Co-infection with influenza A/H1N1 and A/H3N2 viruses in a patient with influenza-like illness during the winter/spring of 2008 in Shanghai, China

B, Wang G, Medina RA, Van Bakel H, García-Sastre A, Nelson MI, Ghedin E, Veiga ABG. Tracking the emergence of antigenic variants in influenza A virus epidemics in Brazil

Influenza A virus (IAV) circulation patterns differ in North America and South America, with influenza seasons often characterized by different subtypes and strains. However, South America is relatively undersampled considering the size of its population. To address this gap, we sequenced the complete genomes of 220 IAVs collected between 2009 and 2016 from hospitalized patients in southern Brazil. New genetic drift variants were introduced into southern Brazil each season from a global gene pool, including four H3N2 clades (3c, 3c2, 3c3, and 3c2a) and five H1N1pdm clades (clades 6, 7, 6b, 6c, and 6b1). In 2016, H1N1pdm viruses belonging to a new 6b1 clade caused a severe influenza epidemic in southern Brazil that arrived early and spread rapidly, peaking mid-autumn. Inhibition assays showed that the A/California/07/2009(H1N1) vaccine strain did not protect well against 6b1 viruses. Phylogenetically, most 6b1 sequences that circulated in southern Brazil belong to a single transmission cluster that rapidly diffused across susceptible populations, leading to the highest levels of influenza hospitalization and mortality seen since the 2009 pandemic. Continuous genomic surveillance is needed to monitor rapidly evolving IAVs for vaccine strain selection and understand their epidemiological impact in understudied regions.

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.

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.

Clinical presentations and outcomes of influenza infection among hematology/oncology patients from a single cancer center: pandemic and post-pandemic seasons

BACKGROUND

Influenza can cause severe infection in hematology/oncology patients. The occurrence of the 2009 pandemic represented an opportunity to study the impact of influenza on such patients in pandemic and post-pandemic seasons.

METHODS

We retrospectively reviewed medical records of hematology/oncology patients who had laboratory-confirmed influenza infection during the 2009 pandemic and the first post-pandemic seasons. We assessed influenza-related outcomes in both seasons with emphasis on the development of pneumonia and mortality. We also analyzed factors associated with poor outcomes.

RESULTS

We included 350 patients; 207 were diagnosed in the pandemic and 143 in the post-pandemic seasons. Influenza severity was similar in both seasons with no significant differences in the development of pneumonia or death. Infection with the pH1N1 virus was associated with the development of pneumonia (24.7% vs 14.9%, p = 0.029) but did not affect mortality. A multivariate analysis showed that initiation of antiviral treatment after > 48 h, healthcare acquisition of influenza, and low albumin were independent risk factors for the development of pneumonia (p values 0.022, 0.003, and < 0.0001, respectively). A log-rank test showed increased mortality in patients who received therapy > 48 h after onset of symptoms (p = 0.001).

CONCLUSIONS

In hematology/oncology patients, influenza was as severe in the post-pandemic as in the pandemic season. Pneumonia developed more commonly in patients infected with pH1N1 virus. Healthcare acquisition of infection and low albumin were associated with the development of pneumonia. Delayed initiation of antiviral treatment was associated with both pneumonia and mortality.