The WHO global influenza surveillance and response system (GISRS)-A future perspective

Predicting influenza-like illness trends based on sentinel surveillance data in China from 2011 to 2019: A modelling and comparative study1

Background

Influenza is an acute respiratory infectious disease with a significant global disease burden. Additionally, the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions (NPIs) have introduced uncertainty to the spread of influenza. However, comparative studies on the performance of innovative models and approaches used for influenza prediction are limited. Therefore, this study aimed to predict the trend of influenza-like illness (ILI) in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance.

Methods

The generalized additive model (GAM), deep learning hybrid model based on Gate Recurrent Unit (GRU), and autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model were established to predict the trends of ILI 1-, 2-, 3-, and 4-week-ahead in Beijing, Tianjin, Shanxi, Hubei, Chongqing, Guangdong, Hainan, and the Hong Kong Special Administrative Region in China, based on sentinel surveillance data from 2011 to 2019. Three relevant metrics, namely, Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and R squared, were calculated to evaluate and compare the goodness of fit and robustness of the three models.

Results

Considering the MAPE, RMSE, and R squared values, the ARMA-GARCH model performed best, while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China. Additionally, the models' predictive performance declined as the weeks ahead increased. Furthermore, blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting.

Conclusions

Our study suggested that the ARMA-GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model. Therefore, in the future, the ARMA-GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones, thereby contributing to influenza control and prevention efforts.

Zoonotic spillover and viral mutations from low and middle-income countries: improving prevention strategies and bridging policy gaps

The increasing frequency of zoonotic spillover events and viral mutations in low and middle-income countries presents a critical global health challenge. Contributing factors encompass cultural practices like bushmeat consumption, wildlife trade for traditional medicine, habitat disruption, and the encroachment of impoverished settlements onto natural habitats. The existing "vaccine gap" in many developing countries exacerbates the situation by allowing unchecked viral replication and the emergence of novel mutant viruses. Despite global health policies addressing the root causes of zoonotic disease emergence, there is a significant absence of concrete prevention-oriented initiatives, posing a potential risk to vulnerable populations. This article is targeted at policymakers, public health professionals, researchers, and global health stakeholders, particularly those engaged in zoonotic disease prevention and control in low and middle-income countries. The article underscores the importance of assessing potential zoonotic diseases at the animal-human interface and comprehending historical factors contributing to spillover events. To bridge policy gaps, comprehensive strategies are proposed that include education, collaborations, specialized task forces, environmental sampling, and the establishment of integrated diagnostic laboratories. These strategies advocate simplicity and unity, breaking down barriers, and placing humanity at the forefront of addressing global health challenges. Such a strategic and mental shift is crucial for constructing a more resilient and equitable world in the face of emerging zoonotic threats.

Characterisation of novel influenza-derived HLA-B*18:01-restricted epitopes

Objectives

Seasonal influenza viruses cause roughly 650 000 deaths annually despite available vaccines. CD8+ T cells typically recognise influenza-derived peptides from internal structural and non-structural influenza proteins and are an attractive avenue for future vaccine design as they could reduce the severity of disease following infection with diverse influenza strains. CD8+ T cells recognise peptides presented by the highly polymorphic Human Leukocyte Antigens class I molecules (HLA-I). Each HLA-I variant has distinct peptide binding preferences, representing a significant obstacle for designing vaccines that elicit CD8+ T cell responses across broad populations. Consequently, the rational design of a CD8+ T cell-mediated vaccine would require the identification of highly immunogenic peptides restricted to a range of different HLA molecules.

Methods

Here, we assessed the immunogenicity of six recently published novel influenza-derived peptides identified by mass-spectrometry and predicted to bind to the prevalent HLA-B*18:01 molecule.

Results

Using CD8+ T cell activation assays and protein biochemistry, we showed that 3/6 of the novel peptides were immunogenic in several HLA-B*18:01+ individuals and confirmed their HLA-B*18:01 restriction. We subsequently compared CD8+ T cell responses towards the previously identified highly immunogenic HLA-B*18:01-restricted NP219 peptide. Using X-ray crystallography, we solved the first crystal structures of HLA-B*18:01 presenting immunogenic influenza-derived peptides. Finally, we dissected the first TCR repertoires specific for HLA-B*18:01 restricted pathogen-derived peptides, identifying private and restricted repertoires against each of the four peptides.

Conclusion

Overall the characterisation of these novel immunogenic peptides provides additional HLA-B*18:01-restricted vaccine targets derived from the Matrix protein 1 and potentially the non-structural protein and the RNA polymerase catalytic subunit of influenza viruses.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024

BACKGROUND

Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993.

OBJECTIVE

We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework.

METHODS

Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC.

RESULTS

We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval.

CONCLUSIONS

The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

[Importance of National Influenza Centers in the surveillance of highly pathogenic avian viruses. The time for One-Health is now]

Since 1996, the highly pathogenic avian influenza subtype A(H5N1) has been causing almost uninterrupted outbreaks in wild and domestic birds, as well as cases in humans with a mortality rate close to 50%. However, the years of greatest circulation have been precisely the years following the COVID-19 pandemic, in which several cases have been recorded in humans in places where they had never appeared before, in addition to multiple cases in wild, domestic and peri-domestic mammals, which raise some concern about the risk that the virus may jump to humans through chains of transmission of greater or lesser extent. The current outbreak of A(H5N1) shows us that the One-Health concept should be more alive than ever to join efforts between professionals from different sectors of human, animal and environmental health to avoid or minimize these risks, so that reference laboratories such as the National Influenza Centers have the human and material resources to provide rapid and relevant information in the shortest possible time before emergencies of this type. The diagnostic and monitoring tools to be used in these cases must be available for any eventuality, and going beyond the basic data must be an indispensable premise to be able to carry out a detailed monitoring that serves to limit outbreaks, limit the spread of the disease, and help in the design of future pandemic vaccines against avian viruses.

High pathogenicity avian influenza A (H5N1) clade 2.3.4.4b virus infection in a captive Tibetan black bear (Ursus thibetanus): investigations based on paraffin-embedded tissues, France, 2022

High pathogenicity avian influenza viruses (HPAIVs) H5Nx of clade 2.3.4.4b have been circulating increasingly in both wild and domestic birds in recent years. In turn, this has led to an increase in the number of spillover events affecting mammals. In November 2022, an HPAIV H5N1 caused an outbreak in a zoological park in the south of France, resulting in the death of a Tibetan black bear (Ursus thibetanus) and several captive and wild bird species. We detected the virus in various tissues of the bear and a wild black-headed gull (Chroicocephalus ridibundus) found dead in its enclosure using histopathology, two different in situ detection techniques, and next-generation sequencing, all performed on formalin-fixed paraffin-embedded tissues. Phylogenetic analysis performed on the hemagglutinin gene segment showed that bear and gull strains shared 99.998% genetic identity, making the bird strain the closest related strain. We detected the PB2 E627K mutation in minute quantities in the gull, whereas it predominated in the bear, which suggests that this mammalian adaptation marker was selected during the bear infection. Our results provide the first molecular and histopathological characterization of an H5N1 virus infection in this bear species.

IMPORTANCE

Avian influenza viruses are able to cross the species barrier between birds and mammals because of their high genetic diversity and mutation rate. Using formalin-fixed paraffin-embedded tissues, we were able to investigate a Tibetan black bear's infection by a high pathogenicity H5N1 avian influenza virus at the molecular, phylogenetic, and histological levels. Our results highlight the importance of virological surveillance programs in mammals and the importance of raising awareness among veterinarians and zookeepers of the clinical presentations associated with H5Nx virus infection in mammals.

Fighting flu: novel CD8+ T-cell targets are required for future influenza vaccines

Seasonal influenza viruses continue to cause severe medical and financial complications annually. Although there are many licenced influenza vaccines, there are billions of cases of influenza infection every year, resulting in the death of over half a million individuals. Furthermore, these figures can rise in the event of a pandemic, as seen throughout history, like the 1918 Spanish influenza pandemic (50 million deaths) and the 1968 Hong Kong influenza pandemic (~4 million deaths). In this review, we have summarised many of the currently licenced influenza vaccines available across the world and current vaccines in clinical trials. We then briefly discuss the important role of CD8+ T cells during influenza infection and why future influenza vaccines should consider targeting CD8+ T cells. Finally, we assess the current landscape of known immunogenic CD8+ T-cell epitopes and highlight the knowledge gaps required to be filled for the design of rational future influenza vaccines that incorporate CD8+ T cells.

Differential effects of microRNAs miR-21, miR-99 and miR-145 on lung regeneration and inflammation during recovery from influenza pneumonia

In a mouse model of influenza pneumonia, we previously documented that proliferating alveolar type II (AT2) cells are the major stem cells involved in early lung recovery. Profiling of microRNAs revealed significant dysregulation of specific ones, including miR-21 and miR-99a. Moreover, miR-145 is known to exhibit antagonism to miR-21. This follow-up study investigated the roles of microRNAs miR-21, miR-99a, and miR-145 in the murine pulmonary regenerative process and inflammation during influenza pneumonia. Inhibition of miR-21 resulted in severe morbidity, and in significantly decreased proliferating AT2 cells due to impaired transition from innate to adaptive immune responses. Knockdown of miR-99a culminated in moderate morbidity, with a significant increase in proliferating AT2 cells that may be linked to PTEN downregulation. In contrast, miR-145 antagonism did not impact morbidity nor the proliferating AT2 cell population, and was associated with downregulation of TNF-alpha, IL1-beta, YM1, and LY6G. Hence, a complex interplay exists between expression of specific miRNAs, lung regeneration, and inflammation during recovery from influenza pneumonia. Inhibition of miR-21 and miR-99a (but not miR-145) can lead to deleterious cellular and molecular effects on pulmonary repair and inflammatory processes during influenza pneumonia.

Optimizing ancestral trait reconstruction of large HIV Subtype C datasets through multiple-trait subsampling

Large datasets along with sampling bias represent a challenge for phylodynamic reconstructions, particularly when the study data are obtained from various heterogeneous sources and/or through convenience sampling. In this study, we evaluate the presence of unbalanced sampled distribution by collection date, location, and risk group of human immunodeficiency virus Type 1 Subtype C using a comprehensive subsampling strategy and assess their impact on the reconstruction of the viral spatial and risk group dynamics using phylogenetic comparative methods. Our study shows that a most suitable dataset for ancestral trait reconstruction can be obtained through subsampling by all available traits, particularly using multigene datasets. We also demonstrate that sampling bias is inflated when considerable information for a given trait is unavailable or of poor quality, as we observed for the trait risk group. In conclusion, we suggest that, even if traits are not well recorded, including them deliberately optimizes the representativeness of the original dataset rather than completely excluding them. Therefore, we advise the inclusion of as many traits as possible with the aid of subsampling approaches in order to optimize the dataset for phylodynamic analysis while reducing the computational burden. This will benefit research communities investigating the evolutionary and spatio-temporal patterns of infectious diseases.

Old and new aspects of influenza

Influenza is a classic infectious disease that, through the continuous variation of the viruses that produce it, imposes new challenges that we must solve as quickly as possible. The COVID-19 pandemic has substantially modified the behavior of influenza and other respiratory viruses, and in the coming years we will have to coexist with a new pathogen that will probably interact with existing pathogens in a way that we cannot yet glimpse. However, knowledge prior to the pandemic allows us to focus on the aspects that must be modified to make influenza an acceptable challenge for the future. In this review, emphasis is placed on the most relevant aspects of epidemiology, disease burden, diagnosis, and vaccine prevention, and how scientific and clinical trends in these aspects flow from the previously known to future challenges.

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.

Understanding the divergent evolution and epidemiology of H3N8 influenza viruses in dogs and horses

Cross-species virus transmission events can lead to dire public health emergencies in the form of epidemics and pandemics. One example in animals is the emergence of the H3N8 equine influenza virus (EIV), first isolated in 1963 in Miami, FL, USA, after emerging among horses in South America. In the early 21st century, the American lineage of EIV diverged into two 'Florida' clades that persist today, while an EIV transferred to dogs around 1999 and gave rise to the H3N8 canine influenza virus (CIV), first reported in 2004. Here, we compare CIV in dogs and EIV in horses to reveal their host-specific evolution, to determine the sources and connections between significant outbreaks, and to gain insight into the factors controlling their different evolutionary fates. H3N8 CIV only circulated in North America, was geographically restricted after the first few years, and went extinct in 2016. Of the two EIV Florida clades, clade 1 circulates widely and shows frequent transfers between the USA and South America, Europe and elsewhere, while clade 2 was globally distributed early after it emerged, but since about 2018 has only been detected in Central Asia. Any potential zoonotic threat of these viruses to humans can only be determined with an understanding of its natural history and evolution. Our comparative analysis of these three viral lineages reveals distinct patterns and rates of sequence variation yet with similar overall evolution between clades, suggesting epidemiological intervention strategies for possible eradication of H3N8 EIV.

Influenza vaccine viruses and the development of seasonal vaccines: A Japanese perspective

In Japan, the Ministry of Health, Labour and Welfare (MHLW) designates one specific virus strain for each component of the quadrivalent seasonal influenza vaccine, and four domestic manufacturers produce egg-based influenza vaccines with the same formulation (inactivated, split-virus) using uniform vaccine strains. Thus, discussions of the development of effective seasonal influenza vaccines so far has focused solely on the antigenic match between the vaccine strains and epidemic viruses. However, in 2017, the Japanese selection system of vaccine viruses demonstrated that even a candidate vaccine virus that is antigenically similar to the predicted circulating viruses is not necessarily suitable for vaccine production, given lower productivity of the vaccine. Taking this experience into account, the MHLW reformed the scheme of vaccine strain selection in 2018, and instructed the Vaccine Epidemiology Research Group created by the MHLW to probe how the virus strains for the seasonal influenza vaccine should be selected in Japan. In this context, a symposium, entitled "Issues of the Present Seasonal Influenza Vaccines and Future Prospects", was held as part of the 22nd Annual Meeting of the Japanese Society for Vaccinology in 2018, and subjects related to the influenza vaccine viruses were discussed among relevant administrators, manufacturers, and researchers. This report summarizes the presentations given at that symposium in order to convey the present scheme of vaccine virus selection, the evaluation of the resulting vaccines, and the efforts at new vaccine formulation in Japan. Notably, from March 2022, the MHLW has launched a discussion of the merits of the seasonal influenza vaccines produced by foreign manufacturers.

A framework for seroepidemiologic investigations in future pandemics: insights from an evaluation of WHO's Unity Studies initiative

BACKGROUND

The WHO Unity Studies initiative supports countries, especially low- and middle-income countries (LMICs), in conducting seroepidemiologic studies for rapidly informing responses to the COVID-19 pandemic. Ten generic study protocols were developed which standardized epidemiologic and laboratory methods. WHO provided technical support, serological assays and funding for study implementation. An external evaluation was conducted to assess (1) the usefulness of study findings in guiding response strategies, (2) management and support to conduct studies and (3) capacity built from engagement with the initiative.

METHODS

The evaluation focused on the three most frequently used protocols, namely first few cases, household transmission and population-based serosurvey, 66% of 339 studies tracked by WHO. All 158 principal investigators (PIs) with contact information were invited to complete an online survey. A total of 19 PIs (randomly selected within WHO regions), 14 WHO Unity focal points at the country, regional and global levels, 12 WHO global-level stakeholders and eight external partners were invited to be interviewed. Interviews were coded in MAXQDA™, synthesized into findings and cross-verified by a second reviewer.

RESULTS

Among 69 (44%) survey respondents, 61 (88%) were from LMICs. Ninety-five percent gave positive feedback on technical support, 87% reported that findings contributed to COVID-19 understanding, 65% to guiding public health and social measures, and 58% to guiding vaccination policy. Survey and interview group responses showed that the main technical barriers to using study findings were study quality, variations in study methods (challenge for meta-analysis), completeness of reporting study details and clarity of communicating findings. Untimely study findings were another barrier, caused by delays in ethical clearance, receipt of serological assays and approval to share findings. There was strong agreement that the initiative created equitable research opportunities, connected expertise and facilitated study implementation. Around 90% of respondents agreed the initiative should continue in the future.

CONCLUSIONS

The Unity Studies initiative created a highly valued community of practice, contributed to study implementation and research equity, and serves as a valuable framework for future pandemics. To strengthen this platform, WHO should establish emergency-mode procedures to facilitate timeliness and continue to build capacity to rapidly conduct high-quality studies and communicate findings in a format friendly to decision-makers.

The impact of the SARS-CoV-2 pandemic on global influenza surveillance: Insights from 18 National Influenza Centers based on a survey conducted between November 2021 and March 2022

Background

National Influenza Centers (NICs) have played a crucial role in the surveillance of SARS-CoV-2. The FluCov project, covering 22 countries, was initiated to monitor the impact of the SARS-CoV-2 pandemic on influenza activity.

Methods

This project consisted of an epidemiological bulletin and NIC survey. The survey, designed to assess the impact of the pandemic on the influenza surveillance system, was shared with 36 NICs located across 22 countries. NICs were invited to reply between November 2021 and March 2022.

Results

We received 18 responses from NICs in 14 countries. Most NICs (76%) indicated that the number of samples tested for influenza decreased. Yet, many NICs (60%) were able to increase their laboratory testing capacity and the "robustness" (e.g., number of sentinel sites) (59%) of their surveillance systems. In addition, sample sources (e.g., hospital or outpatient setting) shifted. All NICs reported a higher burden of work following the onset of the pandemic, with some NICs hiring additional staff or partial outsourcing to other institutes or departments. Many NICs anticipate the future integration of SARS-CoV-2 surveillance into the existing respiratory surveillance system.

Discussion

The survey shows the profound impact of SARS-CoV-2 on national influenza surveillance in the first 27 months of the pandemic. Surveillance activities were temporarily disrupted, whilst priority was given to SARS-CoV-2. However, most NICs have shown rapid adaptive capacity underlining the importance of strong national influenza surveillance systems. These developments have the potential to benefit global respiratory surveillance in the years to come; however, questions about sustainability remain.

The global region-specific epidemiologic characteristics of influenza: World Health Organization FluNet data from 1996 to 2021

OBJECTIVES

This study aimed to investigate region-specific epidemiologic characteristics of influenza and influenza transmission zones (ITZs).

METHODS

Weekly influenza surveillance data of 156 countries from 1996 to 2021 were obtained using FluNet. Joinpoint regression was used to describe global influenza virus trends, and clustering analyses were used to classify the ITZs.

RESULTS

The global median average positive rate for total influenza virus was 16.19% (interquartile range: 11.62-25.70%). Overall, three major subtypes (influenza H1, H3, and B viruses) showed alternating epidemics. Notably, the proportion of influenza B viruses increased significantly from July 2020 to June 2021, reaching 62.66%. The primary peaks of influenza virus circulation in the north were earlier than those in the south. Global influenza virus circulation was significantly characterized by seven ITZs, including "Northern America" (primary peak: week 10), "Eastern & Southern-Asia" (primary peak: week 10), "Europe" (primary peak: week 11), "Asia-Europe" (primary peak: week 12), "Southern-America" (primary peak: week 30), "Oceania-Melanesia-Polynesia" (primary peak: week 39), and "Africa" (primary peak: week 46).

CONCLUSION

Global influenza virus circulation was significantly characterized by seven ITZs that could be applied to influenza surveillance and warning.

The effects of the COVID-19 pandemic on community respiratory virus activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused substantial global morbidity and deaths, leading governments to turn to non-pharmaceutical interventions to slow down the spread of infection and lessen the burden on health care systems. These policies have evolved over the course of the COVID-19 pandemic, including after the availability of COVID-19 vaccines, with regional and country-level differences in their ongoing use. The COVID-19 pandemic has been associated with changes in respiratory virus infections worldwide, which have differed between virus types. Reductions in respiratory virus infections, including by influenza virus and respiratory syncytial virus, were most notable at the onset of the COVID-19 pandemic and continued in varying degrees through subsequent waves of SARS-CoV-2 infections. The decreases in community infection burden have resulted in reduced hospitalizations and deaths associated with non-SARS-CoV-2 respiratory infections. Respiratory virus evolution relies on the maintaining of a diverse genetic pool, but evidence of genetic bottlenecking brought on by case reduction during the COVID-19 pandemic has resulted in reduced genetic diversity of some respiratory viruses, including influenza virus. By describing the differences in these changes between viral species across different geographies over the course of the COVID-19 pandemic, we may better understand the complex factors involved in community co-circulation of respiratory viruses.

Criteria for selecting sentinel unit locations in a surveillance system for vector-borne disease: A decision tool

Objectives

With vector-borne diseases emerging across the globe, precipitated by climate change and other anthropogenic changes, it is critical for public health authorities to have well-designed surveillance strategies in place. Sentinel surveillance has been proposed as a cost-effective approach to surveillance in this context. However, spatial design of sentinel surveillance system has important impacts on surveillance outcomes, and careful selection of sentinel unit locations is therefore an essential component of planning.

Methods

A review of the available literature, based on the realist approach, was used to identify key decision issues for sentinel surveillance planning. Outcomes of the review were used to develop a decision tool, which was subsequently validated by experts in the field.

Results

The resulting decision tool provides a list of criteria which can be used to select sentinel unit locations. We illustrate its application using the case example of designing a national sentinel surveillance system for Lyme disease in Canada.

Conclusions

The decision tool provides researchers and public health authorities with a systematic, evidence-based approach for planning the spatial design of sentinel surveillance systems, taking into account the aims of the surveillance system and disease and/or context-specific considerations.

Emergence of infectious diseases and role of advanced nanomaterials in point-of-care diagnostics: a review

Infectious outbreaks are the foremost global public health concern, challenging the current healthcare system, which claims millions of lives annually. The most crucial way to control an infectious outbreak is by early detection through point-of-care (POC) diagnostics. POC diagnostics are highly advantageous owing to the prompt diagnosis, which is economical, simple and highly efficient with remote access capabilities. In particular, utilization of nanomaterials to architect POC devices has enabled highly integrated and portable (compact) devices with enhanced efficiency. As such, this review will detail the factors influencing the emergence of infectious diseases and methods for fast and accurate detection, thus elucidating the underlying factors of these infections. Furthermore, it comprehensively highlights the importance of different nanomaterials in POCs to detect nucleic acid, whole pathogens, proteins and antibody detection systems. Finally, we summarize findings reported on nanomaterials based on advanced POCs such as lab-on-chip, lab-on-disc-devices, point-of-action and hospital-on-chip. To this end, we discuss the challenges, potential solutions, prospects of integrating internet-of-things, artificial intelligence, 5G communications and data clouding to achieve intelligent POCs.

Influenza During the 2010-2020 Decade in the United States: Seasonal Outbreaks and Vaccine Interventions

The 10 years between the last influenza pandemic and start of the severe acute respiratory syndrome coronavirus 2 pandemic have been marked by great advances in our ability to follow influenza occurrence and determine vaccine effectiveness (VE), largely based on widespread use of the polymerase chain reaction assay. We examine the results, focusing mainly on data from the United States and inactivated vaccines. Surveillance has expanded, resulting in increased ability to characterize circulating viruses and their impact. The surveillance has often confirmed previous observations on timing of outbreaks and age groups affected, which can now be examined in greater detail. Selection of strains for vaccines is now based on enhanced viral characterization using immunologic, virologic, and computational techniques not previously available. Vaccine coverage has been largely stable, but VE has remained modest and, in some years, very low. We discuss ways to improve VE based on existing technology while we work toward supraseasonal vaccines.

Resurgence of Influenza Circulation in the Russian Federation during the Delta and Omicron COVID-19 Era

Influenza circulation was substantially reduced after March 2020 in the European region and globally due to the wide introduction of non-pharmaceutical interventions (NPIs) against COVID-19. The virus, however, has been actively circulating in natural reservoirs. In summer 2021, NPIs were loosened in Russia, and influenza activity resumed shortly thereafter. Here, we summarize the epidemiological and virological data on the influenza epidemic in Russia in 2021–2022 obtained by the two National Influenza Centers. We demonstrate that the commonly used baseline for acute respiratory infection (ARI) is no longer sufficiently sensitive and BL for ILI incidence was more specific for early recognition of the epidemic. We also present the results of PCR detection of influenza, SARS-CoV-2 and other respiratory viruses as well as antigenic and genetic analysis of influenza viruses. Influenza A(H3N2) prevailed this season with influenza B being detected at low levels at the end of the epidemic. The majority of A(H3N2) viruses were antigenically and genetically homogenous and belonged to the clade 3C.2a1b.2a.2 of the vaccine strain A/Darwin/9/2021 for the season 2022–2023. All influenza B viruses belonged to the Victoria lineage and were similar to the influenza B/Austria/1359417/2021 virus. No influenza A(H1N1)pdm09 and influenza B/Yamagata lineage was isolated last season.

Genomic Epidemiology of Seasonal Influenza Circulation in China During Prolonged Border Closure from 2020 to 2021

China experienced a resurgence of seasonal influenza activity throughout 2021 despite intermittent control measures and prolonged international border closure. We show genomic evidence for multiple A(H3N2), A(H1N1), and B/Victoria transmission lineages circulating over 3 years, with the 2021 resurgence mainly driven by two B/Victoria clades. Phylodynamic analysis revealed unsampled ancestry prior to widespread outbreaks in December 2020, showing that influenza lineages can circulate cryptically under non-pharmaceutical interventions enacted against COVID-19. Novel haemagglutinin gene mutations and altered age profiles of infected individuals were observed, and Jiangxi province was identified as a major source for nationwide outbreaks. Following major holiday periods, fluctuations in the effective reproduction number were observed, underscoring the importance of influenza vaccination prior to holiday periods or travel. Extensive heterogeneity in seasonal influenza circulation patterns in China determined by historical strain circulation indicates that a better understanding of demographic patterns is needed for improving effective controls.

Immunogenicity and safety of an egg culture-based quadrivalent inactivated non-adjuvanted subunit influenza vaccine in subjects ≥3 years: A randomized, multicenter, double-blind, active-controlled phase III, non-inferiority trial

Subunit influenza vaccine only formulated with surface antigen proteins has better safety profiles relative to split-virion influenza vaccine. Compared to the traditional quadrivalent split-virion influenza vaccine, a novel quadrivalent subunit influenza vaccine is urgently needed in China. We completed a phase 3, randomized, double-blind, active-controlled, non-inferiority clinical study at two sites in Henan Province, China. Eligible volunteers were split into four age cohorts (3-8 years, 9-17 years, 18-64 years, and ≥ 65 years, based on their dates of birth) and randomly assigned (1:1) to the subunit and the split-virion ecNAIIV4 groups. All volunteers were intramuscularly administered a single vaccine dose at baseline, and children aged 3-8 years received a boosting dose at day 28. And the immune response was evaluated by measuring hemagglutinin-inhibition antibody titers against the four vaccine strains in blood samples. Safety profiles had nonsignificant differences between the study groups in ≥ 3 years cohort. Most adverse reactions post-vaccination, both local and systemic, were mild to moderate and resolved within 3 days. And no serious adverse events occurred. The immunogenicity of the trial vaccine was non-inferior to the comparator. Further, a two-dose vaccine series can provide better seroprotection than that of a one-dose series in children aged 3-8 years, with clinically acceptable safety profiles. Clinical Trials Registration. ChiCTR2100049934.

Severe Acute Respiratory Infection Surveillance in Brazil: the Role of Public, Private, and Philanthropic Health Care Units

Epidemiological surveillance and notification of respiratory infections are important for management and control of epidemics and pandemics. Fact-based decisions, like social distancing policies and preparation of hospital beds, are taken based on several factors, including case numbers; hence, health authorities need quick access to reliable and well-analysed data. We aimed to analyse the role of the Brazilian public health system in the notification and hospitalization of patients with severe acute respiratory infection (SARI). Data of SARI cases in Brazil (2013–20) were obtained from SIVEP-Gripe platform, and legal status of each healthcare unit (HCU) responsible for case notification and hospitalization was obtained from the National Registry of Health Facilities (CNES) database. HCUs that are part of the hospital network were classified as ‘Public Administration’, ‘Business Entities’, ‘Philanthropic Entities’ or ‘Individuals’. SARI notification data from Brazilian macro-regions (North, Northeast, Midwest, Southeast and South) were analysed and compared between administrative spheres. This study reveals that hospitalizations due to SARI increased significantly in Brazil during the coronavirus disease 2019 (COVID-19) pandemic, especially in HCUs of Public Administration. In the Southeast and South, where incidence of SARI is high, philanthropic HCUs also contribute to hospitalization of SARI cases and attend up to 7.4% of the cases notified by the Public Administration. The number of cases is usually lower in other regions, but in 2020 the Northeast showed more hospitalizations than the South. In the South, SARI season occurs later; however, in 2020, an early peak was observed because of COVID-19. Notably, the contribution of each administrative sphere that manages hospital networks in Brazil in the control and management of SARI varies between regions. Our approach will allow managers to assess the use of public resources, given that there are different profiles of healthcare in each region of Brazil and that the public health system has a major role in notifying and attending SARI cases.

Trends in Influenza Infections in Three States of India from 2015-2021: Has There Been a Change during COVID-19 Pandemic?

The COVID-19 pandemic and public health response to the pandemic has caused huge setbacks in the management of other infectious diseases. In the present study, we aimed to (i) assess the trends in numbers of samples from patients with influenza-like illness and severe acute respiratory syndrome tested for influenza and the number and proportion of cases detected from 2015−2021 and (ii) examine if there were changes during the COVID-19 period (2020−2021) compared to the pre-COVID-19 period (2015−2019) in three states of India. The median (IQR) number of samples tested per month during the pre-COVID-19 period was 653 (395−1245), compared to 27 (11−98) during the COVID-19 period (p value < 0.001). The median (IQR) number of influenza cases detected per month during the pre-COVID-19 period was 190 (113−372), compared to 29 (27−30) during the COVID-19 period (p value < 0.001). Interrupted time series analysis (adjusting for seasonality and testing charges) confirmed a significant reduction in the total number of samples tested and influenza cases detected during the COVID-19 period. However, there was no change in the influenza positivity rate between pre-COVID-19 (29%) and COVID-19 (30%) period. These findings suggest that COVID-19-related disruptions, poor health-seeking behavior, and overburdened health systems might have led to a reduction in reported influenza cases rather than a true reduction in disease transmission.

Rate of diagnosed seasonal influenza in children with influenza-like illness: A cross-sectional study

Introduction

Although influenza surveillance systems have been used to monitor influenza epidemics, these systems generally evaluate diagnostic information obtained from medical institutions and they do not include patients who have not been examined. In contrast, community based epidemiological studies target people with influenza-like illness (ILI) that self-reported influenza-like symptoms whether they have medical examinations or not. Because the criteria for influenza surveillance systems and ILI differ, there is a gap between them. The purpose of this study was to clarify this gap using school-based survey data.

Methods

Questionnaires about both ILI and the influenza diagnosis history during the 2018/19 season were administered to the guardians of 11,684 elementary schoolchildren in a single city in Japan. Based on their responses, a Bayesian model was constructed to estimate the probability of infection, ILI onset, and diagnosis at medical institutions.

Results

Responses were obtained from guardians of 10,309 children (88.2%). Of these, 3,380 children (32.8%) had experienced ILI, with 2,380 (23.1%) diagnosed as influenza at a medical institution. Bayesian estimation showed that the probability of influenza cases being diagnosed among ILI symptomatic children was 70% (95% credible interval, 69–71%). Of the infected children, 5% were without ILI symptoms, with 11% of these patients diagnosed with influenza.

Conclusions

This epidemiological study clarified the proportion gap between ILI and influenza diagnosis among schoolchildren. These results may help to establish epidemic control measures and secure sufficient medical resources.

Global respiratory virus surveillance: strengths, gaps, and way forward

Current situation

The global influenza surveillance and response system (GISRS), coordinated by the World Health Organization (WHO), is a global framework for surveillance of influenza and other respiratory viruses, data collection, laboratory capacity building, genomic data submission and archival, standardization, and calibration of reagents and vaccine strains, production of seasonal influenza vaccines and creating a facilitatory regulatory environment for the same.

Gaps

WHO-designated national influenza centers (NICs) are entrusted with establishing surveillance in their respective countries. National and subnational surveillance remains weak in most parts of the world because of varying capacities of the NICs, lack of funds, poor human and veterinary surveillance mechanisms, lack of intersectoral coordination, and varying commitments of the local government.

Way forward

As influenza viruses have a wide variety of nonhuman hosts, it is critical to strengthen surveillance at local levels for timely detection of untypable or novel strains with potential to cause epidemics or pandemics. In this article, we have proposed possible strategies to strengthen and expand local capacities for respiratory virus surveillance through the designated NICs of the WHO.

Dynamics of influenza-like illness under urbanization procedure and COVID-19 pandemic in the sub-center of Beijing during 2013-2021

Influenza‐like illness (ILI) varies in intensity year by year, generally keeping a stable pattern except for great changes of its epidemic pattern. Of the most impacting factors, urbanization has been suggested as shaping the intensity of influenza epidemics. Besides, growing evidence indicates the nonpharmaceutical interventions (NPIs) to severe acute respiratory syndrome coronavirus 2 offer great advantages in controlling infectious diseases. The present study aimed to evaluate the impact of urbanization and NPIs on the dynamic of ILI in Tongzhou, Beijing, during January 2013 to March 2021. ILI epidemiological surveillance data in Tongzhou district were obtained from Beijing Influenza Surveillance Network and separated into three periods of urbanization and four intervals of coronavirus disease 2019 pandemic. Standardized average incidence rates of ILI in each separate stages were calculated and compared by using Wilson method and time series model of seasonal ARIMA. Influenza seasonal outbreaks showed similar epidemic size and intensity before urbanization during 2013–2016. Increased ILI activity was found during the process of Tongzhou's urbanization during 2017–2019, with the rate difference of 2.48 (95% confidence interva [CI]: 2.44, 2.52) and the rate ratio of 1.75 (95% CI: 1.74, 1.76) of ILI incidence between preurbanization and urbanization periods. ILI activity abruptly decreased from the beginning of 2020 and kept at the bottom level almost in every epidemic interval. The top decrease in ILI activity by NPIs was shown in 5–14 years group in 2020–2021 influenza season, as 92.2% (95% CI: 78.3%, 95.2%). The results indicated that both urbanization and NPIs interrupted the epidemic pattern of ILI. We should pay more attention to public health when facing increasing population density, human contact, population mobility, and migration in the process of urbanization. NPIs and influenza vaccination should be implemented as necessary measures to protect people from common infectious diseases like ILI.

An Implementation Strategy to Develop Sustainable Surveillance Activities Through Adoption of a Target Operating Model

The increasing threat of emerging and re-emerging pathogens calls for a shared vision toward developing and maintaining global surveillance mechanisms to enable rapid characterization of pathogens, a foundational requirement for effective outbreak response. Efforts establishing new surveillance programs in low- and middle-income countries (LMICs) have repeatedly led to siloed systems that prove unsustainable or ineffective due to narrowly focused approaches, competing priorities, or lack of resourcing. Barriers inherent to LMICs, such as resource limitations, workforce strain, unreliable supply chains, and lack of enduring champions exacerbate implementation and sustainability challenges. In order to improve adoption and endurance of new surveillance programs, more effective design and implementation of programs is needed to adequately reflect stakeholder needs and simultaneously support population-level disease monitoring and clinical decision-making across a range of chronic and acute health issues. At the heart of this cross-sectorial integration between clinical care and public health initiatives are emerging technologies and data modalities, including sequencing data. In this prospective, we propose an implementation strategy for genomics-based surveillance initiatives in LMICs founded on the use of a target operating model. Adoption of a target operating model for the design and implementation of genomic surveillance programs will ensure programs are agile, relevant, and unified across diverse stakeholder communities, thereby increasing their overall impact and sustainability.

The effectiveness of governmental nonpharmaceutical interventions against COVID-19 at controlling seasonal influenza transmission: an ecological study

BACKGROUND

A range of strict nonpharmaceutical interventions (NPIs) were implemented in many countries to combat the coronavirus 2019 (COVID-19) pandemic. These NPIs may also be effective at controlling seasonal influenza virus infections, as influenza viruses have the same transmission path as severe acute respiratory syndrome coronavirus 2. The aim of this study was to evaluate the effects of different NPIs on the control of seasonal influenza.

METHODS

Data for 14 NPIs implemented in 33 countries and the corresponding influenza virological surveillance data were collected. The influenza suppression index was calculated as the difference between the influenza positivity rate during its period of decline from 2019 to 2020 and during the influenza epidemic seasons in the previous 9 years. A machine learning model was developed using an extreme gradient boosting tree regressor to fit the NPI and influenza suppression index data. The SHapley Additive exPlanations tool was used to characterize the NPIs that suppressed the transmission of influenza.

RESULTS

Of all NPIs tested, gathering limitations had the greatest contribution (37.60%) to suppressing influenza transmission during the 2019-2020 influenza season. The three most effective NPIs were gathering limitations, international travel restrictions, and school closures. For these three NPIs, their intensity threshold required to generate an effect were restrictions on the size of gatherings less than 1000 people, ban of travel to all regions or total border closures, and closing only some categories of schools, respectively. There was a strong positive interaction effect between mask-wearing requirements and gathering limitations, whereas merely implementing a mask-wearing requirement, and not other NPIs, diluted the effectiveness of mask-wearing requirements at suppressing influenza transmission.

CONCLUSIONS

Gathering limitations, ban of travel to all regions or total border closures, and closing some levels of schools were found to be the most effective NPIs at suppressing influenza transmission. It is recommended that the mask-wearing requirement be combined with gathering limitations and other NPIs. Our findings could facilitate the precise control of future influenza epidemics and other potential pandemics.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Human seasonal influenza under COVID-19 and the potential consequences of influenza lineage elimination

Annual epidemics of seasonal influenza cause hundreds of thousands of deaths, high levels of morbidity, and substantial economic loss. Yet, global influenza circulation has been heavily suppressed by public health measures and travel restrictions since the onset of the COVID-19 pandemic. Notably, the influenza B/Yamagata lineage has not been conclusively detected since April 2020, and A(H3N2), A(H1N1), and B/Victoria viruses have since circulated with considerably less genetic diversity. Travel restrictions have largely confined regional outbreaks of A(H3N2) to South and Southeast Asia, B/Victoria to China, and A(H1N1) to West Africa. Seasonal influenza transmission lineages continue to perish globally, except in these select hotspots, which will likely seed future epidemics. Waning population immunity and sporadic case detection will further challenge influenza vaccine strain selection and epidemic control. We offer a perspective on the potential short- and long-term evolutionary dynamics of seasonal influenza and discuss potential consequences and mitigation strategies as global travel gradually returns to pre-pandemic levels.

COVID-19 control measures have suppressed circulation of other infections including influenza. Here, the authors analyse WHO global influenza sequence and case report data and describe changes in the phylogenetic and geographic distribution of influenza lineages during the COVID-19 pandemic.

Global epidemiology of human infections with variant influenza viruses, 1959-2021: A descriptive study

BACKGROUND

Although human case numbers of variant influenza viruses have increased worldwide, the epidemiology of human cases and human-to-human transmissibility of different variant viruses remain uncertain.

METHODS

We used descriptive statistics to summarize the epidemiologic characteristics of variant virus infections. The hospitalization rate, case-fatality and hospitalization-fatality risks were used to assess disease severity. Transmissibility of variant viruses between humans was determined by the effective reproductive number (Re) and probability of infection following exposure to human cases.

RESULTS

We identified 707 cases of variant viruses from 1959-2021, and their spatiotemporal/demographic characteristics changed across subtypes. The clinical severity of cases of variant viruses was generally mild; cases older than 18 years with underlying conditions were associated with hospitalization. Of 69 clusters of human infections with variant viruses (median cluster size: 2), the upper limit of Re was 0.09 (H1N1v, H1N2v and H3N2v: 0.20 vs. 0.18 vs. 0.05), while it was not significantly different from the pooled estimates for avian influenza A(H7N9) and A(H5N1) viruses (0.10). Moreover, contacts of H5N1 cases (15.7%) had a significantly higher probability of infection than contacts of individuals with H7N9 (4.2%) and variant virus infections (4.2-7.2%).

CONCLUSIONS

The epidemiology of cases of variant viruses varied across time periods, geographical regions and subtypes during 1959-2021. The transmissibility of different variant viruses between humans remains limited. However, given the continuous evolution of viruses and the rapidly evolving epidemiology of cases of variant viruses, improving the surveillance systems for human variant virus infections is needed worldwide.

Non-Pharmaceutical Interventions Implemented to Control the COVID-19 Were Associated With Reduction of Influenza Incidence

Background

Non-pharmaceutical interventions were implemented in most countries to reduce the transmission of COVID-19. We aimed to describe the incidence of influenza in four countries in the 2019–2020 season and examined the effect of these non-pharmaceutical interventions on the incidence of influenza.

Methods

We used the network surveillance data from 2015 to 2020 to estimate the percentage increase in influenza cases to explore the effect of non-pharmaceutical interventions implemented to control the COVID-19 on the incidence of influenza in China, the United States, Japan, and Singapore.

Results

We found that the incidence of influenza has been almost zero and reached a persistent near-zero level for a continuous period of six months since epidemiologic week 14 of 2020 in the four countries. Influenza incidence decreased by 77.71% and 60.50% in the early days of COVID-19 in the 2019–2020 season compared to the same period in preceding years in Japan and Singapore, respectively. Furthermore, influenza incidence decreased by 60.50–99.48% during the period of compulsory interventions in the 2019–2020 season compared to the same period in preceding years in the four countries.

Conclusion

These findings suggest that the application of non-pharmaceutical interventions, even everyday preventive action, was associated with a reduction of influenza incidence, which highlights that more traditional public health interventions need to be reasserted and universalized to reduce influenza incidence.

Applying the Moving Epidemic Method to Establish the Influenza Epidemic Thresholds and Intensity Levels for Age-Specific Groups in Hubei Province, China

BACKGROUND

School-aged children were reported to act as the main transmitter during influenza epidemic seasons. It is vital to set up an early detection method to help with the vaccination program in such a high-risk population. However, most relative studies only focused on the general population. Our study aims to describe the influenza epidemiology characteristics in Hubei Province and to introduce the moving epidemic method to establish the epidemic thresholds for age-specific groups.

METHODS

We divided the whole population into pre-school, school-aged and adult groups. The virology data from 2010/2011 to 2017/2018 were applied to the moving epidemic method to establish the epidemic thresholds for the general population and age-specific groups for the detection of influenza in 2018/2019. The performances of the model were compared by the cross-validation process.

RESULTS

The epidemic threshold for school-aged children in the 2018/2019 season was 15.42%. The epidemic thresholds for influenza A virus subtypes H1N1 and H3N2 and influenza B were determined as 5.68%, 6.12% and 10.48%, respectively. The median start weeks of the school-aged children were similar to the general population. The cross-validation process showed that the sensitivity of the model established with school-aged children was higher than those established with the other age groups in total influenza, H1N1 and influenza B, while it was only lower than the general population group in H3N2.

CONCLUSIONS

This study proved the feasibility of applying the moving epidemic method in Hubei Province. Additional influenza surveillance and vaccination strategies should be well-organized for school-aged children to reduce the disease burden of influenza in China.

Epidemiology of influenza under the coronavirus disease 2019 pandemic in Nanjing, China

PURPOSE

Since the pandemic of coronavirus disease-19 (COVID-19), the incidence of influenza has decreased significantly, but there are still few reports in the short period before and after the pandemic period. This study aimed to explore influenza activity and dynamic changes before and during the pandemic.

METHODS

A total of 1,324,357 influenza-like illness (ILI) cases were reported under ILI surveillance network from Jan 1, 2018 to Sep 5, 2021 in Nanjing, of which 16,158 cases were detected in laboratory. Differences of ILI and influenza was conducted with the chi-square test.

RESULTS

The number of ILI cases accounted for 8.97% of outpatient and emergency department visits. The influenza-positive ratio (IPR) was 7.84% in ILI cases. During the COVID-19 pandemic, ILI% and IPR dropped by 6.03% and 11.83% on average, respectively. Besides, IPR rose slightly in Week 30-35 of 2021. Not only differences in gender, age and employment status, but also the circulating strains had changed from type A to B through the COVID-19 pandemic.

CONCLUSION

The level of influenza activity was severely affected by COVID-19, but it seemed that it is inevitable to be vigilant against the co-circulation in the future. This article is protected by copyright. All rights reserved.

Attitudes, practices, and obstacles towards influenza vaccination for international travelers among travel health advisors in Germany: A questionnaire-based survey

BACKGROUND

Influenza is the most frequent vaccine-preventable infection in travelers, and both national and international guidelines recommend considering seasonal influenza vaccination (SIV) not only for those with risk factors for complications but for all travelers. However, vaccination coverage may be hampered by a lack of awareness among travelers and health care providers and limited vaccine availability outside the local influenza season.

METHODS

We identified travel health advisors in databases of German medical professional societies and invited them to complete an online questionnaire between April and May 2021.

RESULTS

Among 1085 travel health advisors contacted by email, 253 (23.3%) completed the online questionnaire. Most of them recommend SIV for travelers older than 60 years or those with comorbidities regardless of the travel destination or the influenza season in Germany. However, only very few respondents stated that they had regular access to SIV in June (n = 16, 6.5%), July (n = 10, 4.0%), and August (n = 17, 6.9%), respectively. While most participants (n = 197, 79.4%) stated that they would vaccinate more travelers if they had SIV regularly available outside the German influenza season, only eleven respondents (4.4%) have previously ordered SIV produced for the southern hemisphere, which was attributed mainly to logistic barriers.

CONCLUSIONS

Travel health advisors in Germany recommend SIV for a considerable proportion of travelers. While most of them see a necessity to vaccinate throughout the year, availability of SIV outside the German season is very limited. Current organizational barriers must be overcome to increase vaccination coverage among international travelers.

The science of the host-virus network

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

Genetic and Antigenic Characterization of an Influenza A(H3N2) Outbreak in Cambodia and the Greater Mekong Subregion during the COVID-19 Pandemic, 2020

Introduction of non-pharmaceutical interventions to control COVID-19 in early 2020 coincided with a global decrease in active influenza circulation. However, between July and November 2020, an influenza A(H3N2) epidemic occurred in Cambodia and in other neighboring countries in the Greater Mekong Subregion in Southeast Asia. We characterized the genetic and antigenic evolution of A(H3N2) in Cambodia and found that the 2020 epidemic comprised genetically and antigenically similar viruses of Clade3C2a1b/131K/94N, but they were distinct from the WHO recommended influenza A(H3N2) vaccine virus components for 2020–2021 Northern Hemisphere season. Phylogenetic analysis revealed multiple virus migration events between Cambodia and bordering countries, with Laos PDR and Vietnam also reporting similar A(H3N2) epidemics immediately following the Cambodia outbreak: however, there was limited circulation of these viruses elsewhere globally. In February 2021, a virus from the Cambodian outbreak was recommended by WHO as the prototype virus for inclusion in the 2021–2022 Northern Hemisphere influenza vaccine.

IMPORTANCE The 2019 coronavirus disease (COVID-19) pandemic has significantly altered the circulation patterns of respiratory diseases worldwide and disrupted continued surveillance in many countries. Introduction of control measures in early 2020 against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection has resulted in a remarkable reduction in the circulation of many respiratory diseases. Influenza activity has remained at historically low levels globally since March 2020, even when increased influenza testing was performed in some countries. Maintenance of the influenza surveillance system in Cambodia in 2020 allowed for the detection and response to an influenza A(H3N2) outbreak in late 2020, resulting in the inclusion of this virus in the 2021–2022 Northern Hemisphere influenza vaccine.

Editorial: A Decline in Influenza During the COVID-19 Pandemic and the Emergence of Potential Epidemic and Pandemic Influenza Viruses

There have been five viral pandemics in the past century, four were due to influenza, and the ongoing COVID-19 pandemic is due to SARS-CoV-2 infection. During the COVID-19 pandemic, there has been a 99% global reduction in the diagnosis of influenza. Also, from 2020, global mortality rates from influenza fell to record levels during the influenza seasons in the southern and northern hemispheres. However, as social restrictions become lifted and the winter season begins in the northern hemisphere, it is expected that influenza will re-emerge. The World Health Organization (WHO) FluNet surveillance platform provides global surveillance data on influenza, and the US Centers for Disease Control and Prevention (CDC) records national weekly infection rates. Both surveillance programs have identified zoonotic avian and swine influenza variants in humans. The WHO Pandemic Influenza Preparedness (PIP) Framework requires WHO Member States to share data on cases of emerging influenza viruses with pandemic potential in a regular and timely way. The WHO PIP Framework organizes the Global Influenza Surveillance and Response System (GISRS), a global network of public health laboratories developing candidate virus vaccines. This Editorial aims to present the reasons for concern regarding the emergence of pandemic influenza viruses driven by the social and public health responses to the COVID-19 pandemic and highlights the importance of global influenza surveillance at this time.

Influenza polymerase inhibitor resistance: Assessment of the current state of the art - A report of the isirv Antiviral group

It is more than 20 years since the neuraminidase inhibitors, oseltamivir and zanamivir were approved for the treatment and prevention of influenza. Guidelines for global surveillance and methods for evaluating resistance were established initially by the Neuraminidase Inhibitor Susceptibility Network (NISN), which merged 10 years ago with the International Society for influenza and other Respiratory Virus Diseases (isirv) to become the isirv-Antiviral Group (isirv-AVG). With the ongoing development of new influenza polymerase inhibitors and recent approval of baloxavir marboxil, the isirv-AVG held a closed meeting in August 2019 to discuss the impact of resistance to these inhibitors. Following this meeting and review of the current literature, this article is intended to summarize current knowledge regarding the clinical impact of resistance to polymerase inhibitors and approaches for surveillance and methods for laboratory evaluation of resistance, both in vitro and in animal models. We highlight limitations and gaps in current knowledge and suggest some strategies for addressing these gaps, including the need for additional clinical studies of influenza antiviral drug combinations. Lessons learned from influenza resistance monitoring may also be helpful for establishing future drug susceptibility surveillance and testing for SARS-CoV-2.

Spotlight influenza: Influenza surveillance before and after the introduction of point-of-care testing in Denmark, season 2014/15 to 2018/19

Background

In Denmark, influenza surveillance is ensured by data capturing from existing population-based registers. Since 2017, point-of-care (POC) testing has been implemented outside the regional clinical microbiology departments (CMD).

Aim

We aimed to assess influenza laboratory results in view of the introduction of POC testing.

Methods

We retrospectively observed routine surveillance data on national influenza tests before and after the introduction of POC testing as available in the Danish Microbiological Database. Also, we conducted a questionnaire study among Danish CMD about influenza diagnostics.

Results

Between the seasons 2014/15 and 2018/19, 199,744 influenza tests were performed in Denmark of which 44,161 were positive (22%). After the introduction of POC testing, the overall percentage of positive influenza tests per season did not decrease. The seasonal influenza test incidence was higher in all observed age groups. The number of operating testing platforms placed outside a CMD and with an instrument analytical time ≤ 3 h increased after 2017. Regionally, the number of tests registered as POC in the Danish Microbiological Database and the number of tests performed with an instrument analytical time ≤ 3 h or outside a CMD partially differed. Where comparable (71% of tests), the relative proportion of POC tests out of all tests increased from season 2017/18 to 2018/19. In both seasons, the percentage of positive POC tests resulted slightly lower than for non-POC tests.

Conclusion

POC testing integrated seamlessly into national influenza surveillance. We propose the use of POC results in the routine surveillance of seasonal influenza.

Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases

BACKGROUND

The WHO's Research and Development Blueprint priority list designates emerging diseases with the potential to generate public health emergencies for which insufficient preventive solutions exist. The list aims to reduce the time to the availability of resources that can avert public health crises. The current SARS-CoV-2 pandemic illustrates that an effective method of mitigating such crises is the pre-emptive prediction of outbreaks. This scoping review thus aimed to map and identify the evidence available to predict future outbreaks of the Blueprint diseases.

METHODS

We conducted a scoping review of PubMed, Embase and Web of Science related to the evidence predicting future outbreaks of Ebola and Marburg virus, Zika virus, Lassa fever, Nipah and Henipaviral disease, Rift Valley fever, Crimean-Congo haemorrhagic fever, Severe acute respiratory syndrome, Middle East respiratory syndrome and Disease X. Prediction methods, outbreak features predicted and implementation of predictions were evaluated. We conducted a narrative and quantitative evidence synthesis to highlight prediction methods that could be further investigated for the prevention of Blueprint diseases and COVID-19 outbreaks.

RESULTS

Out of 3959 articles identified, we included 58 articles based on inclusion criteria. 5 major prediction methods emerged; the most frequent being spatio-temporal risk maps predicting outbreak risk periods and locations through vector and climate data. Stochastic models were predominant. Rift Valley fever was the most predicted disease. Diseases with complex sociocultural factors such as Ebola were often predicted through multifactorial risk-based estimations. 10% of models were implemented by health authorities. No article predicted Disease X outbreaks.

CONCLUSIONS

Spatiotemporal models for diseases with strong climatic and vectorial components, as in River Valley fever prediction, may currently best reduce the time to the availability of resources. A wide literature gap exists in the prediction of zoonoses with complex sociocultural and ecological dynamics such as Ebola, COVID-19 and especially Disease X.

Report on influenza viruses received and tested by the Melbourne WHO Collaborating Centre for Reference and Research on Influenza in 2019

Abstract

As part of its role in the World Health Organization's (WHO) Global Influenza Surveillance and Response System (GISRS), the WHO Collaborating Centre for Reference and Research on Influenza in Melbourne received a record total of 9,266 human influenza positive samples during 2019. Viruses were analysed for their antigenic, genetic and antiviral susceptibility properties. Selected viruses were propagated in qualified cells or embryonated hen's eggs for potential use in seasonal influenza virus vaccines. In 2019, influenza A(H3N2) viruses predominated over influenza A(H1N1)pdm09 and B viruses, accounting for a total of 51% of all viruses analysed. The majority of A(H1N1)pdm09, A(H3N2) and influenza B viruses analysed at the Centre were found to be antigenically similar to the respective WHO recommended vaccine strains for the Southern Hemisphere in 2019. However, phylogenetic analysis indicated that a significant proportion of circulating A(H3N2) viruses had undergone genetic drift relative to the WHO recommended vaccine strain for 2019. Of 5,301 samples tested for susceptibility to the neuraminidase inhibitors oseltamivir and zanamivir, four A(H1N1)pdm09 viruses showed highly reduced inhibition with oseltamivir, one A(H1N1)pdm09 virus showed highly reduced inhibition with zanamivir and three B/Victoria viruses showed highly reduced inhibition with zanamivir.