenced by SO2 and wind speed. Public health professionals should take greater care in controlling HFRS in low humidity, low windy conditions and 2-3 days after SO2 levels above 200 μg/m3.

Cost-effectiveness of pharmaceutical strategies to prevent respiratory syncytial virus disease in young children: a decision-support model for use in low-income and middle-income countries

BACKGROUND

Respiratory syncytial virus (RSV) is a leading cause of respiratory disease in young children. A number of mathematical models have been used to assess the cost-effectiveness of RSV prevention strategies, but these have not been designed for ease of use by multidisciplinary teams working in low-income and middle-income countries (LMICs).

METHODS

We describe the UNIVAC decision-support model (a proportionate outcomes static cohort model) and its approach to exploring the potential cost-effectiveness of two RSV prevention strategies: a single-dose maternal vaccine and a single-dose long-lasting monoclonal antibody (mAb) for infants. We identified model input parameters for 133 LMICs using evidence from the literature and selected national datasets. We calculated the potential cost-effectiveness of each RSV prevention strategy (compared to nothing and to each other) over the lifetimes of all children born in the year 2025 and compared our results to a separate model published by PATH. We ran sensitivity and scenario analyses to identify the inputs with the largest influence on the cost-effectiveness results.

RESULTS

Our illustrative results assuming base case input assumptions for maternal vaccination ($3.50 per dose, 69% efficacy, 6 months protection) and infant mAb ($3.50 per dose, 77% efficacy, 5 months protection) showed that both interventions were cost-saving compared to status quo in around one-third of 133 LMICs, and had a cost per DALY averted below 0.5 times the national GDP per capita in the remaining LMICs. UNIVAC generated similar results to a separate model published by PATH. Cost-effectiveness results were most sensitive to changes in the price, efficacy and duration of protection of each strategy, and the rate (and cost) of RSV hospital admissions.

CONCLUSIONS

Forthcoming RSV interventions (maternal vaccines and infant mAbs) are worth serious consideration in LMICs, but there is a good deal of uncertainty around several influential inputs, including intervention price, efficacy, and duration of protection. The UNIVAC decision-support model provides a framework for country teams to build consensus on data inputs, explore scenarios, and strengthen the local ownership and policy-relevance of results.

Respiratory virus circulation during the first year of the COVID-19 pandemic in the Household Influenza Vaccine Evaluation (HIVE) cohort

Background

The annual reappearance of respiratory viruses has been recognized for decades. COVID-19 mitigation measures taken during the pandemic were targeted at respiratory transmission and broadly impacted the burden of acute respiratory illnesses (ARIs).

Methods

We used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort in southeast Michigan to characterize the circulation of respiratory viruses from March 1, 2020, to June 30, 2021, using RT-PCR of respiratory specimens collected at illness onset. Participants were surveyed twice during the study period, and SARS-CoV-2 antibodies were measured in serum by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were compared between the study period and a preceding pre-pandemic period of similar duration.

Results

Overall, 437 participants reported a total of 772 ARIs; 42.6% had respiratory viruses detected. Rhinoviruses were the most frequent virus, but seasonal coronaviruses, excluding SARS-CoV-2, were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Seropositivity for SARS-CoV-2 was 5.3% in summer 2020 and increased to 11.3% in spring 2021. The incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p < 0.001) than the incidence rate from a pre-pandemic comparison period (March 1, 2016, to June 30, 2017).

Conclusions

The burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. Rhinovirus and seasonal coronaviruses continued to circulate even when influenza and SARS-CoV-2 circulation was low.

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.

Global patterns and drivers of influenza decline during the COVID-19 pandemic

OBJECTIVES

The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.

METHODS

The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.

RESULTS

During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The "zero-COVID" countries experienced the greatest decline.

CONCLUSION

Our findings set the stage for interpreting the resurgence of influenza worldwide.

The effects of the COVID-19 pandemic on community respiratory virus activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused substantial global morbidity and deaths, leading governments to turn to non-pharmaceutical interventions to slow down the spread of infection and lessen the burden on health care systems. These policies have evolved over the course of the COVID-19 pandemic, including after the availability of COVID-19 vaccines, with regional and country-level differences in their ongoing use. The COVID-19 pandemic has been associated with changes in respiratory virus infections worldwide, which have differed between virus types. Reductions in respiratory virus infections, including by influenza virus and respiratory syncytial virus, were most notable at the onset of the COVID-19 pandemic and continued in varying degrees through subsequent waves of SARS-CoV-2 infections. The decreases in community infection burden have resulted in reduced hospitalizations and deaths associated with non-SARS-CoV-2 respiratory infections. Respiratory virus evolution relies on the maintaining of a diverse genetic pool, but evidence of genetic bottlenecking brought on by case reduction during the COVID-19 pandemic has resulted in reduced genetic diversity of some respiratory viruses, including influenza virus. By describing the differences in these changes between viral species across different geographies over the course of the COVID-19 pandemic, we may better understand the complex factors involved in community co-circulation of respiratory viruses.

The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants

Introduction

A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures.

Methods

Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out with few cases.

Results

We find that, if cross-reactive immunity is complete (i.e. someone infected by the previously circulating virus is not susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population.

Discussion

Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses against novel SARS-CoV-2 variants is an essential component of novel variant risk assessments.

Vaccination against Community-Acquired Pneumonia in Spanish Adults: Practical Recommendations by the NeumoExperts Prevention Group

In the adult population, community-acquired pneumonia (CAP) is a serious disease that is responsible for high morbidity and mortality rates, being frequently associated with multidrug resistant pathogens. The aim of this review is to update a practical immunization prevention guideline for CAP in Spain caused by prevalent respiratory pathogens, based on the available scientific evidence through extensive bibliographic review and expert opinion. The emergence of COVID-19 as an additional etiological cause of CAP, together with the rapid changes in the availability of vaccines and recommendations against SARS-CoV-2, justifies the need for an update. In addition, new conjugate vaccines of broader spectrum against pneumococcus, existing vaccines targeting influenza and pertussis or upcoming vaccines against respiratory syncytial virus (RSV) will be very useful prophylactic tools to diminish the burden of CAP and all of its derived complications. In this manuscript, we provide practical recommendations for adult vaccination against the pathogens mentioned above, including their contribution against antibiotic resistance. This guide is intended for the individual perspective of protection and not for vaccination policies, as we do not pretend to interfere with the official recommendations of any country. The use of vaccines is a realistic approach to fight these infections and ameliorate the impact of antimicrobial resistance. All of the recently available scientific evidence included in this review gives support to the indications established in this practical guide to reinforce the dissemination and implementation of these recommendations in routine clinical practice.

Mitigating co-circulation of seasonal influenza and COVID-19 pandemic in the presence of vaccination: A mathematical modeling approach

The co-circulation of two respiratory infections with similar symptoms in a population can significantly overburden a healthcare system by slowing the testing and treatment. The persistent emergence of contagious variants of SARS-CoV-2, along with imperfect vaccines and their waning protections, have increased the likelihood of new COVID-19 outbreaks taking place during a typical flu season. Here, we developed a mathematical model for the co-circulation dynamics of COVID-19 and influenza, under different scenarios of influenza vaccine coverage, COVID-19 vaccine booster coverage and efficacy, and testing capacity. We investigated the required minimal and optimal coverage of COVID-19 booster (third) and fourth doses, in conjunction with the influenza vaccine, to avoid the coincidence of infection peaks for both diseases in a single season. We show that the testing delay brought on by the high number of influenza cases impacts the dynamics of influenza and COVID-19 transmission. The earlier the peak of the flu season and the greater the number of infections with flu-like symptoms, the greater the risk of flu transmission, which slows down COVID-19 testing, resulting in the delay of complete isolation of patients with COVID-19 who have not been isolated before the clinical presentation of symptoms and have been continuing their normal daily activities. Furthermore, our simulations stress the importance of vaccine uptake for preventing infection, severe illness, and hospitalization at the individual level and for disease outbreak control at the population level to avoid putting strain on already weak and overwhelmed healthcare systems. As such, ensuring optimal vaccine coverage for COVID-19 and influenza to reduce the burden of these infections is paramount. We showed that by keeping the influenza vaccine coverage about 35% and increasing the coverage of booster or fourth dose of COVID-19 not only reduces the infections with COVID-19 but also can delay its peak time. If the influenza vaccine coverage is increased to 55%, unexpectedly, it increases the peak size of influenza infections slightly, while it reduces the peak size of COVID-19 as well as significantly delays the peaks of both of these diseases. Mask-wearing coupled with a moderate increase in the vaccine uptake may mitigate COVID-19 and prevent an influenza outbreak.

Respiratory Virus Circulation during the First Year of the COVID-19 Pandemic in the Household Influenza Vaccine Evaluation (HIVE) Cohort

Background

The annual reappearance of respiratory viruses has been recognized for decades. The onset of the COVID-19 pandemic altered typical respiratory virus transmission patterns. COVID-19 mitigation measures taken during the pandemic were targeted at SARS-CoV-2 respiratory transmission and thus broadly impacted the burden of acute respiratory illnesses (ARIs), in general.

Methods

We used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort of households in southeast Michigan to characterize mitigation strategy adherence, respiratory illness burden, and the circulation of 15 respiratory viruses during the COVID-19 pandemic determined by RT-PCR of respiratory specimens collected at illness onset. Study participants were surveyed twice during the study period (March 1, 2020, to June 30, 2021), and serologic specimens were collected for antibody measurement by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were calculated and compared using incidence rate ratios for the study period and a pre-pandemic period of similar length.

Results

Overall, 437 participants reported a total of 772 ARIs and 329 specimens (42.6%) had respiratory viruses detected. Rhinoviruses were the most frequently detected organism, but seasonal coronaviruses-excluding SARS-CoV-2-were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Study participants were more adherent to mitigation measures in the first survey compared with the second survey. Supplemental serology surveillance identified 5.3% seropositivity for SARS-CoV-2 in summer 2020; 3.0% between fall 2020 and winter 2021; and 11.3% in spring 2021. Compared to a pre-pandemic period of similar length, the incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p<0.001) than the incidence rate from March 1, 2016, to June 30, 2017.

Conclusions

The burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. It is notable, however, that rhinovirus and seasonal coronaviruses continued to circulate even as influenza and SARS-CoV-2 circulation was low.

Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria

Detection of foodborne pathogens at an early stage is very important to control food quality and improve medical response. Rapid detection of foodborne pathogens with high sensitivity and specificity is becoming an urgent requirement in health safety, medical diagnostics, environmental safety, and controlling food quality. Despite the existing bacterial detection methods being reliable and widely used, these methods are time-consuming, expensive, and cumbersome. Therefore, researchers are trying to find new methods by integrating spectroscopy techniques with artificial intelligence and advanced materials. Within this progress report, advances in the detection of foodborne pathogens using spectroscopy techniques are discussed. This paper presents an overview of the progress and application of spectroscopy techniques for the detection of foodborne pathogens, particularly new trends in the past few years, including surface-enhanced Raman spectroscopy, surface plasmon resonance, fluorescence spectroscopy, multiangle laser light scattering, and imaging analysis. In addition, the applications of artificial intelligence, microfluidics, smartphone-based techniques, and advanced materials related to spectroscopy for the detection of bacterial pathogens are discussed. Finally, we conclude and discuss possible research prospects in aspects of spectroscopy techniques for the identification and classification of pathogens.

Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths

Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.

Interactions Between Severe Acute Respiratory Syndrome Coronavirus 2 Replication and Major Respiratory Viruses in Human Nasal Epithelium

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with extensive nonpharmacological interventions, have profoundly altered the epidemiology of major respiratory viruses. Some studies have described virus-virus interactions, particularly manifested by viral interference mechanisms at different scales. However, our knowledge of the interactions between SARS-CoV-2 and other respiratory viruses remains incomplete. Here, we studied the interactions between SARS-CoV-2 and several respiratory viruses (influenza, respiratory syncytial virus, human metapneumovirus, and human rhinovirus) in a reconstituted human epithelial airway model, exploring different scenarios affecting the sequence and timing of coinfections. We show that the virus type and sequence of infections are key factors in virus-virus interactions, the primary infection having a determinant role in the immune response to the secondary infection.

Epidemiologic and clinical characteristics of human bocavirus infection in children hospitalized for acute respiratory tract infection in Qingdao, China

Persistent infection and prolonged shedding of human bocavirus 1 (HBoV1) in children have been reported, and the role of HBoV1 as a sole causative pathogen in acute respiratory infection (ARI) is yet to be established. While the reported prevalence of HBoV infection varies due to different detection methods and sampling criteria, determining the viral and bacterial etiology of HBoV infection using multiplex real-time PCR is yet to be reported. Herein, we aimed to further explore the pathogenicity of HBoV in patients with ARI by screening the viral and bacterial infections in children with ARI in Qingdao and comparing the epidemiological, clinical characteristics, and etiological results. Human bocavirus was identified in 28.1% of the samples, and further sequencing analysis of the detected HBoV confirmed 96.4% as HBoV1. The rate of HBoV as a single viral infection was 75%, and the rate of coinfection with bacteria was 66.1%, suggesting the need for continued monitoring of HBoV in children with ARIs. Clinical characterization suggested that HBoV infection may affect the function of organs, such as the liver, kidney, and heart, and the blood acid–base balance. Additionally, it is essential to promote awareness about the importance of disinfection and sterilization of the hospital environment and standardizing operations. The interactions between HBoV and other pathogens remain to be investigated in further detail in the future.

How influenza vaccination and virus interference may impact combined influenza-coronavirus disease burden

Demand for influenza vaccine rose as countries prepared for the second COVID-19 wave over the winter months of 2020-2021. High coverage of the influenza vaccine can significantly reduce morbidity and mortality of the burden of influenza. Natural influenza infection creates short-term non-specific immunity against respiratory viruses (virus interference). We model two viral diseases, both of the SEIR type, to investigate whether the influenza vaccine increases the combined disease burden of influenza and COVID-19 in a dual outbreak. We show that the combined disease burden’s behavior depends on virus interference factors and the proportion of the population vaccinated against influenza. Our results indicate that influenza vaccination only lowers the overall disease burden when net virus interference is relatively low.

Interactions among common non-SARS-CoV-2 respiratory viruses and influence of the COVID-19 pandemic on their circulation in New York City

BACKGROUND

Non-pharmaceutical interventions (NPIs) and voluntary behavioral changes during the COVID-19 pandemic have influenced the circulation of non-SARS-CoV-2 respiratory infections. We aimed to examine interactions among common non-SARS-CoV-2 respiratory virus and further estimate the impact of the COVID-19 pandemic on these viruses.

METHODS

We analyzed incidence data for seven groups of respiratory viruses in New York City (NYC) during October 2015 to May 2021 (i.e., before and during the COVID-19 pandemic). We first used elastic net regression to identify potential virus interactions and further examined the robustness of the found interactions by comparing the performance of Seasonal Auto Regressive Integrated Moving Average (SARIMA) models with and without the interactions. We then used the models to compute counterfactual estimates of cumulative incidence and estimate the reduction during the COVID-19 pandemic period from March 2020 to May 2021, for each virus.

RESULTS

We identified potential interactions for three endemic human coronaviruses (CoV-NL63, CoV-HKU, and CoV-OC43), parainfluenza (PIV)-1, rhinovirus, and respiratory syncytial virus (RSV). We found significant reductions (by ~70-90%) in cumulative incidence of CoV-OC43, CoV-229E, human metapneumovirus, PIV-2, PIV-4, RSV, and influenza virus during the COVID-19 pandemic. In contrast, the circulation of adenovirus and rhinovirus was less affected.

CONCLUSIONS

Circulation of several respiratory viruses has been low during the COVID-19 pandemic, which may lead to increased population susceptibility. It is thus important to enhance monitoring of these viruses and promptly enact measures to mitigate their health impacts (e.g., influenza vaccination campaign and hospital infection prevention) as societies resume normal activities.

Evidence for influenza and RSV interaction from 10 years of enhanced surveillance in Nha Trang, Vietnam, a modelling study

Influenza and Respiratory Syncytial Virus (RSV) interact within their host posing the concern for impacts on heterologous viruses following vaccination. We aimed to estimate the population level impact of their interaction. We developed a dynamic age-stratified two-pathogen mathematical model that includes pathogen interaction through competition for infection and enhanced severity of dual infections. We used parallel tempering to fit its parameters to 11 years of enhanced hospital-based surveillance for acute respiratory illnesses (ARI) in children under 5 years old in Nha Trang, Vietnam. The data supported either a 41% (95%CrI: 36–54) reduction in susceptibility following infection and for 10.0 days (95%CrI 7.1–12.8) thereafter, or no change in susceptibility following infection. We estimate that co-infection increased the probability for an infection in <2y old children to be reported 7.2 fold (95%CrI 5.0–11.4); or 16.6 fold (95%CrI 14.5–18.4) in the moderate or low interaction scenarios. Absence of either pathogen was not to the detriment of the other. We find stronger evidence for severity enhancing than for acquisition limiting interaction. In this setting vaccination against either pathogen is unlikely to have a major detrimental effect on the burden of disease caused by the other.

Influenza and Respiratory Syncytial Virus (RSV) cause large burdens of disease. Instead of acting independently, there may be short term cross-protection between them. The evidence of this to date comes from ecological studies which are unable to test the mechanism, or biological studies that are unable to determine the population level impacts of such cross-protection. We create a mathematical model that simulates the circulation of these two viruses, and allows for cross-protection between them. We then fit this model to hospital reported cases of confirmed infection from Nha Trang, Vietnam in order to estimate whether any cross-protection exists in this setting. We show that there are two possibilities—either no interaction or moderate interaction that can result in the observed circulation patterns. However, we further show that co-infection results in an increased reporting rate, presumably due to increased severity.

Analysis of severe human adenovirus infection outbreak in Guangdong Province, southern China in 2019

During 2018-2019, a severe human adenovirus (HAdV) infection outbreak occurred in southern China. Here, we screened 18 respiratory pathogens in 1704 children (≤ 14 years old) hospitalized with acute respiratory illness in Guangzhou, China, in 2019. In total, 151 patients had positive HAdV test results; 34.4% (52/151) of them exhibited severe illness. HAdV infection occurred throughout the year, with a peak in summer. The median patient age was 3.0 (interquartile range: 1.1-5.0) years. Patients with severe HAdV infection exhibited increases in 12 clinical indexes (P ​≤ ​0.019) and decreases in four indexes (P ​≤ ​0.007), compared with patients exhibiting non-severe infection. No significant differences were found in age or sex distribution according to HAdV infection severity (P ​> ​0.05); however, the distributions of comorbid disease and HAdV co-infection differed according to HAdV infection severity (P ​< ​0.05). The main epidemic types were HAdV-3 (47.0%, 71/151) and HAdV-7 (46.4%, 70/151). However, the severe illness rate was significantly higher in patients with HAdV-7 (51.4%) than in patients with HAdV-3 (19.7%) and other types of HAdV (20%) (P ​< ​0.001). Sequencing analysis of genomes/capsid genes of 13 HAdV-7 isolates revealed high similarity to previous Chinese isolates. A representative HAdV-7 isolate exhibited a similar proliferation curve to the curve described for the epidemic HAdV-3 strain Guangzhou01 (accession no. DQ099432) (P ​> ​0.05); the HAdV-7 isolate exhibited stronger virulence and infectivity, compared with HAdV-3 (P ​< ​0.001). Overall, comorbid disease, HAdV co-infection, and high virulence and infectivity of HAdV-7 were critical risk factors for severe HAdV infection; these data can facilitate treatment, control, and prevention of HAdV infection.

Combinational Recommendation of Vaccinations, Mask-Wearing, and Home-Quarantine to Control Influenza in Megacities: An Agent-Based Modeling Study With Large-Scale Trajectory Data

The outbreak of COVID-19 stimulated a new round of discussion on how to deal with respiratory infectious diseases. Influenza viruses have led to several pandemics worldwide. The spatiotemporal characteristics of influenza transmission in modern cities, especially megacities, are not well-known, which increases the difficulty of influenza prevention and control for populous urban areas. For a long time, influenza prevention and control measures have focused on vaccination of the elderly and children, and school closure. Since the outbreak of COVID-19, the public's awareness of measures such as vaccinations, mask-wearing, and home-quarantine has generally increased in some regions of the world. To control the influenza epidemic and reduce the proportion of infected people with high mortality, the combination of these three measures needs quantitative evaluation based on the spatiotemporal transmission characteristics of influenza in megacities. Given that the agent-based model with both demographic attributes and fine-grained mobility is a key planning tool in deploying intervention strategies, this study proposes a spatially explicit agent-based influenza model for assessing and recommending the combinations of influenza control measures. This study considers Shenzhen city, China as the research area. First, a spatially explicit agent-based influenza transmission model was developed by integrating large-scale individual trajectory data and human response behavior. Then, the model was evaluated across multiple intra-urban spatial scales based on confirmed influenza cases. Finally, the model was used to evaluate the combined effects of the three interventions (V: vaccinations, M: mask-wearing, and Q: home-quarantining) under different compliance rates, and their optimal combinations for given control objectives were recommended. This study reveals that adults were a high-risk population with a low reporting rate, and children formed the lowest infected proportion and had the highest reporting rate in Shenzhen. In addition, this study systematically recommended different combinations of vaccinations, mask-wearing, and home-quarantine with different compliance rates for different control objectives to deal with the influenza epidemic. For example, the "V45%-M60%-Q20%" strategy can maintain the infection percentage below 5%, while the "V20%-M60%-Q20%" strategy can maintain the infection percentage below 15%. The model and policy recommendations from this study provide a tool and intervention reference for influenza epidemic management in the post-COVID-19 era.

Virus-virus interactions of febrile respiratory syndrome among patients in China based on surveillance data from February 2011 to December 2020

BACKGROUND

The burden of acute respiratory infections is still considerable, and virus-virus interactions may affect their epidemics, but previous evidence is inconclusive.

OBJECTIVE

To quantitatively investigate the interactions among respiratory viruses at both the population and individual levels.

METHODS

Cases tested for influenza virus (IV), respiratory syncytial virus (RSV), human parainfluenza virus (PIV), human Adenovirus (AdV), human coronavirus (CoV), human bocavirus (BoV) and rhinoviruses (RV) were collected from the pathogen surveillance for febrile respiratory syndrome (FRS) in China from February 2011 to December 2020. We used spearman's rank correlation coefficients and binary logistic regression models to analyze the interactions between any two of the viruses at the population and individual levels, respectively.

RESULTS

Among 120,237 cases, 4.5% were co-infected with two or more viruses. Correlation coefficients showed 7 virus pairs were positively correlated, namely: IV and RSV, PIV and AdV, PIV and CoV, PIV and BoV, PIV and RV, AdV and BoV, CoV and RV. Regression models showed except for the negative interaction between IV and RV (OR=0.70, 95%CI: 0.61-0.81), all other virus pairs had positive interactions.

CONCLUSION

Most of the respiratory viruses interact positively, while IV and RV interact negatively. This article is protected by copyright. All rights reserved.

Distinguishing viruses responsible for influenza-like illness

The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a fever of 100 degrees Fahrenheit, a cough, and/or a sore throat. In the United States alone, ILI impacts 9-49 million people every year. While tracking ILI as a single clinical syndrome is informative in many respects, the underlying viruses differ in parameters and outbreak properties. Most existing models treat either a single respiratory virus or ILI as a whole. However, there is a need for models capable of comparing several individual viruses that cause respiratory illness, including ILI. To address this need, here we present a flexible model and simulations of epidemics for influenza, RSV, rhinovirus, seasonal coronavirus, adenovirus, and SARS/MERS, parameterized by a systematic literature review and accompanied by a global sensitivity analysis. We find that for these biological causes of ILI, their parameter values, timing, prevalence, and proportional contributions differ substantially. These results demonstrate that distinguishing the viruses that cause ILI will be an important aspect of future work on diagnostics, mitigation, modeling, and preparation for future pandemics.

System Complexity in Influenza Infection and Vaccination: Effects upon Excess Winter Mortality

Unexpected outcomes are usually associated with interventions in complex systems. Excess winter mortality (EWM) is a measure of the net effect of all competing forces operating each winter, including influenza(s) and non-influenza pathogens. In this study over 2400 data points from 97 countries are used to look at the net effect of influenza vaccination rates in the elderly aged 65+ against excess winter mortality (EWM) each year from the winter of 1980/81 through to 2019/20. The observed international net effect of influenza vaccination ranges from a 7.8% reduction in EWM estimated at 100% elderly vaccination for the winter of 1989/90 down to a 9.3% increase in EWM for the winter of 2018/19. The average was only a 0.3% reduction in EWM for a 100% vaccinated elderly population. Such outcomes do not contradict the known protective effect of influenza vaccination against influenza mortality per se—they merely indicate that multiple complex interactions lie behind the observed net effect against all-causes (including all pathogen causes) of winter mortality. This range from net benefit to net disbenefit is proposed to arise from system complexity which includes environmental conditions (weather, solar cycles), the antigenic distance between constantly emerging circulating influenza clades and the influenza vaccine makeup, vaccination timing, pathogen interference, and human immune diversity (including individual history of host-virus, host-antigen interactions and immunosenescence) all interacting to give the observed outcomes each year. We propose that a narrow focus on influenza vaccine effectiveness misses the far wider complexity of winter mortality. Influenza vaccines may need to be formulated in different ways, and perhaps administered over a shorter timeframe to avoid the unanticipated adverse net outcomes seen in around 40% of years.

Epidemiological Consequences of Viral Interference: A Mathematical Modeling Study of Two Interacting Viruses

Some viruses have the ability to block or suppress growth of other viruses when simultaneously present in the same host. This type of viral interference or viral block has been suggested as a potential interaction between some respiratory viruses including SARS-CoV-2 and other co-circulating respiratory viruses. We explore how one virus' ability to block infection with another within a single host affects spread of the viruses within a susceptible population using a compartmental epidemiological model. We find that population-level effect of viral block is a decrease in the number of people infected with the suppressed virus. This effect is most pronounced when the viruses have similar epidemiological parameters. We use the model to simulate co-circulating epidemics of SARS-CoV-2 and influenza, respiratory syncytial virus (RSV), and rhinovirus, finding that co-circulation of SARS-CoV-2 and RSV causes the most suppression of SARS-CoV-2. Paradoxically, co-circulation of SARS-CoV-2 and influenza or rhinovirus results in almost no change in the SARS-CoV-2 epidemic, but causes a shift in the timing of the influenza and rhinovirus epidemics.

Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data

Background

Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates.

Methods

We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel.

Results

21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load.

Conclusions

Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.

Bacterial coinfection in influenza pneumonia: Rates, pathogens, and outcomes

BACKGROUND

Evidence from pandemics suggests that influenza is often associated with bacterial coinfection. Among patients hospitalized for influenza pneumonia, we report the rate of coinfection and distribution of pathogens, and we compare outcomes of patients with and without bacterial coinfection.

METHODS

We included adults admitted with community-acquired pneumonia (CAP) and tested for influenza from 2010 to 2015 at 179 US hospitals participating in the Premier database. Pneumonia was identified using an International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) algorithm. We used multiple logistic and gamma-generalized linear mixed models to assess the relationships between coinfection and inpatient mortality, intensive care unit (ICU) admission, length of stay, and cost.

RESULTS

Among 38,665 patients hospitalized with CAP and tested for influenza, 4,313 (11.2%) were positive. In the first 3 hospital days, patients with influenza were less likely than those without to have a positive culture (10.3% vs 16.2%; P < .001), and cultures were more likely to contain Staphylococcus aureus (34.2% vs 28.2%; P = .007) and less likely to contain Streptococcus pneumoniae (24.9% vs 31.0%; P = .008). Of S. aureus isolates, 42.8% were methicillin resistant among influenza patients versus 53.2% among those without influenza (P = .01). After hospital day 3, pathogens for both groups were similar. Bacterial coinfection was associated with increased odds of in-hospital mortality (aOR, 3.00; 95% CI, 2.17-4.16), late ICU transfer (aOR, 2.83; 95% CI, 1.98-4.04), and higher cost (risk-adjusted mean multiplier, 1.77; 95% CI, 1.59-1.96).

CONCLUSIONS

In a large US inpatient sample hospitalized with influenza and CAP, S. aureus was the most frequent cause of bacterial coinfection. Coinfection was associated with worse outcomes and higher costs.

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

BACKGROUND

Circulation of seasonal non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory viruses with syndromic overlap during the coronavirus disease 2019 (COVID-19) pandemic may alter the quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures.

METHODS

Using a multipathogen susceptible-exposed-infectious-recovered (SEIR) transmission model formalizing cocirculation of SARS-CoV-2 and another respiratory virus, we assessed how an outbreak of secondary virus may affect 2 COVID-19 surveillance indicators: testing demand and positivity. Using simulation, we assessed to what extent the use of multiplex polymerase chain reaction tests on a subsample of symptomatic individuals can help correct the observed SARS-CoV-2 percentage positivity and improve surveillance quality.

RESULTS

We find that a non-SARS-CoV-2 epidemic strongly increases SARS-CoV-2 daily testing demand and artificially reduces the observed SARS-CoV-2 percentage positivity for the duration of the outbreak. We estimate that performing 1 multiplex test for every 1000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percentage positivity.

CONCLUSIONS

This study showed that cocirculating respiratory viruses can distort SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex polymerase chain reaction tests, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.

The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2

There is growing experimental evidence that many respiratory viruses-including influenza and SARS-CoV-2-can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio-defined as the ratio of co-infection prevalence to the product of single-infection prevalences-should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza-SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection-such as a high reproduction number or a short infectious period-that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.

Opposite Outcomes of the Within-Host Competition between High- and Low-Pathogenic H5N8 Avian Influenza Viruses in Chickens Compared to Ducks

Highly pathogenic avian influenza viruses (HPAIV) emerge from low-pathogenic avian influenza viruses (LPAIV) through the introduction of basic amino acids at the hemagglutinin (HA) cleavage site. Following viral evolution, the newly formed HPAIV likely represents a minority variant within the index host, predominantly infected with the LPAIV precursor. Using reverse genetics-engineered H5N8 viruses differing solely at the HA cleavage, we tested the hypothesis that the interaction between the minority HPAIV and the majority LPAIV could modulate the risk of HPAIV emergence and that the nature of the interaction could depend on the host species. In chickens, we observed that the H5N8LP increased H5N8HP replication and pathogenesis. In contrast, the H5N8LP antagonized H5N8HP replication and pathogenesis in ducks. Ducks mounted a more potent antiviral innate immune response than chickens against the H5N8LP, which correlated with H5N8HP inhibition. These data provide experimental evidence that HPAIV may be more likely to emerge in chickens than in ducks and underscore the importance of within-host viral variant interactions in viral evolution. IMPORTANCE Highly pathogenic avian influenza viruses represent a threat to poultry production systems and to human health because of their impact on food security and because of their zoonotic potential. It is therefore crucial to better understand how these viruses emerge. Using a within-host competition model between high- and low-pathogenic avian influenza viruses, we provide evidence that highly pathogenic avian influenza viruses could be more likely to emerge in chickens than in ducks. These results have important implications for highly pathogenic avian influenza virus emergence prevention, and they underscore the importance of within-host viral variant interactions in virus evolution.