Mortality attributable to seasonal influenza A and B infections in Thailand, 2005-2009: a longitudinal study

All-Cause and Cause-Specific Mortality Attributable to Seasonal Influenza: A Nationwide Matched Cohort Study

BACKGROUND

Although influenza poses substantial mortality burden, most studies have estimated excess mortality using time-aggregated data. Here, we estimated mortality risk and population attributable fraction (PAF) attributed to seasonal influenza using individual-level data from a nationwide matched cohort.

METHODS

Individuals with influenza during four consecutive influenza seasons (2013-2017) (n = 5,497,812) and 1:4 age- and sex-matched individuals without influenza (n = 20,990,683) were identified from a national health insurance database. The endpoint was mortality within 30 days after influenza diagnosis. All-cause and cause-specific mortality risk ratios (RRs) attributed to influenza were estimated. Excess mortality, mortality RR, and PAF of mortality were determined, including for underlying disease subgroups.

RESULTS

Excess mortality rate, mortality RR, and PAF of all-cause mortality were 49.5 per 100,000, 4.03 (95% confidence interval [CI], 3.63-4.48), and 5.6% (95% CI, 4.5-6.7%). Cause-specific mortality RR (12.85; 95% CI, 9.40-17.55) and PAF (20.7%; 95% CI, 13.2-27.0%) were highest for respiratory diseases. In subgroup analysis according to underlying disorders, PAF of all-cause mortality was 5.9% (95% CI, 0.6-10.7%) for liver disease, 5.8% (95% CI, 2.9-8.5%) for respiratory disease, and 3.8% (95% CI, 1.4-6.1%) for cancer.

CONCLUSION

Individuals with influenza had a 4-fold higher mortality risk than individuals without influenza. Preventing seasonal influenza may lead to 5.6% and 20.7% reductions in all-cause and respiratory mortality, respectively. Individuals with respiratory disease, liver disease, and cancer may benefit from prioritization when establishing influenza prevention strategies.

Estimation of Excess All-Cause Mortality Due to COVID-19 in Thailand

Thailand has experienced the most prominent COVID-19 outbreak in 2021, resulting in a new record for COVID-19 cases and deaths. To assess the influence of the COVID-19 outbreak on mortality, we estimated excess all-cause and pneumonia mortality in Thailand during the COVID-19 outbreak from April to October 2021. We used mortality from the previous 5 years to estimate the baseline number of deaths using generalized linear mixed models. The models were adjusted for seasonality and demographics. We found that, during the outbreak in 2021, there was a significant rise in excess fatalities, especially in the older age groups. The estimated cumulative excess death was 14.3% (95% CI: 8.6–18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, excess pneumonia deaths were also found to be 26.2% (95% CI: 4.8–46.0%) above baseline.

Economic Burden of Influenza in Thailand: A Systematic Review

Thailand has a high incidence and high mortality rates of influenza. This study summarizes the evidence on economic burden or costs of influenza subsequent to the occurrence of influenza illness in the Thai population by specific characteristics such as population demographics, health conditions, healthcare facilities, and/or cost types from published literature. A systematic search was conducted in six electronic databases. All costs were extracted and adjusted to 2018 US dollar value. Out of 581 records, 11 articles (1 with macroeconomic analysis and 10 with microeconomic analyses) were included. Direct medical costs per episode for outpatients and inpatients ranged from US$4.21 to US$212.17 and from US$163.62 to US$4577.83, respectively, across distinct influenza illnesses. The overall burden of influenza was between US$31.1 and US$83.6 million per year and 50-53% of these estimates referred to lost productivity. Costs of screening for an outbreak of influenza at an 8-bed-intensive-care-unit hospital was US$38242.75 per year. Labor-sensitive sectors such as services were the most affected part of the Thai economy. High economic burden tended to occur among children and older adults with co-morbidities and to be related to complications, non-vaccinated status, and severe influenza illness. Strategies involving prevention, limit of transmission, and treatment focusing on aforementioned patients’ factors, containment of hospitalization expenses and quarantine process, and assistance on labor-sensitive economy sectors are likely to reduce the economic burden of influenza. However, a research gap exists regarding knowledge about the economic burden of influenza in Thailand.

A Novel Mechanism Underlying Antiviral Activity of an Influenza Virus M2-Specific Antibody

Protective immunity against influenza A viruses (IAVs) generally depends on antibodies to the major envelope glycoprotein, hemagglutinin (HA), whose antigenicity is distinctive among IAV subtypes. On the other hand, the matrix 2 (M2) protein is antigenically highly conserved and has been studied as an attractive vaccine antigen to confer cross-protective immunity against multiple subtypes of IAVs. However, antiviral mechanisms of M2-specific antibodies are not fully understood. Here, we report the molecular basis of antiviral activity of an M2-specific monoclonal antibody (MAb), rM2ss23. We first found that rM2ss23 inhibited A/Aichi/2/1968 (H3N2) (Aichi) but not A/PR/8/1934 (H1N1) (PR8) replication. rM2ss23 altered the cell surface distribution of M2, likely by cross-linking the molecules, and interfered with the colocalization of HA and M2, resulting in reduced budding of progeny viruses. However, these effects were not observed for another strain, PR8, despite the binding capacity of rM2ss23 to PR8 M2. Interestingly, HA was also involved in the resistance of PR8 to rM2ss23. We also found that two amino acid residues at positions 54 and 57 in the M2 cytoplasmic tail were critical for the insensitivity of PR8 to rM2ss2. These findings suggest that the disruption of the M2-HA colocalization on infected cells and subsequent reduction of virus budding is one of the principal mechanisms of antiviral activity of M2-specific antibodies and that anti-M2 antibody-sensitive and -resistant IAVs have different properties in the interaction between M2 and HA.IMPORTANCE Although the IAV HA is the major target of neutralizing antibodies, most of the antibodies are HA subtype specific, restricting the potential of HA-based vaccines. On the contrary, the IAV M2 protein has been studied as a vaccine antigen to confer cross-protective immunity against IAVs with multiple HA subtypes, since M2 is antigenically conserved. Although a number of studies highlight the protective role of anti-HA neutralizing and nonneutralizing antibodies, precise information on the molecular mechanism of action of M2-specific antibodies is still obscure. In this study, we found that an anti-M2 antibody interfered with the HA-M2 association, which is important for efficient budding of progeny virus particles from infected cells. The antiviral activity was IAV strain dependent despite the similar binding capacity of the antibody to M2, and, interestingly, HA was involved in susceptibility to the antibody. Our data provide a novel mechanism underlying antiviral activity of M2-specific antibodies.

Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect

IntroductionEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges.AimIn a modelling study we combined environmental, epidemiological and laboratory surveillance data to estimate influenza-attributable mortality in Greece, over four seasons (2013/14 to 2016/17), specifically addressing the lag dimension and the confounding effect of temperature.MethodsAssociations of influenza type/subtype-specific incidence proxies and of daily mean temperature with mortality were estimated with a distributed-lag nonlinear model with 30 days of maximum lag, separately by age group (all ages, 15-64 and ≥ 65 years old). Total and weekly deaths attributable to influenza and cold temperatures were calculated.ResultsOverall influenza-attributable mortality was 23.6 deaths per 100,000 population per year (95% confidence interval (CI): 17.8 to 29.2), and varied greatly between seasons, by influenza type/subtype and by age group, with the vast majority occurring in persons aged ≥ 65 years. Most deaths were attributable to A(H3N2), followed by influenza B. During periods of A(H1N1)pdm09 circulation, weekly attributable mortality to this subtype among people ≥ 65 years old increased rapidly at first, but then fell to zero and even negative, suggesting a mortality displacement (harvesting) effect. Mortality attributable to cold temperatures was much higher than that attributable to influenza.ConclusionsStudies of influenza-attributable mortality need to consider distributed-lag effects, stratify by age group and adjust both for circulating influenza virus types/subtypes and daily mean temperatures, in order to produce reliable estimates. Our approach addresses these issues, is readily applicable in the context of influenza surveillance, and can be useful for other countries.

Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review

Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from -0.3-1.3 and 0.6-8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4-119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No "average" estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.

Evaluation of data sources and approaches for estimation of influenza-associated mortality in India

BACKGROUND

No estimates of influenza-associated mortality exist for India.

OBJECTIVE

To evaluate national mortality and viral surveillance data from India for assessing their appropriateness in estimating influenza-associated mortality using varied analytic approaches.

METHODS

We reviewed influenza virus surveillance data from a national influenza surveillance network. We also reviewed national mortality data from Civil Registration System (CRS), Medical Certification of Cause of Death (MCCD) and the Sample Registration System (SRS). We compared and scored the different sources of mortality data using specific criteria, including the process of cause of death assignment, sample size, proportion of ill-defined deaths, representativeness and availability of time series data. Each of these 5 parameters was scored on a scale from 1 to 5. To evaluate how to generate an influenza-associated mortality estimate for India, we also reviewed 4 methodologic approaches to assess the appropriateness of their assumptions and requirements for these data sets.

RESULTS

The influenza virus surveillance data included year-round sample testing for influenza virus and was found to be suitable for influenza mortality estimation modelling. Based on scoring for the 5 mortality data criteria, the SRS data had the highest score with 20 of 25 possible score, whereas MCCD and CRS scored 16 and 12, respectively. The SRS which used verbal autopsy survey methods was determined to be nationally representative and thus adequate for estimating influenza-associated mortality. Evaluation of the modelling methods demonstrated that Poisson regression, risk difference and mortality multiplier methods could be applied to the Indian setting.

CONCLUSION

Despite significant challenges, it is possible to estimate influenza-associated mortality in India.

Influenza-associated mortality in Yancheng, China, 2011-15

INTRODUCTION

The Yangtze river delta in eastern China, centered on Shanghai, is one of the most populated regions of the world with more than 100 million residents. We examined the impact of influenza on excess mortality in Yancheng, a prefecture-level city with 8.2 million population located 250 km north of Shanghai, during 2011-2015.

METHODS

We obtained individual data on deaths by date, age, sex, and cause in Yancheng from the Chinese Centers for Disease Control and Prevention, and used these to derive weekly rates of mortality from respiratory causes, respiratory and cardiovascular causes combined, and all causes. We used data on influenza-like illnesses and laboratory detections of influenza to construct a proxy measure of the weekly incidence of influenza virus infections in the community. We used regression models to estimate the association of influenza activity with mortality and excess mortality by age, cause, and influenza type/subtype.

RESULTS

We estimated that an annual average of 4.59 (95% confidence interval: 3.94, 7.41) excess respiratory deaths per 100 000 persons were associated with influenza, which was 4.6% of all respiratory deaths in the years studied. Almost all influenza-associated excess deaths occurred in persons ≥65 years. Influenza A(H3N2) had the greatest impact on mortality and was associated with around 50% of the influenza-associated respiratory deaths in the 5 years studied.

CONCLUSIONS

Influenza has a substantial impact on respiratory mortality in Yancheng, mainly in older adults. Influenza vaccination has the potential to reduce disease burden, and cost-effectiveness analysis could be used to compare policy options.

Tackling influenza with broadly neutralizing antibodies

Monoclonal antibodies have revolutionized the treatment of several human diseases, including cancer, autoimmunity and inflammatory conditions and represent a new frontier for the treatment of infectious diseases. In the last decade, new methods have allowed the efficient interrogation of the human antibody repertoire from influenza immune individuals and the isolation of several monoclonal antibodies capable of dealing with the high variability of influenza viruses. Here, we will provide a comprehensive overview of the specificity, antiviral and immunological mechanisms of action and development into the clinic of broadly reactive monoclonal antibodies against influenza A and B viruses.

A joint analysis of influenza-associated hospitalizations and mortality in Hong Kong, 1998-2013

Influenza viruses may cause severe human infections leading to hospitalization or death. Linear regression models were fitted to population-based data on hospitalizations and deaths. Surveillance data on influenza virus activity permitted inference on influenza-associated hospitalizations and deaths. The ratios of these estimates were used as a potential indicator of severity. Influenza was associated with 431 (95% CrI: 358–503) respiratory deaths and 12,700 (95% CrI: 11,700–13,700) respiratory hospitalizations per year. Majority of the excess deaths occurred in persons ≥65 y of age. The ratios of deaths to hospitalizations in adults ≥65 y were significantly higher for influenza A(H1N1) and A(H1N1)pdm09 compared to A(H3N2) and B. Substantial disease burden associated with influenza viruses were estimated in Hong Kong particularly among children and elderly in 1998–2013. Infections with influenza A(H1N1) was suggested to be more serious than A(H3N2) in older adults.

Drug resistance in influenza A virus: the epidemiology and management

Influenza A virus (IAV) is the sole cause of the unpredictable influenza pandemics and deadly zoonotic outbreaks and constitutes at least half of the cause of regular annual influenza epidemics in humans. Two classes of anti-IAV drugs, adamantanes and neuraminidase (NA) inhibitors (NAIs) targeting the viral components M2 ion channel and NA, respectively, have been approved to treat IAV infections. However, IAV rapidly acquired resistance against both classes of drugs by mutating these viral components. The adamantane-resistant IAV has established itself in nature, and a majority of the IAV subtypes, especially the most common H1N1 and H3N2, circulating globally are resistant to adamantanes. Consequently, adamantanes have become practically obsolete as anti-IAV drugs. Similarly, up to 100% of the globally circulating IAV H1N1 subtypes were resistant to oseltamivir, the most commonly used NAI, until 2009. However, the 2009 pandemic IAV H1N1 subtype, which was sensitive to NAIs and has now become one of the dominant seasonal influenza virus strains, has replaced the pre-2009 oseltamivir-resistant H1N1 variants. This review traces the epidemiology of both adamantane- and NAI-resistant IAV subtypes since the approval of these drugs and highlights the susceptibility status of currently circulating IAV subtypes to NAIs. Further, it provides an overview of currently and soon to be available control measures to manage current and emerging drug-resistant IAV. Finally, this review outlines the research directions that should be undertaken to manage the circulation of IAV in intermediate hosts and develop effective and alternative anti-IAV therapies.

Assessment of potential public health impact of a quadrivalent inactivated influenza vaccine in Thailand

BACKGROUND

Each year, an influenza B strain representing only one influenza B lineage is included in the trivalent inactivated influenza vaccine (IIV3); a mismatch between the selected lineage and circulating viruses can result in suboptimal vaccine effectiveness. We modeled the added potential public health impact of a quadrivalent inactivated influenza vaccine (IIV4) that includes strains from both influenza B lineages compared to IIV3 on influenza-associated morbidity and mortality in Thailand.

METHODS

Using data on the incidence of influenza-associated hospitalizations and deaths, vaccine effectiveness, and vaccine coverage from the 2007-2012 influenza seasons in Thailand, we estimated rates of influenza-associated outcomes that might be averted using IIV4 instead of IIV3. We then applied these rates to national population estimates to calculate averted illnesses, hospitalizations, and deaths for each season. We assumed that the influenza B lineage included in IIV3 would provide a relative vaccine effectiveness of 75% against the other B lineage.

RESULTS

Compared to use of IIV3, use of IIV4 might have led to an additional reduction ranging from 0·4 to 14·3 influenza-associated illnesses per 100 000 population/year, <0·1 to 0·5 hospitalizations per 100 000/year, and <0·1 to 0·4 deaths per 1000/year. Based on extrapolation to national population estimates, replacement of IIV3 with IIV4 might have averted an additional 267-9784 influenza-associated illnesses, 9-320 hospitalizations, and 0-3 deaths.

CONCLUSION

Compared to use of IIV3, IIV4 has the potential to further reduce the burden of influenza-associated morbidity and mortality in Thailand.

Influenza-associated mortality in Thailand, 2006-2011

Background

Influenza-associated mortality in subtropical or tropical regions, particularly in developing countries, remains poorly quantified and often underestimated. We analyzed data in Thailand, a middle-income tropical country with good vital statistics and influenza surveillance data.

Methods

We obtained weekly mortality data for all-cause and three underlying causes of death (circulatory and respiratory diseases, and pneumonia and influenza), and weekly influenza virus data, from 2006 to 2011. A negative binomial regression model was used to estimate deaths attributable to influenza in two age groups (<65 and ≥65 years) by incorporating influenza viral data as covariates in the model.

Results

From 2006 to 2011, the average annual influenza-associated mortality per 100 000 persons was 4·0 (95% CI: −18 to 26). Eighty-three percent of influenza-associated deaths occurred among persons aged > 65 years. The average annual rate of influenza-associated deaths was 0·7 (95% CI: −8·2 to 10) per 100 000 population for person aged <65 years and 42 (95% CI: −137 to 216) for person aged ≥ 65 years.

Discussion

In Thailand, estimated excess mortality associated with influenza was considerable even during non-pandemic years. These data provide support for Thailand's seasonal influenza vaccination campaign. Continued monitoring of mortality data is important to assess impact.

Seasonal influenza vaccination for children in Thailand: a cost-effectiveness analysis

BACKGROUND

Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly.

METHODS AND FINDINGS

We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups.

CONCLUSIONS

Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries.