2009 versus 2010 comparison of influenza activity in southern hemisphere temperate countries

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.

Seasonality as a driver of pH1N12009 influenza vaccination campaign impact

Although the most recent respiratory virus pandemic was triggered by a Coronavirus, sustained and elevated prevalence of highly pathogenic avian influenza viruses able to infect mammalian hosts highlight the continued threat of pandemics of influenza A virus (IAV) to global health. Retrospective analysis of pandemic outcomes, including comparative investigation of intervention efficacy in different regions, provide important contributions to the evidence base for future pandemic planning. The swine-origin IAV pandemic of 2009 exhibited regional variation in onset, infection dynamics and annual infection attack rates (IARs). For example, the UK experienced three severe peaks of infection over two influenza seasons, whilst Australia experienced a single severe wave. We adopt a seasonally forced 2-subtype model for the transmission of pH1N12009 and seasonal H3N2 to examine the role vaccination campaigns may play in explaining differences in pandemic trajectories in temperate regions. Our model differentiates between the nature of vaccine- and infection-acquired immunity. In particular, we assume that immunity triggered by infection elicits heterologous cross-protection against viral shedding in addition to long-lasting neutralising antibody, whereas vaccination induces imperfect reduction in susceptibility. We employ an Approximate Bayesian Computation (ABC) framework to calibrate the model using data for pH1N12009 seroprevalence, relative subtype dominance, and annual IARs for Australia and the UK. Heterologous cross-protection substantially suppressed the pandemic IAR over the posterior, with the strength of protection against onward transmission inversely correlated with the initial reproduction number. We show that IAV pandemic timing relative to the usual seasonal influenza cycle influenced the size of the initial waves of pH1N12009 in temperate regions and the impact of vaccination campaigns.

Viral Interference between Respiratory Viruses

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract and lead to virus‒virus interactions. Infection by a first virus could enhance or reduce infection and replication of a second virus, resulting in positive (additive or synergistic) or negative (antagonistic) interaction. The concept of viral interference has been demonstrated at the cellular, host, and population levels. The mechanisms involved in viral interference have been evaluated in differentiated airway epithelial cells and in animal models susceptible to the respiratory viruses of interest. A likely mechanism is the interferon response that could confer a temporary nonspecific immunity to the host. During the coronavirus disease pandemic, nonpharmacologic interventions have prevented the circulation of most respiratory viruses. Once the sanitary restrictions are lifted, circulation of seasonal respiratory viruses is expected to resume and will offer the opportunity to study their interactions, notably with severe acute respiratory syndrome coronavirus 2.

Which influenza viruses will emerge following the SARS-CoV-2 pandemic?

The world has experienced five pandemics in just over one hundred years, four due to influenza and one due to coronavirus (SARS-CoV-2). In each case of pandemic influenza, the pandemic influenza strain has replaced the previous seasonal influenza virus. Notably, throughout the SARS-CoV-2 pandemic, there has been a 99% reduction in influenza isolation globally. It is anticipated that influenza will re-emerge following the SARS-CoV-2 pandemic and circulate again. The potential for which influenza viruses will emerge is examined.

Therapeutic Exploitation of Viral Interference

Viral interference, originally, referred to a state of temporary immunity, is a state whereby infection with a virus limits replication or production of a second infecting virus. However, replication of a second virus could also be dominant over the first virus. In fact, dominance can alternate between the two viruses. Expression of type I interferon genes is many times upregulated in infected epithelial cells. Since the interferon system can control most, if not all, virus infections in the absence of adaptive immunity, it was proposed that viral induction of a nonspecific localized temporary state of immunity may provide a strategy to control viral infections. Clinical observations also support such a theory, which gave credence to the development of superinfection therapy (SIT). SIT is an innovative therapeutic approach where a non-pathogenic virus is used to infect patients harboring a pathogenic virus. For the functional cure of persistent viral infections and for the development of broad- spectrum antivirals against emerging viruses a paradigm shift was recently proposed. Instead of the virus, the therapy should be directed at the host. Such a host-directed-therapy (HDT) strategy could be the activation of endogenous innate immune response via toll-like receptors (TLRs). Superinfection therapy is such a host-directed-therapy, which has been validated in patients infected with two completely different viruses, the hepatitis B (DNA), and hepatitis C (RNA) viruses. SIT exerts post-infection interference via the constant presence of an attenuated non-pathogenic avian double- stranded (ds) RNA viral vector which boosts the endogenous innate (IFN) response. SIT could, therefore, be developed into a biological platform for a new "one drug, multiple bugs" broad-spectrum antiviral treatment approach.

Possible explanations for why some countries were harder hit by the pandemic influenza virus in 2009 - a global mortality impact modeling study

BACKGROUND

A global pandemic mortality study found prominent regional mortality variations in 2009 for Influenza A(H1N1)pdm09. Our study attempts to identify factors that explain why the pandemic mortality burden was high in some countries and low in others.

METHODS

As a starting point, we identified possible risk factors worth investigating for Influenza A(H1N1)pdm09 mortality through a targeted literature search. We then used a modeling procedure (data simulations and regression models) to identify factors that could explain differences in respiratory mortality due to Influenza A(H1N1)pdm09. We ran sixteen models to produce robust results and draw conclusions. In order to assess the role of each factor in explaining differences in excess pandemic mortality, we calculated the reduction in between country variance, which can be viewed as an effect-size for each factor.

RESULTS

The literature search identified 124 publications and 48 possible risk factors, of which we were able to identify 27 factors with appropriate global datasets. The modelling procedure indicated that age structure (explaining 40% of the mean between country variance), latitude (8%), influenza A and B viruses circulating during the pandemic (3-8%), influenza A and B viruses circulating during the preceding influenza season (2-6%), air pollution (pm10; 4%) and the prevalence of other infections (HIV and TB) (4-6%) were factors that explained differences in mortality around the world. Healthcare expenditure, levels of obesity, the distribution of antivirals, and air travel did not explain global pandemic mortality differences.

CONCLUSIONS

Our study found that countries with a large proportion of young persons had higher pandemic mortality rates in 2009. The co-circulation of influenza viruses during the pandemic and the circulation of influenza viruses during the preceding season were also associated with pandemic mortality rates. We found that real time assessments of 2009 pandemic mortality risk factors (e.g. obesity) probably led to a number of false positive findings.

Transmission of the First Influenza A(H1N1)pdm09 Pandemic Wave in Australia Was Driven by Undetected Infections: Pandemic Response Implications

Background

During the first wave of influenza A(H1N1)pdm09 in Victoria, Australia the rapid increase in notified cases and the high proportion with relatively mild symptoms suggested that community transmission was established before cases were identified. This lead to the hypothesis that those with low-level infections were the main drivers of the pandemic.

Methods

A deterministic susceptible-infected-recovered model was constructed to describe the first pandemic wave in a population structured by disease severity levels of asymptomatic, low-level symptoms, moderate symptoms and severe symptoms requiring hospitalisation. The model incorporated mixing, infectivity and duration of infectiousness parameters to calculate subgroup-specific reproduction numbers for each severity level.

Results

With stratum-specific effective reproduction numbers of 1.82 and 1.32 respectively, those with low-level symptoms, and those with asymptomatic infections were responsible for most of the transmission. The effective reproduction numbers for infections resulting in moderate symptoms and hospitalisation were less than one. Sensitivity analyses confirmed the importance of parameters relating to asymptomatic individuals and those with low-level symptoms.

Conclusions

Transmission of influenza A(H1N1)pdm09 was largely driven by those invisible to the health system. This has implications for control measures–such as distribution of antivirals to cases and contacts and quarantine/isolation–that rely on detection of infected cases. Pandemic plans need to incorporate milder scenarios, with a graded approach to implementation of control measures.

Interval Between Infections and Viral Hierarchy Are Determinants of Viral Interference Following Influenza Virus Infection in a Ferret Model

BACKGROUND

Epidemiological studies suggest that, following infection with influenza virus, there is a short period during which a host experiences a lower susceptibility to infection with other influenza viruses. This viral interference appears to be independent of any antigenic similarities between the viruses. We used the ferret model of human influenza to systematically investigate viral interference.

METHODS

Ferrets were first infected then challenged 1-14 days later with pairs of influenza A(H1N1)pdm09, influenza A(H3N2), and influenza B viruses circulating in 2009 and 2010.

RESULTS

Viral interference was observed when the interval between initiation of primary infection and subsequent challenge was <1 week. This effect was virus specific and occurred between antigenically related and unrelated viruses. Coinfections occurred when 1 or 3 days separated infections. Ongoing shedding from the primary virus infection was associated with viral interference after the secondary challenge.

CONCLUSIONS

The interval between infections and the sequential combination of viruses were important determinants of viral interference. The influenza viruses in this study appear to have an ordered hierarchy according to their ability to block or delay infection, which may contribute to the dominance of different viruses often seen in an influenza season.

Efficacy and immunogenicity of influenza vaccine in HIV-infected children: a randomized, double-blind, placebo controlled trial

BACKGROUND

HIV-infected children are at heightened risk for severe influenza illness; however, there is no study on the efficacy or effectiveness of influenza vaccine in these children. We evaluated the safety, immunogenicity, and efficacy of nonadjuvanted, trivalent inactivated influenza vaccine (TIV) against confirmed seasonal influenza virus illness in HIV-infected children.

METHODS

A double-blind, placebo-controlled trial was undertaken in Johannesburg in 2009. Four hundred and ten children were randomized to two doses of TIV or placebo 1 month apart. Nasopharyngeal aspirates obtained at respiratory illness visits were tested by influenza-specific reverse transcriptase-PCR (RT-PCR). Vaccine immunogenicity was evaluated by hemagglutinin inhibition (HAI) assay. Influenza isolates were sequenced and evaluated in maximum likelihood phylogenetic analysis.

RESULTS

Overall, the median age of participants was 23.8 months and their median CD4% was 33.5. Ninety-two percent of enrolees were on antiretroviral therapy. Among children receiving both doses of vaccine/placebo, confirmed seasonal influenza illness occurred in 13 (all H3N2) of 205 TIV recipients and 17 (15 H3N2 and two influenza B) of 200 placebo recipients with vaccine efficacy of 17.7% (95% confidence interval <0-62.4%). The proportion of TIV recipients who seroconverted after second dose against vaccine strains of H1N1, H3N2, and influenza B were 47.5, 50.0, and 40.0%, compared to 4.7, 11.6, and 0%, respectively among placebo recipients. There were no TIV-related serious adverse events. Sequence analysis of wild-type H3N2 strains indicated drift from the H3N2 vaccine strain.

CONCLUSION

Poor immunogenicity of TIV, coupled with drift of circulating H3N2 wild-type compared to vaccine strain, may explain the lack of efficacy of TIV in young HIV-infected children. Alternate TIV vaccine schedules or formulations warrant evaluation for efficacy in HIV-infected children.

Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries

Background

The global impact of the 2009 influenza A(H1N1) pandemic (H1N1pdm) is not well understood.

Objectives

We estimate overall and age‐specific prevalence of cross‐reactive antibodies to H1N1pdm virus and rates of H1N1pdm infection during the first year of the pandemic using data from published and unpublished H1N1pdm seroepidemiological studies.

Methods

Primary aggregate H1N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1N1pdm activity. Seropositivity was assessed using well‐described and standardized hemagglutination inhibition (HI titers ≥32 or ≥40) and microneutralization (MN ≥ 40) laboratory assays. The prevalence of cross‐reactive antibodies to the H1N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1N1pdm cumulative incidence was estimated for studies in which collected both pre‐ and post‐pandemic sera; and H1N1pdm seropositivity was calculated from studies with post‐pandemic sera only (collected between December 2009–June 2010).

Results

Data from 27 published/unpublished studies from 19 countries/administrative regions – Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam – were eligible for inclusion. The overall age‐standardized pre‐pandemic prevalence of cross‐reactive antibodies was 5% (95%CI 3–7%) and varied significantly by age with the highest rates among persons ≥65 years old (14% 95%CI 8–24%). Overall age‐standardized H1N1pdm cumulative incidence was 24% (95%CI 20–27%) and varied significantly by age with the highest in children 5–19 (47% 95%CI 39–55%) and 0–4 years old (36% 95%CI 30–43%).

Conclusions

Our results offer unique insight into the global impact of the H1N1 pandemic and highlight the need for standardization of seroepidemiological studies and for their inclusion in pre‐pandemic preparedness plans. Our results taken together with recent global pandemic respiratory‐associated mortality estimates suggest that the case fatality ratio of the pandemic virus was approximately 0·02%.

Were equatorial regions less affected by the 2009 influenza pandemic? The Brazilian experience

Although it is in the Tropics where nearly half of the world population lives and infectious disease burden is highest, little is known about the impact of influenza pandemics in this area. We investigated the mortality impact of the 2009 influenza pandemic relative to mortality rates from various outcomes in pre-pandemic years throughout a wide range of latitudes encompassing the entire tropical, and part of the subtropical, zone of the Southern Hemisphere (+5^°N to −35^°S) by focusing on a country with relatively uniform health care, disease surveillance, immunization and mitigation policies: Brazil. To this end, we analyzed laboratory-confirmed deaths and vital statistics mortality beyond pre-pandemic levels for each Brazilian state. Pneumonia, influenza and respiratory mortality were significantly higher during the pandemic, affecting predominantly adults aged 25 to 65 years. Overall, there were 2,273 and 2,787 additional P&I- and respiratory deaths during the pandemic, corresponding to a 5.2% and 2.7% increase, respectively, over average pre-pandemic annual mortality. However, there was a marked spatial structure in mortality that was independent of socio-demographic indicators and inversely related with income: mortality was progressively lower towards equatorial regions, where low or no difference from pre-pandemic mortality levels was identified. Additionally, the onset of pandemic-associated mortality was progressively delayed in equatorial states. Unexpectedly, there was no additional mortality from circulatory causes. Comparing disease burden reliably across regions is critical in those areas marked by competing health priorities and limited resources. Our results suggest, however, that tropical regions of the Southern Hemisphere may have been disproportionally less affected by the pandemic, and that climate may have played a key role in this regard. These findings have a direct bearing on global estimates of pandemic burden and the assessment of the role of immunological, socioeconomic and environmental drivers of the transmissibility and severity of this pandemic.