Report on influenza A and B viruses: their coinfection in a Saudi leukemia patient

Viral Coinfections

In nature, viral coinfection is as widespread as viral infection alone. Viral coinfections often cause altered viral pathogenicity, disrupted host defense, and mixed-up clinical symptoms, all of which result in more difficult diagnosis and treatment of a disease. There are three major virus-virus interactions in coinfection cases: viral interference, viral synergy, and viral noninterference. We analyzed virus-virus interactions in both aspects of viruses and hosts and elucidated their possible mechanisms. Finally, we summarized the protocol of viral coinfection studies and key points in the process of virus separation and purification.

Incidence, Disease Severity, and Follow-Up of Influenza A/A, A/B, and B/B Virus Dual Infections in Children: A Hospital-Based Digital Surveillance Program

Influenza virus (IV) coinfection, i.e., simultaneous infection with IV and other viruses, is a common occurrence in humans. However, little is known about the incidence and clinical impact of coinfection with two different IV subtypes or lineages (“dual infections”). We report the incidence, standardized disease severity, and follow-up of IV dual infections from a hospital-based digital surveillance cohort, comprising 6073 pediatric patients fulfilling pre-defined criteria of influenza-like illness in Berlin, Germany. All patients were tested for IV A/B by PCR, including subtypes/lineages. We assessed all patients at the bedside using the mobile ViVI ScoreApp, providing a validated disease severity score in real-time. IV-positive patients underwent follow-up assessments until resolution of symptoms. Overall, IV dual infections were rare (4/6073 cases; 0.07%, incidence 12/100,000 per year) but showed unusual and/or prolonged clinical presentations with slightly above-average disease severity. We observed viral rebound, serial infection, and B/Yamagata-B/Victoria dual infection. Digital tools, used for instant clinical assessments at the bedside, combined with baseline/follow-up virologic investigation, help identify coinfections in cases of prolonged and/or complicated course of illness. Infection with one IV does not necessarily prevent consecutive or simultaneous (co-/dual) infection, highlighting the importance of multivalent influenza vaccination and enhanced digital clinical and virological surveillance.

The Epidemiological Pattern and Co-infection of Influenza A and B by Surveillance Network From 2009 to 2014 in Anhui Province, China

Influenza-like illness (ILI) is one of the most important public health problems globally, causing an enormous disease burden. Influenza infections are the most common cause of ILI. Bacterial and virus co-infection is common yet the data of co-infection with influenza A and B viruses are scarce. To identify the epidemiological patterns of and co-infection of influenza A and B in Anhui province, China, we analyzed the surveillance data of 5 years from 2009 to 2014 collected by the Chinese National influenzas network. The results showed that the weekly ratio of ILI was 3.96 ± 1.9% (95% CI 3.73–4.2%) in outpatients and the highest affected population was children under 5 years old. The epidemic of influenza viruses was highest during 2009–2010. For the other 4 surveillance years, school-aged people (5–14 years) were the most highly affected population. Influenza B and H3N2 viruses were more prevalent than H1N1pdm09 virus after 2010. In addition, a significant co-circulation of influenza A (H1N1pdm09 and H3N2) and influenza B virus was detected with 0.057% PCR positive rate during 2009–2014 in Eastern China, yet isolated only in pediatric patients. Our data reveals school-aged population would be the main vulnerable population and a distinct seasonality for influenza. In addition, the co-infection of influenza A and B were found in Anhui Province, China. Ongoing surveillance is critical to understand the seasonality variation and make evidence-based vaccination recommendations. Information on the epidemiological patterns and co-infections of influenza A and B can help us to implement different strategies for selecting vaccine formulations and monitoring new emerging influenza strains. In addition, the identification of the susceptible population can help us to develop more precise protection measures.

Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting

Background

Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar.

Results

Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A.

Conclusion

In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06526-5.

Molecular Detection of Influenza A and B Viruses in Four Consecutive Influenza Seasons 2015-16 to 2018-19 in a Tertiary Center in Western Saudi Arabia

Introduction: Influenza infection poses a significant public health threat. The core for disease prevention and control relies on strengthened surveillance activities, particularly in Saudi Arabia, the country that hosts the largest annual mass gathering event worldwide. This study aimed to assess the molecular and seasonal pattern of influenza virus subtypes in western Saudi Arabia to inform policy decisions on influenza vaccine.

Methods: This cross-sectional study was conducted at King Abdulaziz Medical City, western Saudi Arabia. Medical records and surveillance database of laboratory-confirmed influenza cases were reviewed from October 2015 to 2019. A panel of real-time polymerase chain reactions was performed to detect influenza A and B. Extracted RNA from a subset of positive samples was used to determine influenza A subtypes and influenza B lineages.

Results: This study included a total of 1928 patients with laboratory-confirmed influenza infections. Influenza peaks were observed in October each season, with variant predominant strains. Influenza virus subtypes co-circulate with no reports of co-infection. Influenza A(H3N2) was reported in 42% of the cases, then influenza B (30.7%) and influenza A(H1N1)pdm09 (27.3%). Healthcare workers represented 9.4% of the cases. One-third of the cases (30.4%) were admitted to the hospital with a median admission duration of 4 days. The influenza B viruses were subtyped in 218 cases. Victoria lineage was predominant (64.1%) in 2015 and 2016; however, Yamagata was predominant in the next two consecutive seasons (94.4% and 85.4%, respectively).

Conclusion: The burden due to influenza B may be underestimated with an observed vaccine mismatch. A quadrivalent influenza vaccine is recommended to reduce the health impact associated with influenza B infections. Molecular surveillance of the influenza viruses should be enhanced continuously for a better understanding of the influenza activity and assessment of vaccine effectiveness.

A Mathematical Modeling Study: Assessing Impact of Mismatch Between Influenza Vaccine Strains and Circulating Strains in Hajj

The influenza virus causes severe respiratory illnesses and deaths worldwide every year. It spreads quickly in an overcrowded area like the annual Hajj pilgrimage in Saudi Arabia. Vaccination is the primary strategy for protection against influenza. Due to the occurrence of antigenic shift and drift of the influenza virus, a mismatch between vaccine strains and circulating strains of influenza may occur. The objective of this study is to assess the impact of mismatch between vaccine strains and circulating strains during Hajj, which brings together individuals from all over the globe. To this end, we develop deterministic mathematical models of influenza with different populations and strains from the northern and southern hemispheres. Our results show that the existence and duration of an influenza outbreak during Hajj depend on vaccine efficacy. In this concern, we discuss four scenarios: vaccine strains for both groups match/mismatch circulating strains, and vaccine strains match their target strains and mismatch the other strains. Further, there is a scenario where a novel pandemic strain arises. Our results show that as long as the influenza vaccines match their target strains, there will be no outbreak of strain H1N1 and only a small outbreak of strain H3N2. Mismatching for non-target strains causes about 10,000 new H3N2 cases, and mismatching for both strains causes about 2,000 more new H1N1 cases and 6,000 additional H3N2 cases during Hajj. Complete mismatch in a pandemic scenario may infect over 342,000 additional pilgrims (13.75%) and cause more cases in their home countries.

A six-plex droplet digital RT-PCR assay for seasonal influenza virus typing, subtyping, and lineage determination

BACKGROUND

There are two influenza A subtypes (H1 and H3) and two influenza B lineages (Victoria and Yamagata) that currently co-circulate in humans. In this study, we report the development of a six-plex droplet digital RT-PCR (ddRT-PCR) assay that can detect HA and M segments of influenza A (H1, H3, and M) and influenza B (Yamagata HA, Victoria HA, and M) viruses in a single reaction mixture. It can simultaneously detect six different nucleic acid targets in a ddRT-PCR platform.

METHODS

The six-plex ddRT-PCR used in this study is an amplitude-based multiplex assay. The analytical performance of the assay was evaluated. Correlation with standard qRT-PCR methodology was assessed using 55 clinical samples.

RESULTS

The assay has a wide dynamic range, and it has good reproducibility within and between runs. The limit of quantification of each target in this assay ranged from 15 copies/reaction for influenza B Victoria M gene to 45 copies/reaction for influenza B Yamagata M gene. In addition, this assay can accurately quantify each of these targets in samples containing viral RNAs from two different viruses that were mixed in a highly skewed ratio. Typing, subtyping, and lineage differentiation data of 55 tested clinical respiratory specimens were found to be identical to those deduced from standard monoplex qRT-PCR assays.

CONCLUSIONS

The six-plex ddRT-PCR test was demonstrated to be highly suitable for detecting dual influenza infection cases. This assay is expected to be a useful diagnostic tool for clinical and research use.

Dual and Triple Infections With Influenza A and B Viruses: A Case-Control Study in Southern Brazil

Influenza surveillance is important for disease control and should consider possible coinfection with different viruses, which can be associated with disease severity. This study analyzed 34 459 patients with respiratory infection from 2009 to 2018, of whom 8011 were positive for influenza A virus (IAV) or influenza B virus (IBV). We found 18 cases of dual influenza virus infection, including coinfection with 2009 pandemic influenza A(H1N1) virus (A[H1N1]pdm09) and influenza A(H3N2) virus (1 case), A(H1N1)pdm09 and IBV (6 cases), A(H3N2) and IBV (8 cases), and nonsubtyped IAV and IBV (3 cases); and 1 case of triple infection with A(H3N2), A(H1N1)pdm09, and IBV. Compared with 76 monoinfected patients, coinfection was significantly associated with cardiopathy and death. Besides demographic characteristics and clinical symptoms, we assessed vaccination status, antiviral treatment, timeliness of antiviral use, hospitalization, and intensive care unit admission, but no significant differences were found between coinfected and monoinfected cases. Our findings indicate that influenza virus coinfection occurs more often than previously reported and that it can lead to a worse disease outcome.

Epidemiology of respiratory viruses in Saudi Arabia: toward a complete picture

Acute lower respiratory tract infection is a major health problem that affects more than 15% of the total population of Saudi Arabia each year. Epidemiological studies conducted over the last three decades have indicated that viruses are responsible for the majority of these infections. The epidemiology of respiratory viruses in Saudi Arabia is proposed to be affected mainly by the presence and mobility of large numbers of foreign workers and the gathering of millions of Muslims in Mecca during the Hajj and Umrah seasons. Knowledge concerning the epidemiology, circulation pattern, and evolutionary kinetics of respiratory viruses in Saudi Arabia are scant, with the available literature being inconsistent. This review summarizes the available data on the epidemiology and evolution of respiratory viruses. The demographic features associated with Middle East respiratory syndrome-related coronavirus infections are specifically analyzed for a better understanding of the epidemiology of this virus. The data support the view that continuous entry and exit of pilgrims and foreign workers with different ethnicities and socioeconomic backgrounds in Saudi Arabia is the most likely vehicle for global dissemination of respiratory viruses and for the emergence of new viruses (or virus variants) capable of greater dissemination.

An Overview of the Most Significant Zoonotic Viral Pathogens Transmitted from Animal to Human in Saudi Arabia

Currently, there has been an increasing socioeconomic impact of zoonotic pathogens transmitted from animals to humans worldwide. Recently, in the Arabian Peninsula, including in Saudi Arabia, epidemiological data indicated an actual increase in the number of emerging and/or reemerging cases of several viral zoonotic diseases. Data presented in this review are very relevant because Saudi Arabia is considered the largest country in the Peninsula. We believe that zoonotic pathogens in Saudi Arabia remain an important public health problem; however, more than 10 million Muslim pilgrims from around 184 Islamic countries arrive yearly at Makkah for the Hajj season and/or for the Umrah. Therefore, for health reasons, several countries recommend vaccinations for various zoonotic diseases among preventive protocols that should be complied with before traveling to Saudi Arabia. However, there is a shortage of epidemiological data focusing on the emerging and reemerging of zoonotic pathogens transmitted from animal to humans in different densely populated cities and/or localities in Saudi Arabia. Therefore, further efforts might be needed to control the increasing impacts of zoonotic viral disease. Also, there is a need for a high collaboration to enhance the detection and determination of the prevalence, diagnosis, control, and prevention as well as intervention and reduction in outbreaks of these diseases in Saudi Arabia, particularly those from other countries. Persons in the health field including physicians and veterinarians, pet owners, pet store owners, exporters, border guards, and people involved in businesses related to animal products have adopted various preventive strategies. Some of these measures might pave the way to highly successful prevention and control results on the different transmission routes of these viral zoonotic diseases from or to Saudi Arabia. Moreover, the prevention of these viral pathogens depends on socioeconomic impacts, available data, improved diagnosis, and highly effective therapeutics or prophylaxis.

Influenza A and B co-infection: a case-control study and review of the literature

Influenza virus infection remains a major cause of morbidity and mortality during winter seasons. Bacterial and virus co-infection is a commonly described situation in these patients. However, data on co-infection by influenza A and B viruses are lacking. In this study, we present the cases of co-infection by influenza A and B viruses during the winter season of 2014-2015 in our institution. We analyzed 2759 samples from 2111 patients and found that 625 samples corresponding to 609 patients were positive for influenza A or B virus. A total of 371 patients had influenza A, 228 had influenza B, and 10 (1.6 %) had influenza A and B virus detection in the same sample. The median age of co-infected patients was 78.6 years, and only one of the co-infected patients died because of the infection. Comparison with a control group of mono-infected patients revealed that co-infection was significantly associated with nosocomial acquisition [odds ratio (OR) = 4.5, 95 % confidence interval (CI) = 1.05-19.25, p = 0.042]. However, co-infection was not associated with worse outcome, previous underlying condition, or vaccination status. Multivariate analysis revealed that co-infection was not an independent risk factor for death and that no single risk factor could predict co-infection.

Strain Interactions as a Mechanism for Dominant Strain Alternation and Incidence Oscillation in Infectious Diseases: Seasonal Influenza as a Case Study

Background

Many human infectious diseases are caused by pathogens that have multiple strains and show oscillation in infection incidence and alternation of dominant strains which together are referred to as epidemic cycling. Understanding the underlying mechanisms of epidemic cycling is essential for forecasting outbreaks of epidemics and therefore important for public health planning. Current theoretical effort is mainly focused on the factors that are extrinsic to the pathogens themselves (“extrinsic factors”) such as environmental variation and seasonal change in human behaviours and susceptibility. Nevertheless, co-circulation of different strains of a pathogen was usually observed and thus strains interact with one another within concurrent infection and during sequential infection. The existence of these intrinsic factors is common and may be involved in the generation of epidemic cycling of multi-strain pathogens.

Methods and Findings

To explore the mechanisms that are intrinsic to the pathogens themselves (“intrinsic factors”) for epidemic cycling, we consider a multi-strain SIRS model including cross-immunity and infectivity enhancement and use seasonal influenza as an example to parameterize the model. The Kullback-Leibler information distance was calculated to measure the match between the model outputs and the typical features of seasonal flu (an outbreak duration of 11 weeks and an annual attack rate of 15%). Results show that interactions among strains can generate seasonal influenza with these characteristic features, provided that: the infectivity of a single strain within concurrent infection is enhanced 2−7 times that within a single infection; cross-immunity as a result of past infection is 0.5–0.8 and lasts 2–9 years; while other parameters are within their widely accepted ranges (such as a 2–3 day infectious period and the basic reproductive number of 1.8–3.0). Moreover, the observed alternation of the dominant strain among epidemics emerges naturally from the best fit model. Alternative modelling that also includes seasonal forcing in transmissibility shows that both external mechanisms (i.e. seasonal forcing) and the intrinsic mechanisms (i.e., strain interactions) are equally able to generate the observed time-series in seasonal flu.

Conclusions

The intrinsic mechanism of strain interactions alone can generate the observed patterns of seasonal flu epidemics, but according to Kullback-Leibler information distance the importance of extrinsic mechanisms cannot be excluded. The intrinsic mechanism illustrated here to explain seasonal flu may also apply to other infectious diseases caused by polymorphic pathogens.