Prediction of upcoming global infection burden of influenza seasons after relaxation of public health and social measures during the COVID-19 pandemic: a modelling study

Duration of fever in children infected with influenza A(H1N1)pdm09, A(H3N2) or B virus and treated with baloxavir marboxil, oseltamivir, laninamivir, or zanamivir in Japan during the 2012-2013 and 2019-2020 influenza seasons

We compared the duration of fever in children infected with A(H1N1)pdm09, A(H3N2), or influenza B viruses following treatment with baloxavir marboxil (baloxavir) or neuraminidase inhibitors (NAIs) (oseltamivir, zanamivir, or laninamivir). This observational study was conducted at 10 outpatient clinics across 9 prefectures in Japan during the 2012-2013 and 2019-2020 influenza seasons. Patients with influenza rapid antigen test positive were treated with one of four anti-influenza drugs. The type/subtype of influenza viruses were identified from MDCK or MDCK SIAT1 cell-grown samples using two-step real-time PCR. Daily self-reported body temperature after treatment were used to evaluate the duration of fever by treatment group and various underlying factors. Among 1742 patients <19 years old analyzed, 452 (26.0%) were A(H1N1)pdm09, 827 (48.0%) A(H3N2), and 463 (26.0%) influenza B virus infections. Among fours treatment groups, baloxavir showed a shorter median duration of fever compared to oseltamivir in univariate analysis for A(H1N1)pdm09 virus infections (baloxavir, 22.0 h versus oseltamivir, 26.7 h, P < 0.05; laninamivir, 25.5 h, and zanamivir, 25.0 h). However, this difference was not significant in multivariable analyses. For A(H3N2) virus infections, there were no statistically significant differences observed (20.3, 21.0, 22.0, and 19.0 h) uni- and multivariable analyses. For influenza B, baloxavir shortened the fever duration by approximately 15 h than NAIs (20.3, 35.0, 34.3, and 34.1 h), as supported by uni- and multivariable analyses. Baloxavir seems to have comparable clinical effectiveness with NAIs on influenza A but can be more effective for treating pediatric influenza B virus infections than NAIs.

Detection of influenza A(H3N2) viruses with polymerase acidic subunit substitutions after and prior to baloxavir marboxil treatment during the 2022-2023 influenza season in Japan

Baloxavir marboxil (baloxavir), approved as an anti-influenza drug in Japan in March 2018, can induce reduced therapeutic effectiveness due to PA protein substitutions. We assessed PA substitutions in clinical samples from influenza-infected children and adults pre- and post-baloxavir treatment, examining their impact on fever and symptom duration. During the 2022-2023 influenza season, the predominant circulating influenza subtype detected by cycling-probe RT-PCR was A(H3N2) (n = 234), with a minor circulation of A(H1N1)pdm09 (n = 10). Of the 234 influenza A(H3N2) viruses collected prior to baloxavir treatment, 2 (0.8%) viruses carry PA/I38T substitution. One virus was collected from a toddler and one from an adult, indicating the presence of viruses with reduced susceptibility to baloxavir, without prior exposure to the drug. Of the 54 paired influenza A(H3N2) viruses collected following baloxavir treatment, 8 (14.8%) viruses carried E23 K/G, or I38 M/T substitutions in PA. Variant calling through next-generation sequencing (NGS) showed varying proportions (6-100 %), a polymorphism and a mixture of PA/E23 K/G, and I38 M/T substitutions in the clinical samples. These eight viruses were obtained from children aged 7-14 years, with a median fever duration of 16.7 h and a median symptom duration of 93.7 h, which were similar to those of the wild type. However, the delayed viral clearance associated with the emergence of PA substitutions was observed. No substitutions conferring resistance to neuraminidase inhibitors were detected in 37 paired samples collected before and following oseltamivir treatment. These findings underscore the need for ongoing antiviral surveillance, informing public health strategies and clinical antiviral recommendations for seasonal influenza.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

CD8+ T-cell responses towards conserved influenza B virus epitopes across anatomical sites and age

Influenza B viruses (IBVs) cause substantive morbidity and mortality, and yet immunity towards IBVs remains understudied. CD8+ T-cells provide broadly cross-reactive immunity and alleviate disease severity by recognizing conserved epitopes. Despite the IBV burden, only 18 IBV-specific T-cell epitopes restricted by 5 HLAs have been identified currently. A broader array of conserved IBV T-cell epitopes is needed to develop effective cross-reactive T-cell based IBV vaccines. Here we identify 9 highly conserved IBV CD8+ T-cell epitopes restricted to HLA-B*07:02, HLA-B*08:01 and HLA-B*35:01. Memory IBV-specific tetramer+CD8+ T-cells are present within blood and tissues. Frequencies of IBV-specific CD8+ T-cells decline with age, but maintain a central memory phenotype. HLA-B*07:02 and HLA-B*08:01-restricted NP30-38 epitope-specific T-cells have distinct T-cell receptor repertoires. We provide structural basis for the IBV HLA-B*07:02-restricted NS1196-206 (11-mer) and HLA-B*07:02-restricted NP30-38 epitope presentation. Our study increases the number of IBV CD8+ T-cell epitopes, and defines IBV-specific CD8+ T-cells at cellular and molecular levels, across tissues and age.

Cocirculation and coinfection of multiple respiratory viruses during autumn and winter seasons of 2023 in Beijing, China: A retrospective study

China experienced severe epidemics of multiple respiratory pathogens in 2023 after lifting "Zero-COVID" policy. The present study aims to investigate the changing circulation and infection patterns of respiratory pathogens in 2023. The 160 436 laboratory results of influenza virus and respiratory syncytial virus (RSV) from February 2020 to December 2023, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from June 2020 to December 2023, Mycoplasma pneumoniae, adenovirus, and human rhinovirus from January 2023 to December 2023 were analyzed. We observed the alternating epidemics of SARS-CoV-2 and influenza A virus (IAV), as well as the out-of-season epidemic of RSV during the spring and summer of 2023. Cocirculation of multiple respiratory pathogens was observed during the autumn and winter of 2023. The susceptible age range of RSV in this winter epidemic (10.5, interquartile range [IQR]: 5-30) was significantly higher than previously (4, IQR: 3-34). The coinfection rate of IAV and RSV in this winter epidemic (0.695%) was significantly higher than that of the last cocirculation period (0.027%) (p < 0.001). Similar trend was also found in the coinfection of IAV and SARS-CoV-2. The present study observed the cocirculation of multiple respiratory pathogens, changing age range of susceptible population, and increasing coinfection rates during the autumn and winter of 2023, in Beijing, China.

The epidemic forest reveals the spatial pattern of the spread of acute respiratory infections in Jakarta, Indonesia

Acute respiratory infection (ARI) is a communicable disease of the respiratory tract that implies impaired breathing. The infection can expand from one to the neighboring areas at a region-scale level through a human mobility network. Specific to this study, we leverage a record of ARI incidences in four periods of outbreaks for 42 regions in Jakarta to study its spatio-temporal spread using the concept of the epidemic forest. This framework generates a forest-like graph representing an explicit spread of disease that takes the onset time, spatio-temporal distance, and case prevalence into account. To support this framework, we use logistic curves to infer the onset time of the outbreak for each region. The result shows that regions with earlier onset dates tend to have a higher burden of cases, leading to the idea that the culprits of the disease spread are those with a high load of cases. To justify this, we generate the epidemic forest for the four periods of ARI outbreaks and identify the implied dominant trees (that with the most children cases). We find that the primary infected city of the dominant tree has a relatively higher burden of cases than other trees. In addition, we can investigate the timely ( R t ) and spatial reproduction number ( R c ) by directly evaluating them from the inferred graphs. We find that R t for dominant trees are significantly higher than non-dominant trees across all periods, with regions in western Jakarta tend to have higher values of R c . Lastly, we provide simulated-implied graphs by suppressing 50% load of cases of the primary infected city in the dominant tree that results in a reduced R c , suggesting a potential target of intervention to depress the overall ARI spread.

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.

Effects of scheduled school breaks on the circulation of influenza in children, school-aged population, and adults in China: A spatio-temporal analysis

OBJECTIVES

To investigate the effect of scheduled school break on the circulation of influenza in young children, school-aged population, and adults.

METHODS

In a spatial-temporal analysis using influenza activity, school break dates, and meteorological covariates across mainland China during 2015-2018, we estimated age-specific, province-specific, and overall relative risk (RR) and effectiveness of school break on influenza.

RESULTS

We included data in 24, 25, and 17 provinces for individuals aged 0-4 years, 5-19 years and 20+ years. We estimated a RR meta-estimate of 0.34 (95% confidence interval 0.29-0.40) and an effectiveness of 66% for school break in those aged 5-19 years. School break showed a lagged and smaller mitigation effect in those aged 0-4 years (RR meta-estimate: 0.73, 0.68-0.79) and 20+ years (RR meta-estimate: 0.89, 0.78-1.01) versus those aged 5-19 years.

CONCLUSION

The results show heterogeneous effects of school break between population subgroups, a pattern likely to hold for other respiratory infectious diseases. Our study highlights the importance of anticipating age-specific effects of implementing school closure interventions and provides evidence for rational use of school closure interventions in future epidemics.

Immunogenicity and protective efficacy of a co-formulated two-in-one inactivated whole virus particle COVID-19/influenza vaccine

Due to the synchronous circulation of seasonal influenza viruses and severe acute respiratory coronavirus 2 (SARS-CoV-2) which causes coronavirus disease 2019 (COVID-19), there is need for routine vaccination for both COVID-19 and influenza to reduce disease severity. Here, we prepared individual WPVs composed of formalin-inactivated SARS-CoV-2 WK 521 (Ancestral strain; Co WPV) or influenza virus [A/California/07/2009 (X-179A) (H1N1) pdm; Flu WPV] to produce a two-in-one Co/Flu WPV. Serum analysis from vaccinated mice revealed that a single dose of Co/Flu WPV induced antigen-specific neutralizing antibodies against both viruses, similar to those induced by either type of WPV alone. Following infection with either virus, mice vaccinated with Co/Flu WPV showed no weight loss, reduced pneumonia and viral titers in the lung, and lower gene expression of proinflammatory cytokines, as observed with individual WPV-vaccinated. Furthermore, a pentavalent vaccine (Co/qFlu WPV) comprising of Co WPV and quadrivalent influenza vaccine (qFlu WPV) was immunogenic and protected animals from severe COVID-19. These results suggest that a single dose of the two-in-one WPV provides efficient protection against SARS-CoV-2 and influenza virus infections with no evidence of vaccine interference in mice. We propose that concomitant vaccination with the two-in-one WPV can be useful for controlling both diseases.

Determinants of epidemic size and the impacts of lulls in seasonal influenza virus circulation

During the COVID-19 pandemic, levels of seasonal influenza virus circulation were unprecedentedly low, leading to concerns that a lack of exposure to influenza viruses, combined with waning antibody titres, could result in larger and/or more severe post-pandemic seasonal influenza epidemics. However, in most countries the first post-pandemic influenza season was not unusually large and/or severe. Here, based on an analysis of historical influenza virus epidemic patterns from 2002 to 2019, we show that historic lulls in influenza virus circulation had relatively minor impacts on subsequent epidemic size and that epidemic size was more substantially impacted by season-specific effects unrelated to the magnitude of circulation in prior seasons. From measurements of antibody levels from serum samples collected each year from 2017 to 2021, we show that the rate of waning of antibody titres against influenza virus during the pandemic was smaller than assumed in predictive models. Taken together, these results partially explain why the re-emergence of seasonal influenza virus epidemics was less dramatic than anticipated and suggest that influenza virus epidemic dynamics are not currently amenable to multi-season prediction.

Age-dependent influenza infection patterns and subtype circulation in Denmark, in seasons 2015/16 to 2021/22

BackgroundInfluenza was almost absent for 2 years following the implementation of strict public health measures to prevent the spread of SARS-CoV-2. The consequence of this on infections in different age groups is not yet known.AimTo describe the age groups infected with the influenza virus in 2021/22, the first post-pandemic influenza season in Denmark, compared with the previous six seasons, and subtypes circulating therein.MethodsInfection and hospitalisation incidences per season and age group were estimated from data in Danish registries. Influenza virus subtypes and lineages were available from samples sent to the National Influenza Centre at Statens Serum Institut.ResultsTest incidence followed a similar pattern in all seasons, being highest in 0-1-year-olds and individuals over 75 years, and lowest in 7-14-year-olds and young people 15 years to late twenties. When the influenza A virus subtypes A(H3N2) and A(H1N1)pdm09 co-circulated in seasons 2015/16 and 2017/18 to 2019/20, the proportion of A(H1N1)pdm09 was higher in 0-1-year-olds and lower in the over 85-year-olds  compared with the overall proportion of A(H1N1)pdm09 in these seasons. The proportion of A(H3N2) was higher in the over 85 years age group compared with the overall proportion of A(H3N2). The 2016/17 and 2021/22 seasons were dominated by A(H3N2) but differed in age-specific trends, with the over 85 years age group initiating the 2016/17 season, while the 2021/22 season was initiated by the 15-25-year-olds, followed by 7-14-year-olds.ConclusionThe 2021/22 influenza season had a different age distribution compared with pre-COVID-19 pandemic seasons.

Nowcasting and Forecasting Seasonal Influenza Epidemics - China, 2022-2023

Background

Seasonal influenza resurged in China in February 2023, causing a large number of hospitalizations. While influenza epidemics occurred across China during the coronavirus disease 2019 (COVID-19) pandemic, the relaxation of COVID-19 containment measures in December 2022 may have contributed to the spread of acute respiratory infections in winter 2022/2023.

Methods

Using a mathematical model incorporating influenza activity as measured by influenza-like illness (ILI) data for northern and southern regions of China, we reconstructed the seasonal influenza incidence from October 2015 to September 2019 before the COVID-19 pandemic. Using this trained model, we predicted influenza activities in northern and southern China from March to September 2023.

Results

We estimated the effective reproduction number R e as 1.08 [95% confidence interval ( CI): 0.51, 1.65] in northern China and 1.10 (95% CI: 0.55, 1.67) in southern China at the start of the 2022-2023 influenza season. We estimated the infection attack rate of this influenza wave as 18.51% (95% CI: 0.00%, 37.78%) in northern China and 28.30% (95% CI: 14.77%, 41.82%) in southern China.

Conclusions

The 2023 spring wave of seasonal influenza in China spread until July 2023 and infected a substantial number of people.

Co-evolution of immunity and seasonal influenza viruses

Seasonal influenza viruses cause recurring global epidemics by continually evolving to escape host immunity. The viral constraints and host immune responses that limit and drive the evolution of these viruses are increasingly well understood. However, it remains unclear how most of these advances improve the capacity to reduce the impact of seasonal influenza viruses on human health. In this Review, we synthesize recent progress made in understanding the interplay between the evolution of immunity induced by previous infections or vaccination and the evolution of seasonal influenza viruses driven by the heterogeneous accumulation of antibody-mediated immunity in humans. We discuss the functional constraints that limit the evolution of the viruses, the within-host evolutionary processes that drive the emergence of new virus variants, as well as current and prospective options for influenza virus control, including the viral and immunological barriers that must be overcome to improve the effectiveness of vaccines and antiviral drugs.

Resurgence of human metapneumovirus infection and influenza after three seasons of inactivity in the post-COVID-19 era in Hokkaido, Japan, 2022-2023

Following the coronavirus disease 2019 (COVID-19) outbreak in February 2020, incidences of various infectious diseases decreased notably in Hokkaido Prefecture, Japan. However, Japan began gradually easing COVID-19 infection control measures in 2022. Here, we conducted a survey of children hospitalized with human metapneumovirus (hMPV), influenza A and B, and respiratory syncytial virus infections in 18 hospitals across Hokkaido Prefecture, Japan, spanning from July 2019 to June 2023. From March 2020 to June 2022 (28 months), only 13 patients were hospitalized with hMPV, and two patients had influenza A. However, in October to November 2022, there was a re-emergence of hMPV infections, with a maximum of 27 hospitalizations per week. From July 2022 to June 2023 (12 months), the number of hMPV-related hospitalizations dramatically increased to 317 patients, with the majority aged 3-6 years (38.2%, [121/317]). Influenza A also showed an increase from December 2022, with a peak of 13 hospitalizations per week in March 2023, considerably fewer than the pre-COVID-19 outbreak in December 2019, when rates reached 45 hospitalizations per week. These findings suggest the possibility of observing more resurgences in infectious diseases in Japan after 2023 if infection control measures continue to be relaxed. Caution is needed in managing potential outbreaks.

Unraveling the association between vaccine attitude, vaccine conspiracies and self-reported side effects following COVID-19 vaccination among nurses and physicians in Jordan

Background

The negative impact of vaccine conspiracies is linked with negative health behavior. The aim of the current study was to examine the association between attitudes toward booster COVID-19, influenza, and monkeypox (mpox) vaccinations with post-COVID-19 vaccine side effects, vaccine conspiracies, and attitude towards mandatory vaccination among nurses and physicians in Jordan.

Methods

A structured closed-ended questionnaire was used to collect data on demographics, COVID-19 history, COVID-19 vaccine type and doses received, self-reported side effects post-COVID-19 vaccination, acceptance of booster COVID-19, seasonal influenza, and mpox vaccinations, attitudes towards mandatory vaccination, and beliefs in vaccine conspiracies.

Results

The study sample comprised a total of 341 participants. Acceptance of yearly booster COVID-19 vaccination was expressed by 46.6% of the sample, while 73.3% accepted seasonal influenza vaccination, and only 37.0% accepted mpox vaccination. A higher frequency of self-reported side effects following the first COVID-19 vaccine dose was associated with embrace of vaccine conspiracies and vaccine type. For the second vaccine dose, a higher frequency of self-reported side effects was associated with the embrace of vaccine conspiracies, older age, and affiliation to private sector. In multinomial logistic regression analyses, the lower embrace of vaccine conspiracies was associated with lower odds of reporting side effects post-COVID-19 vaccination. The lower embrace of vaccine conspiracies and favorable attitude towards mandatory vaccination were associated with the willingness to get COVID-19, influenza, and mpox vaccinations.

Conclusion

The study findings highlighted the negative impact of embracing vaccine conspiracies on health-seeking behavior among nurses and physicians. The findings indicated that the willingness to get vaccinated was associated with lower endorsement of vaccine conspiracies. Additionally, the lower embrace of vaccine conspiracies was associated with a lower frequency of self-reported side effects following COVID-19 vaccination. These results emphasize the importance of addressing vaccine misinformation and promoting accurate information to ensure optimal vaccine uptake and public health outcomes.

Enhancing breadth and durability of humoral immune responses in non-human primates with an adjuvanted group 1 influenza hemagglutinin stem antigen

Seasonal influenza vaccines must be updated annually and suboptimally protect against strains mismatched to the selected vaccine strains. We previously developed a subunit vaccine antigen consisting of a stabilized trimeric influenza A group 1 hemagglutinin (H1) stem protein that elicits broadly neutralizing antibodies. Here, we further optimized the stability and manufacturability of the H1 stem antigen (H1 stem v2, also known as INFLUENZA G1 mHA) and characterized its formulation and potency with different adjuvants in vitro and in animal models. The recombinant H1 stem antigen (50 µg) was administered to influenza-naïve non-human primates either with aluminum hydroxide [Al(OH)3] + NaCl, AS01B, or SLA-LSQ formulations at week 0, 8 and 34. These SLA-LSQ formulations comprised of varying ratios of the synthetic TLR4 agonist 'second generation synthetic lipid adjuvant' (SLA) with liposomal QS-21 (LSQ). A vaccine formulation with aluminum hydroxide or SLA-LSQ (starting at a 10:25 µg ratio) induced HA-specific antibodies and breadth of neutralization against a panel of influenza A group 1 pseudoviruses, comparable with vaccine formulated with AS01B, four weeks after the second immunization. A formulation with SLA-LSQ in a 5:2 μg ratio contained larger fused or aggregated liposomes and induced significantly lower humoral responses. Broadly HA stem-binding antibodies were detectable for the entire period after the second vaccine dose up to week 34, after which they were boosted by a third vaccine dose. These findings inform about potential adjuvant formulations in clinical trials with an H1 stem-based vaccine candidate.

A Digital Mask-Voiceprint System for Postpandemic Surveillance and Tracing Based on the STRONG Strategy

Lockdowns and border closures due to COVID-19 imposed mental, social, and financial hardships in many societies. Living with the virus and resuming normal life are increasingly being advocated due to decreasing virus severity and widespread vaccine coverage. However, current trends indicate a continued absence of effective contingency plans to stop the next more virulent variant of the pandemic. The COVID-19-related mask waste crisis has also caused serious environmental problems and virus spreads. It is timely and important to consider how to precisely implement surveillance for the dynamic clearance of COVID-19 and how to efficiently manage discarded masks to minimize disease transmission and environmental hazards. In this viewpoint, we sought to address this issue by proposing an appropriate strategy for intelligent surveillance of infected cases and centralized management of mask waste. Such an intelligent strategy against COVID-19, consisting of wearable mask sample collectors (masklect) and voiceprints and based on the STRONG (Spatiotemporal Reporting Over Network and GPS) strategy, could enable the resumption of social activities and economic recovery and ensure a safe public health environment sustainably.

Prevalence and associated outcomes of coinfection between SARS-CoV-2 and influenza: a systematic review and meta-analysis

OBJECTIVES

To estimate the prevalence of influenza coinfection in COVID-19 patients and investigate its association with severe clinical outcomes.

METHODS

We systematically searched the Web of Science, PubMed, Scopus, Embase, The Cochrane Library, and CNKI for studies published between January 01, 2020, and May 31, 2023. Meta-analysis was performed to estimate the pooled prevalence of coinfection and the impact on clinical outcomes. Systematic review registered in PROSPERO (CRD42023423113).

RESULTS

A total of 95 studies involving 62,107 COVID-19 patients were included. The pooled prevalence of coinfection with influenza virus was 2.45% (95% confidence interval [CI]: 1.67-3.58%), with a high proportion of influenza A. Compared with mono-infected patients (COVID-19 only), the odds ratio (OR) for severe outcomes (including intensive care unit admission [OR = 2.20, 95% CI: 1.68-2.87, P < 0.001], mechanical ventilation support [OR = 2.73, 95% CI: 1.46-5.10, P = 0.002], and mortality [OR = 2.92, 95% CI: 1.16-7.30, P = 0.022]) was significantly higher among patients coinfected influenza A.

CONCLUSION

Although the prevalence of coinfection is low, coinfected patients are at higher risk of severe outcomes. Enhanced identification of both viruses, as well as individualized treatment protocols for coinfection, are recommended to reduce the occurrence of serious disease outcomes in the future.

Resurgence of influenza during COVID-19 in Chongqing, China: A retrospective analysis

To better understand the trends of influenza and the impact of public health and social measures (PHSMs) implemented during the coronavirus disease 2019 (COVID-19) period in Chongqing, China. Data from the China Influenza Surveillance Information System from January 2017 to June 2022 were extracted. Epidemiological characteristics (influenza-like illness [ILI] and ILI%) and virological characteristics (influenza positive rate and circulating (sub)types) of influenza were described and compared between the pre-COVID-19 period and the COVID-19 period. Our survey showed that the implementation of PHSMs during the COVID-19 period had a positive impact on reducing influenza transmission. However, influenza activity resurged in 2021-2022 as the PHSMs were eased. Children under 5 years old constituted the highest proportion of ILI cases. The overall influenza positive rate was 23.70%, with a higher rate observed during the pre-COVID-19 period (31.55%) compared to the COVID-19 period (13.68%). Influenza virus subtypes co-circulated and the predominant subtype varied each year, with influenza A subtypes predominated in 2018/2019, while influenza B/Victoria lineage dominated in 2020/2021. PHSMs are effective measures to mitigate the spread of influenza. The findings underscore the need for bolstering monitoring systems, advocating influenza vaccination, and implementing practical PHSMs to strengthen prevention and control measures against influenza.

Epidemiology of Influenza-like Illness and Respiratory Viral Etiology in Adult Patients in Taiyuan City, Shanxi Province, China between 2018 and 2019

To determine the epidemiological status of influenza and understand the distribution of common respiratory viruses in adult patients with influenza-like illness (ILI) cases in Taiyuan City, Shanxi Province, China, epidemiological data between 2018 and 2019 were retrieved from the China Influenza Surveillance Information System, and two sentinel ILI surveillance hospitals were selected for sample collection. All specimens were screened for influenza virus (IFV) and the other 14 common respiratory viruses using real-time polymerase chain reaction. The results of the 2-year ILI surveillance showed that 26,205 (1.37%) of the 1,907,869 outpatients and emergency patients presented with ILI, with an average annual incidence of 297.75 per 100,000 individuals, and ILI cases were predominant in children <15 years (21,348 patients, 81.47%). Of the 2713 specimens collected from adult patients with ILI, the overall detection rate of respiratory viruses was 20.13%, with IFV being the most frequently detected (11.79%) and at a relatively lower rate than other respiratory viruses. Further subtype analysis indicated an alternating or mixed prevalence of H1N1 (2009), H3N2, Victoria, and Yamagata subtypes. This study provides a baseline epidemiological characterization of ILI and highlights the need for a nationwide detection and surveillance system for multiple respiratory pathogens.

Using artificial intelligence to improve public health: a narrative review

Artificial intelligence (AI) is a rapidly evolving tool revolutionizing many aspects of healthcare. AI has been predominantly employed in medicine and healthcare administration. However, in public health, the widespread employment of AI only began recently, with the advent of COVID-19. This review examines the advances of AI in public health and the potential challenges that lie ahead. Some of the ways AI has aided public health delivery are via spatial modeling, risk prediction, misinformation control, public health surveillance, disease forecasting, pandemic/epidemic modeling, and health diagnosis. However, the implementation of AI in public health is not universal due to factors including limited infrastructure, lack of technical understanding, data paucity, and ethical/privacy issues.

Impact of Nonpharmacological Interventions on Severe Acute Respiratory Infections in Children: From the National Surveillance Database

BACKGROUND

Nonpharmacological interventions (NPIs) reduce the incidence of respiratory infections. After NPIs imposed during the coronavirus disease 2019 pandemic ceased, respiratory infections gradually increased worldwide. However, few studies have been conducted on severe respiratory infections requiring hospitalization in pediatric patients. This study compares epidemiological changes in severe respiratory infections during pre-NPI, NPI, and post-NPI periods in order to evaluate the effect of that NPI on severe respiratory infections in children.

METHODS

We retrospectively studied data collected at 13 Korean sentinel sites from January 2018 to October 2022 that were lodged in the national Severe Acute Respiratory Infections (SARIs) surveillance database.

RESULTS

A total of 9,631 pediatric patients were admitted with SARIs during the pre-NPI period, 579 during the NPI period, and 1,580 during the post-NPI period. During the NPI period, the number of pediatric patients hospitalized with severe respiratory infections decreased dramatically, thus from 72.1 per 1,000 to 6.6 per 1,000. However, after NPIs ceased, the number increased to 22.8 per 1,000. During the post-NPI period, the positive test rate increased to the level noted before the pandemic.

CONCLUSION

Strict NPIs including school and daycare center closures effectively reduced severe respiratory infections requiring hospitalization of children. However, childcare was severely compromised. To prepare for future respiratory infections, there is a need to develop a social consensus on NPIs that are appropriate for children.

Clinical, epidemiological, and genomic characteristics of a seasonal influenza A virus outbreak in Beijing: A descriptive study

China experienced a severe influenza season that began at the end of February 2023. The aim of this post hoc analysis was to investigate the clinical, epidemiological, and genomic features of this outbreak in Beijing. The number of cases increased rapidly from the end of February and reached its peak in March, with 7262 confirmed cases included in this study. The median age was 33 years, and 50.3% of them were male. The average daily positive rate reached 69% during the peak period. The instantaneous reproduction number (Rt) showed a median of 2.1, exceeded 2.5 initially, and remaining above 1 for the following month. The most common symptoms were fever (75.0%), cough (51.0%), and expectoration (42.9%), with a median body temperature of 38.5°C (interquartile range 38-39). Eight clinical symptoms were more likely to be observed in cases with fever, with odds ratio greater than 1. Viral shedding time ranged from 3 to 25 days, with median of 7.5 days. The circulating viruses in Beijing mainly included H1N1pdm09 (clades 5a.2a and 5a.2a.1), following with H3N2 (clade 2a.2a.3a.1). The descriptive study suggests that influenza viruses in this influenza season had a higher transmissibility and longer shedding duration, with fever being the most common symptom.

The interplay between susceptibility and vaccine effectiveness control the timing and size of an emerging seasonal influenza wave in England

Relaxing social distancing measures and reduced level of influenza over the last two seasons may lead to a winter 2022 influenza wave in England. We used an established model for influenza transmission and vaccination to evaluate the rolled out influenza immunisation programme over October to December 2022. Specifically, we explored how the interplay between pre-season population susceptibility and influenza vaccine efficacy control the timing and the size of a possible winter influenza wave. Our findings suggest that susceptibility affects the timing and the height of a potential influenza wave, with higher susceptibility leading to an earlier and larger influenza wave while vaccine efficacy controls the size of the peak of the influenza wave. With pre-season susceptibility higher than pre-COVID-19 levels, under the planned vaccine programme an early influenza epidemic wave is possible, its size dependent on vaccine effectiveness against the circulating strain. If pre-season susceptibility is low and similar to pre-COVID levels, the planned influenza vaccine programme with an effective vaccine could largely suppress a winter 2022 influenza outbreak in England.

Assessing the Intense Influenza A(H1N1)pdm09 Epidemic and Vaccine Effectiveness in the Post-COVID Season in the Russian Federation

The COVID-19 pandemic had a profound impact on influenza activity worldwide. However, as the pandemic progressed, influenza activity resumed. Here, we describe the influenza epidemic of high intensity of the 2022-2023 season. The epidemic had an early start and peaked in week 51.2022. The extremely high intensity of the epidemic may have been due to a significant decrease in herd immunity. The results of PCR-testing of 220,067 clinical samples revealed that the influenza A(H1N1)pdm09 virus dominated, causing 56.4% of positive cases, while A(H3N2) influenza subtype accounted for only 0.6%, and influenza B of Victoria lineage-for 34.3%. The influenza vaccine was found to be highly effective, with an estimated effectiveness of 92.7% in preventing admission with laboratory-confirmed influenza severe acute respiratory illness (SARI) cases and 54.7% in preventing influenza-like illness/acute respiratory illness (ILI/ARI) cases due to antigenic matching of circulated viruses with influenza vaccine strains for the season. Full genome next-generation sequencing of 1723 influenza A(H1N1)pdm09 viruses showed that all of them fell within clade 6B.1A.5.a2; nine of them possessed H275Y substitution in the NA gene, a genetic marker of oseltamivir resistance. Influenza A(H3N2) viruses belonged to subclade 3C.2a1b.2a.2 with the genetic group 2b being dominant. All 433 influenza B viruses belonged to subclade V1A.3a.2 encoding HA1 substitutions A127T, P144L, and K203R, which could be further divided into two subgroups. None of the influenza A(H3N2) and B viruses sequenced had markers of resistance to NA inhibitors. Thus, despite the continuing circulation of Omicron descendant lineages, influenza activity has resumed in full force, raising concerns about the intensity of fore coming seasonal epidemics.

Associations between COVID-19 Vaccination and Behavioural Intention to Receive Seasonal Influenza Vaccination among Chinese Older Adults: A Population-Based Random Telephone Survey

During the Coronavirus Disease 2019 (COVID-19) pandemic, seasonal influenza remained a significant health threat for older adults. Seasonal influenza vaccination (SIV) is highly effective and safe for older adults. This study investigated the associations of COVID-19 vaccination, perceptions related to COVID-19 and SIV, with the behavioural intention to receive SIV among older adults in Hong Kong, China. A random telephone survey was conducted among 440 community-dwelling Hong Kong residents aged 65 years or above, between November 2021 and January 2022. Among the participants, 55.7% intended to receive SIV in the next year. After adjustment for significant background characteristics, concern about whether SIV and COVID-19 vaccination would negatively affect each other was associated with a lower intention to receive SIV, while a perceived higher risk of co-infection with COVID-19 and seasonal influenza was positively associated with the dependent variable. In addition, the perceived severe consequences of seasonal influenza, perceived benefits of SIV, received cues to action from doctors and participants' family members or friends, and the perception that more older people would receive SIV was associated with a higher behavioural intention. Future programmes promoting SIV among older adults should modify perceptions related to COVID-19 vaccination and SIV at the same time.

Robust immunity to influenza vaccination in haematopoietic stem cell transplant recipients following reconstitution of humoral and adaptive immunity

Objectives

Influenza causes significant morbidity and mortality, especially in high-risk populations. Although current vaccination regimens are the best method to combat annual influenza disease, vaccine efficacy can be low in high-risk groups, such as haematopoietic stem cell transplant (HSCT) recipients.

Methods

We comprehensively assessed humoral immunity, antibody landscapes, systems serology and influenza-specific B-cell responses, together with their phenotypes and isotypes, to the inactivated influenza vaccine (IIV) in HSCT recipients in comparison to healthy controls.

Results

Inactivated influenza vaccine significantly increased haemagglutination inhibition (HAI) titres in HSCT recipients, similar to healthy controls. Systems serology revealed increased IgG1 and IgG3 antibody levels towards the haemagglutinin (HA) head, but not to neuraminidase, nucleoprotein or HA stem. IIV also increased frequencies of total, IgG class-switched and CD21^loCD27⁺ influenza-specific B cells, determined by HA probes and flow cytometry. Strikingly, 40% of HSCT recipients had markedly higher antibody responses towards A/H3N2 vaccine strain than healthy controls and showed cross-reactivity to antigenically drifted A/H3N2 strains by antibody landscape analysis. These superior humoral responses were associated with a greater time interval after HSCT, while multivariant analyses revealed the importance of pre-existing immune memory. Conversely, in HSCT recipients who did not respond to the first dose, the second IIV dose did not greatly improve their humoral response, although 50% of second-dose patients reached a seroprotective HAI titre for at least one of vaccine strains.

Conclusions

Our study demonstrates efficient, although time-dependent, immune responses to IIV in HSCT recipients, and provides insights into influenza vaccination strategies targeted to immunocompromised high-risk groups.

Moderately Low Effectiveness of the Influenza Quadrivalent Vaccine: Potential Mismatch between Circulating Strains and Vaccine Strains

The annual seasonal influenza vaccination is the most effective way of preventing influenza illness and hospitalization. However, the effectiveness of influenza vaccines has always been controversial. Therefore, we investigated the ability of the quadrivalent influenza vaccine to induce effective protection. Here we report strain-specific influenza vaccine effectiveness (VE) against laboratory-confirmed influenza cases during the 2019/2020 season, characterized by the co-circulation of four different influenza strains. During 2019-2020, 778 influenza-like illness (ILI) samples were collected from 302 (39%) vaccinated ILI patients and 476 (61%) unvaccinated ILI patients in Riyadh, Saudi Arabia. VE was found to be 28% and 22% for influenza A and B, respectively. VE for preventing A(H3N2) and A(H1N1)pdm09 illness was 37.4% (95% CI: 43.7-54.3) and 39.2% (95% CI: 21.1-28.9), respectively. The VE for preventing influenza B Victoria lineage illness was 71.7% (95% CI: -0.9-3), while the VE for the Yamagata lineage could not be estimated due to the limited number of positive cases. The overall vaccine effectiveness was moderately low at 39.7%. Phylogenetic analysis revealed that most of the Flu A genotypes in our dataset clustered together, indicating their close genetic relatedness. In the post-COVID-19 pandemic, flu B-positive cases have reached three-quarters of the total number of influenza-positive cases, indicating a nationwide flu B surge. The reasons for this phenomenon, if related to the quadrivalent flu VE, need to be explored. Annual monitoring and genetic characterization of circulating influenza viruses are important to support Influenza surveillance systems and to improve influenza vaccine effectiveness.

Examining the Negative Sentiments Related to Influenza Vaccination from 2017 to 2022: An Unsupervised Deep Learning Analysis of 261,613 Twitter Posts

Several countries are witnessing significant increases in influenza cases and severity. Despite the availability, effectiveness and safety of influenza vaccination, vaccination coverage remains suboptimal globally. In this study, we examined the prevailing negative sentiments related to influenza vaccination via a deep learning analysis of public Twitter posts over the past five years. We extracted original tweets containing the terms 'flu jab', '#flujab', 'flu vaccine', '#fluvaccine', 'influenza vaccine', '#influenzavaccine', 'influenza jab', or '#influenzajab', and posted in English from 1 January 2017 to 1 November 2022. We then identified tweets with negative sentiment from individuals, and this was followed by topic modelling using machine learning models and qualitative thematic analysis performed independently by the study investigators. A total of 261,613 tweets were analyzed. Topic modelling and thematic analysis produced five topics grouped under two major themes: (1) criticisms of governmental policies related to influenza vaccination and (2) misinformation related to influenza vaccination. A significant majority of the tweets were centered around perceived influenza vaccine mandates or coercion to vaccinate. Our analysis of temporal trends also showed an increase in the prevalence of negative sentiments related to influenza vaccination from the year 2020 onwards, which possibly coincides with misinformation related to COVID-19 policies and vaccination. There was a typology of misperceptions and misinformation underlying the negative sentiments related to influenza vaccination. Public health communications should be mindful of these findings.

The impact of the COVID-19 pandemic on chlamydia infection in South Korea: a comparison between the pre-pandemic and during-pandemic periods

Background

Prior to COVID-19 pandemic, a yearly upward trajectory in the number of chlamydia infection cases was observed in South Korea. However, in response to the COVID-19 pandemic, Korea implemented several public health and social measures, which were shown to have an impact on the epidemiology of other infectious diseases. This study aimed to estimate the impact of the COVID-19 pandemic on the incidence and number of reported chlamydia infections in South Korea.

Methods

Using the monthly number of reported chlamydia infection data between 2017 and 2022, we compared the trends in the reported numbers, and the incidence rates (IR) of chlamydia infection stratified by demographic characteristics (sex, age group, and region) in the pre- and during COVID-19 pandemic period (January 2017-December 2019 and January 2020-December 2022).

Results

We observed an irregular downward trajectory in the number of chlamydia infection in the during-pandemic period. A 30% decrease in the total number of chlamydia infection was estimated in the during-pandemic compared to the pre-pandemic period, with the decrease greater among males (35%) than females (25%). In addition, there was a decrease in the cumulative incidence rate of the during COVID-19 pandemic period (IR: 0.43; 95% CI: 0.42-0.44) compared to the pre-pandemic period (IR: 0.60; 95% CI: 0.59-0.61).

Conclusions

We identified decrease in the number of chlamydia infection during COVID-19 pandemic which is likely due to underdiagnosis and underreporting for the infection. Therefore, strengthening surveillance for sexually transmitted infections including chlamydia is warranted for an effective and timely response in case of an unexpected rebound in the number of the infections.

Characteristics of Respiratory Syncytial Virus Infection in Hospitalized Children Before and During the COVID-19 Pandemic in Thailand

OBJECTIVES

This study compared the epidemiological and clinical manifestations of patients hospitalized with respiratory syncytial virus (RSV) infection before and during the coronavirus disease 2019 (COVID-19) pandemic at a tertiary care hospital in Chiang Mai Province, Thailand.

METHODS

This retrospective observational study utilized data from all cases of laboratory-confirmed RSV infection at Maharaj Nakorn Chiang Mai Hospital from January 2016 to December 2021. Differences in the clinical presentation of RSV infection before (2016 to 2019) and during (2020 to 2021) the COVID-19 pandemic were analyzed and compared.

RESULTS

In total, 358 patients hospitalized with RSV infections were reported from January 2016 to December 2021. During the COVID-19 pandemic, only 74 cases of hospitalized RSV infection were reported. Compared to pre-pandemic levels, the clinical presentations of RSV infection showed statistically significant decreases in fever on admission (p=0.004), productive cough (p=0.004), sputum (p=0.003), nausea (p=0.03), cyanosis (p=0.004), pallor (p&lt;0.001), diarrhea (p&lt;0.001), and chest pain (p<0.001). Furthermore, vigilant measures to prevent the spread of COVID-19, including lockdowns, also interrupted the RSV season in Thailand from 2020 to 2021.

CONCLUSIONS

The incidence of RSV infection was affected by the COVID-19 pandemic in Chiang Mai Province, Thailand, which also changed the clinical presentation and seasonal pattern of RSV infection in children.

Quantifying the rebound of influenza epidemics after the adjustment of zero-COVID policy in China

The coexistence of coronavirus disease 2019 (COVID-19) and seasonal influenza epidemics has become a potential threat to human health, particularly in China in the oncoming season. However, with the relaxation of nonpharmaceutical interventions (NPIs) during the COVID-19 pandemic, the rebound extent of the influenza activities is still poorly understood. In this study, we constructed a susceptible-vaccinated-infectious-recovered-susceptible (SVIRS) model to simulate influenza transmission and calibrated it using influenza surveillance data from 2018 to 2022. We projected the influenza transmission over the next 3 years using the SVIRS model. We observed that, in epidemiological year 2021-2022, the reproduction numbers of influenza in southern and northern China were reduced by 64.0 and 34.5%, respectively, compared with those before the pandemic. The percentage of people susceptible to influenza virus increased by 138.6 and 57.3% in southern and northern China by October 1, 2022, respectively. After relaxing NPIs, the potential accumulation of susceptibility to influenza infection may lead to a large-scale influenza outbreak in the year 2022-2023, the scale of which may be affected by the intensity of the NPIs. And later relaxation of NPIs in the year 2023 would not lead to much larger rebound of influenza activities in the year 2023-2024. To control the influenza epidemic to the prepandemic level after relaxing NPIs, the influenza vaccination rates in southern and northern China should increase to 53.8 and 33.8%, respectively. Vaccination for influenza should be advocated to reduce the potential reemergence of the influenza epidemic in the next few years.

Cessation of Face Mask Use after COVID-19 Vaccination in Patients with Diabetes: Prevalence and Determinants

Studies on the cessation of face mask use after a COVID-19 vaccine in patients with diabetes are not available, despite their greater predisposition to complications. We estimated the prevalence of cessation of face mask use after receiving the COVID-19 vaccine in patients with diabetes and identified which factor was most strongly associated with non-use. This was a cross-sectional study in patients with diabetes 18-70 years with at least one dose of vaccine against COVID-19 (n = 288). Participants were asked to respond face-to-face to a questionnaire in a primary care center. Descriptive statistics, chi-square tests, and multivariate binary logistic regression were used for analyzing the association between vulnerability, benefits, barriers, self-efficacy, vaccine expectations (independent variables), and cessation of use (dependent variable), controlling for sociodemographic, smoking, medical, vaccine, and COVID-19 history. The prevalence of cessation of face masks was 25.3% (95% CI 20.2, 30.5). Not feeling vulnerable to hospitalization increased the odds of non-use (adjusted OR = 3.3, 95% CI 1.2, 8.6), while perceiving benefits did the opposite (adjusted OR = 0.4, 95% CI 0.2, 0.9). The prevalence was low, and only two factors were associated with the cessation of face mask use after COVID-19 vaccination in patients with type 2 diabetes.

Predictors of Seasonal Influenza Vaccination Willingness among High-Risk Populations Three Years after the Onset of the COVID-19 Pandemic

High-risk populations are at increased risk of severe influenza-related illness, hospitalization, and death due to influenza. The aim of our study was to assess the willingness of high-risk populations to take the influenza vaccine for the 2022-2023 season, and to investigate the factors associated with such willingness. We conducted a cross-sectional study in Greece in September 2022 using a convenience sample. We considered demographic characteristics, COVID-19-related variables, resilience, social support, anxiety, depression, and COVID-19-related burnout as potential predictors. Among participants, 39.4% were willing to accept the seasonal influenza vaccine, 33.9% were unwilling, and 26.8% were hesitant. Multivariable analysis identified that increased age and increased family support were associated with increased influenza vaccination willingness. Moreover, participants that have received COVID-19 booster doses were more willing to accept the influenza vaccine. In contrast, adverse effects because of COVID-19 vaccination and exhaustion due to measures against COVID-19 reduced influenza vaccination willingness. We found that the intention of high-risk populations to receive the influenza vaccine was low. Our study contributes to an increased understanding of the factors that affect vaccination willingness. Public health authorities could use this information to update vaccination programs against influenza. Emphasis should be given on safety and effectiveness issues.

Editorial: Infectious Disease Epidemiology and Transmission Dynamics

Infectious diseases, such as COVID-19 [...].

Monitoring School Absenteeism for Influenza-Like Illness Surveillance: Systematic Review and Meta-analysis

Background

Influenza causes considerable disease burden each year, particularly in children. Monitoring school absenteeism has long been proposed as a surveillance tool of influenza activity in the community, but the practice of school absenteeism could be varying, and the potential of such usage remains unclear.

Objective

The aim of this paper is to determine the potential of monitoring school absenteeism as a surveillance tool of influenza.

Methods

We conducted a systematic review of the published literature on the relationship between school absenteeism and influenza activity in the community. We categorized the types of school absenteeism and influenza activity in the community to determine the correlation between these data streams. We also extracted this correlation with different lags in community surveillance to determine the potential of using school absenteeism as a leading indicator of influenza activity.

Results

Among the 35 identified studies, 22 (63%), 12 (34%), and 8 (23%) studies monitored all-cause, illness-specific, and influenza-like illness (ILI)–specific absents, respectively, and 16 (46%) used quantitative approaches and provided 33 estimates on the temporal correlation between school absenteeism and influenza activity in the community. The pooled estimate of correlation between school absenteeism and community surveillance without lag, with 1-week lag, and with 2-week lag were 0.44 (95% CI 0.34, 0.53), 0.29 (95% CI 0.15, 0.42), and 0.21 (95% CI 0.11, 0.31), respectively. The correlation between influenza activity in the community and ILI-specific absenteeism was higher than that between influenza activity in community all-cause absenteeism. Among the 19 studies that used qualitative approaches, 15 (79%) concluded that school absenteeism was in concordance with, coincided with, or was associated with community surveillance. Of the 35 identified studies, only 6 (17%) attempted to predict influenza activity in the community from school absenteeism surveillance.

Conclusions

There was a moderate correlation between school absenteeism and influenza activity in the community. The smaller correlation between school absenteeism and community surveillance with lag, compared to without lag, suggested that careful application was required to use school absenteeism as a leading indicator of influenza epidemics. ILI-specific absenteeism could monitor influenza activity more closely, but the required resource or school participation willingness may require careful consideration to weight against the associated costs. Further development is required to use and optimize the use of school absenteeism to predict influenza activity. In particular, the potential of using more advanced statistical models and validation of the predictions should be explored.

Surveillance of Severe Acute Respiratory Infection and Influenza Vaccine Effectiveness among Hospitalized Italian Adults, 2021/22 Season

Following an extremely low incidence of influenza during the first waves of the ongoing COVID-19 pandemic, the 2021/22 Northern Hemisphere winter season saw a resurgence of influenza virus circulation. The aim of this study was to describe epidemiology of severe acute respiratory infections (SARIs) among Italian adults and estimate the 2021/22 season influenza vaccine effectiveness. For this purpose, a test-negative case-control study was conducted in a geographically representative sample of Italian hospitals. Of 753 SARI patients analyzed, 2.5% (N = 19) tested positive for influenza, most of which belonged to the A(H3N2) subtype. Phylogenetic analysis showed that these belonged to the subclade 3C.2a1b.2a.2, which was antigenically different from the 2021/22 A(H3N2) vaccine component. Most (89.5%) cases were registered among non-vaccinated individuals, suggesting a protective effect of influenza vaccination. Due to a limited number of cases, vaccine effectiveness estimated through the Firth's penalized logistic regression was highly imprecise, being 83.4% (95% CI: 25.8-97.4%) and 83.1% (95% CI: 22.2-97.3%) against any influenza type A and A(H3N2), respectively. Exclusion of SARS-CoV-2-positive controls from the model did not significantly change the base-case estimates. Within the study limitations, influenza vaccination appeared to be effective against laboratory-confirmed SARI.

Coalition Shaping the Vaccination Landscape

In 2022, the National Program for Influenza Prevention coalition will have its 10th anniversary; it is one of Poland's oldest educational initiatives. The National Program for Influenza Prevention was initiated to prevent a further decline and promote influenza prevention in the A(H1N1) post-pandemic years. In this review, we summarize the structure and operational model of the coalition and identify core functional elements that make it a key non-governmental organization involved in the prophylactics of communicable diseases. The coalition-based organization can operate in a complex environment, such as vaccinations requiring scientific, economic, social, and psychological involvement, and communications with different groups. Anchored to the history of the National Program for Influenza Prevention, we review Poland's vaccination landscape changes from the last ten years.

Potential impacts of prolonged absence of influenza virus circulation on subsequent epidemics

Background

During the first two years of the COVID-19 pandemic, the circulation of seasonal influenza viruses was unprecedentedly low. This led to concerns that the lack of immune stimulation to influenza viruses combined with waning antibody titres could lead to increased susceptibility to influenza in subsequent seasons, resulting in larger and more severe epidemics.

Methods

We analyzed historical influenza virus epidemiological data from 2003-2019 to assess the historical frequency of near-absence of seasonal influenza virus circulation and its impact on the size and severity of subsequent epidemics. Additionally, we measured haemagglutination inhibition-based antibody titres against seasonal influenza viruses using longitudinal serum samples from 165 healthy adults, collected before and during the COVID-19 pandemic, and estimated how antibody titres against seasonal influenza waned during the first two years of the pandemic.

Findings

Low country-level prevalence of influenza virus (sub)types over one or more years occurred frequently before the COVID-19 pandemic and had relatively small impacts on subsequent epidemic size and severity. Additionally, antibody titres against seasonal influenza viruses waned negligibly during the first two years of the pandemic.

Interpretation

The commonly held notion that lulls in influenza virus circulation, as observed during the COVID-19 pandemic, will lead to larger and/or more severe subsequent epidemics might not be fully warranted, and it is likely that post-lull seasons will be similar in size and severity to pre-lull seasons.

Funding

European Research Council, Netherlands Organization for Scientific Research, Royal Dutch Academy of Sciences, Public Health Service of Amsterdam.

Research in context

Evidence before this study: During the first years of the COVID-19 pandemic, the incidence of seasonal influenza was unusually low, leading to widespread concerns of exceptionally large and/or severe influenza epidemics in the coming years. We searched PubMed and Google Scholar using a combination of search terms (i.e., "seasonal influenza", "SARS-CoV-2", "COVID-19", "low incidence", "waning rates", "immune protection") and critically considered published articles and preprints that studied or reviewed the low incidence of seasonal influenza viruses since the start of the COVID-19 pandemic and its potential impact on future seasonal influenza epidemics. We found a substantial body of work describing how influenza virus circulation was reduced during the COVID-19 pandemic, and a number of studies projecting the size of future epidemics, each positing that post-pandemic epidemics are likely to be larger than those observed pre-pandemic. However, it remains unclear to what extent the assumed relationship between accumulated susceptibility and subsequent epidemic size holds, and it remains unknown to what extent antibody levels have waned during the COVID-19 pandemic. Both are potentially crucial for accurate prediction of post-pandemic epidemic sizes.Added value of this study: We find that the relationship between epidemic size and severity and the magnitude of circulation in the preceding season(s) is decidedly more complex than assumed, with the magnitude of influenza circulation in preceding seasons having only limited effects on subsequent epidemic size and severity. Rather, epidemic size and severity are dominated by season-specific effects unrelated to the magnitude of circulation in the preceding season(s). Similarly, we find that antibody levels waned only modestly during the COVID-19 pandemic.Implications of all the available evidence: The lack of changes observed in the patterns of measured antibody titres against seasonal influenza viruses in adults and nearly two decades of epidemiological data suggest that post-pandemic epidemic sizes will likely be similar to those observed pre-pandemic, and challenge the commonly held notion that the widespread concern that the near-absence of seasonal influenza virus circulation during the COVID-19 pandemic, or potential future lulls, are likely to result in larger influenza epidemics in subsequent years.

Epidemiology and Transmission Dynamics of Infectious Diseases and Control Measures

The epidemiology and transmission dynamics of infectious diseases must be understood at the individual and community levels to improve public health decision-making for real-time and integrated community-based control strategies. Herein, we explore the epidemiological characteristics for assessing the impact of public health interventions in the community setting and their applications. Computational statistical methods could advance research on infectious disease epidemiology and accumulate scientific evidence of the potential impacts of pharmaceutical/nonpharmaceutical measures to mitigate or control infectious diseases in the community. Novel public health threats from emerging zoonotic infectious diseases are urgent issues. Given these direct and indirect mitigating impacts at various levels to different infectious diseases and their burdens, we must consider an integrated assessment approach, 'One Health', to understand the dynamics and control of infectious diseases.