Global Influenza Surveillance and Response System: 70 years of responding to the expected and preparing for the unexpected

Landscape of H5 Infections in ASEAN Region: Past Insights, Present Realities, & Future Strategies

The H5 Avian Influenza A virus infection has emerged as a global concern, particularly in the ASEAN region. This viral infection poses a significant threat to the poultry industry, public health, and regional economies. This region's reliance on poultry production and the zoonotic potential of H5 subtypes, with documented transmission to various mammalian species and humans, necessitates proactive mitigation strategies. Over the years, comprehensive efforts such as surveillance, vaccination programs, biosecurity measures, and public health education have been implemented to keep outbreaks at bay. In this review, we provide a thorough overview of the H5 infections in the ASEAN region, focusing on the unique challenges and successes in this geographic area. We analyze epidemiological trends, including specific high-risk populations and transmission patterns, and assess the socioeconomic impact of H5 outbreaks on local communities. We also examine regional responses, highlighting innovative surveillance programs, vaccination strategies, and biosecurity measures implemented to control the virus. Furthermore, we explore the crucial role of the One Health approach, emphasizing interdisciplinary collaboration between human, animal, and environmental health sectors. Finally, we discuss future strategies for prevention and control, including the importance of regional cooperation in combating this evolving threat. Through this, we aim to provide valuable insights to the public, policymakers, and researchers involved in tackling H5 infections globally.

Balancing Human Mobility and Health Care Coverage in Sentinel Surveillance of Brazilian Indigenous Areas: Mathematical Optimization Approach

Background

Optimizing sentinel surveillance site allocation for early pathogen detection remains a challenge, particularly in ensuring coverage of vulnerable and underserved populations.

Objective

This study evaluates the current respiratory pathogen surveillance network in Brazil and proposes an optimized sentinel site distribution that balances Indigenous population coverage and national human mobility patterns.

Methods

We compiled Indigenous Special Health District (Portuguese: Distrito Sanitário Especial Indígena [DSEI]) locations from the Brazilian Ministry of Health and estimated national mobility routes by using the Ford-Fulkerson algorithm, incorporating air, road, and water transportation data. To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. We validated our approach by comparing results with Brazil's current influenza sentinel network and analyzing the health attraction index from the Brazilian Institute of Geography and Statistics to assess the feasibility and potential benefits of our optimized surveillance network.

Results

The current Brazilian network includes 199 municipalities, representing 3.6% (199/5570) of the country's cities. The optimized sentinel site design, while keeping the same number of municipalities, ensures 100% coverage of all 34 DSEI regions while rearranging 108 (54.3%) of the 199 cities from the existing flu sentinel system. This would result in a more representative sentinel network, addressing gaps in 9 of 34 previously uncovered DSEI regions, which span 750,515 km² and have a population of 1.11 million. Mobility coverage would improve by 16.8 percentage points, from 52.4% (4,598,416 paths out of 8,780,046 total paths) to 69.2% (6,078,747 paths out of 8,780,046 total paths). Additionally, all newly selected cities serve as hubs for medium- or high-complexity health care, ensuring feasibility for pathogen surveillance.

Conclusions

The proposed framework optimizes sentinel site allocation to enhance disease surveillance and early detection. By maximizing DSEI coverage and integrating human mobility patterns, this approach provides a more effective and equitable surveillance network, which would particularly benefit underserved Indigenous regions.

SARS-CoV-2 Variants: Genetic Insights, Epidemiological Tracking, and Implications for Vaccine Strategies

The emergence of SARS-CoV-2 variants has significantly impacted the global response to the COVID-19 pandemic. This review examines the genetic diversity of SARS-CoV-2 variants, their roles in epidemiological tracking, and their influence on viral fitness. Variants of concern (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron have demonstrated increased transmissibility, altered pathogenicity, and potential resistance to neutralizing antibodies. Epidemiological tracking of these variants is crucial for understanding their spread, informing public health interventions, and guiding vaccine development. The review also explores how specific mutations in the spike protein and other genomic regions contribute to viral fitness, affecting replication efficiency, immune escape, and transmission dynamics. By integrating genomic surveillance data with epidemiological and clinical findings, this review provides a comprehensive overview of the ongoing evolution of SARS-CoV-2 and its implications for public health strategies and new vaccine development.

Recent advances in the influenza virus vaccine landscape: a comprehensive overview of technologies and trials

SUMMARYIn the United Kingdom (UK) in 2022/23, influenza virus infections returned to the levels recorded before the COVID-19 pandemic, exerting a substantial burden on an already stretched National Health Service (NHS) through increased primary and emergency care visits and subsequent hospitalizations. Population groups ≤4 years and ≥65 years of age, and those with underlying health conditions, are at the greatest risk of influenza-related hospitalization. Recent advances in influenza virus vaccine technologies may help to mitigate this burden. This review aims to summarize advances in the influenza virus vaccine landscape by describing the different technologies that are currently in use in the UK and more widely. The review also describes vaccine technologies that are under development, including mRNA, and universal influenza virus vaccines which aim to provide broader or increased protection. This is an exciting and important era for influenza virus vaccinations, and advances are critical to protect against a disease that still exerts a substantial burden across all populations and disproportionately impacts the most vulnerable, despite it being over 80 years since the first influenza virus vaccines were deployed.

Enhanced event-based surveillance: Epidemic Intelligence from Open Sources (EIOS) during FIFA World Cup 2022 Qatar

BACKGROUND

Public health threats can significantly impact mass gatherings and enhancing surveillance systems would thus be crucial. Epidemic Intelligence from Open Sources (EIOS) was introduced to Qatar to complement the existing surveillance measures in preparation to the FIFA World Cup Qatar 2022 (FWC22). This study estimated the empirical probability of EIOS detecting signals of public health relevance. It also looked at the factors responsible for discerning a moderate-high risk signal during a mass gathering event.

METHODS

This cross-sectional descriptive study used data collected between November 8th and December 25th, 2022, through an EIOS dashboard that filtered open-source articles using specific keywords. Triage criteria and scoring scheme were developed to capture signals and these were maintained in MS Excel. EIOS' contribution to epidemic intelligence was assessed by the empirical probability estimation of relevant public health signals. Chi-squared tests of independence were performed to check for associations between various hazard categories and other independent variables. A multivariate logistic regression evaluated the predictors of moderate-high risk signals that required prompt action.

RESULTS

The probability of EIOS capturing a signal relevant to public health was estimated at 0.85 % (95 % confidence interval (CI) [0.82 %-0.88 %]) with three signals requiring a national response. The hazard category of the signal had significant association to the region of occurrence (χ2 (5, N = 2543) = 1021.6, p < .001). The hazard category also showed significant association to its detection during matchdays of the tournament (χ2 (5, N = 2543) = 11.2, p < .05). The triage criteria developed was able to discern between low and moderate-high risk signals with an acceptable discrimination (Area Under the Curve=0.79).

CONCLUSION

EIOS proved useful in the early warning of public health threats.

Electronic Health Record-Based Algorithm for Monitoring Respiratory Virus-Like Illness

Viral respiratory illness surveillance has traditionally focused on single pathogens (e.g., influenza) and required fever to identify influenza-like illness (ILI). We developed an automated system applying both laboratory test and syndrome criteria to electronic health records from 3 practice groups in Massachusetts, USA, to monitor trends in respiratory viral-like illness (RAVIOLI) across multiple pathogens. We identified RAVIOLI syndrome using diagnosis codes associated with respiratory viral testing or positive respiratory viral assays or fever. After retrospectively applying RAVIOLI criteria to electronic health records, we observed annual winter peaks during 2015-2019, predominantly caused by influenza, followed by cyclic peaks corresponding to SARS-CoV-2 surges during 2020-2024, spikes in RSV in mid-2021 and late 2022, and recrudescent influenza in late 2022 and 2023. RAVIOLI rates were higher and fluctuations more pronounced compared with traditional ILI surveillance. RAVIOLI broadens the scope, granularity, sensitivity, and specificity of respiratory viral illness surveillance compared with traditional ILI surveillance.

Antigenic distance between primary and secondary dengue infections correlates with disease risk

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection even in previously exposed individuals. In addition, for some pathogens, such as dengue virus, poorly targeted immunity is associated with increased risk of severe disease through a mechanism known as antibody-dependent enhancement. However, it remains unclear whether the antigenic distances between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalizations across years. Here, we develop a framework that combines detailed antigenic and genetic characterization of viruses with details on hospitalized cases from 21 years of dengue surveillance in Bangkok, Thailand, to identify the role of the antigenic profile of circulating viruses in determining disease risk. We found that the risk of hospitalization depended on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximized at intermediate antigenic distances. These findings suggest that immune imprinting helps determine dengue disease risk and provide a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

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.

Novel Influenza Vaccines: From Research and Development (R&D) Challenges to Regulatory Responses

Influenza vaccines faced significant challenges in achieving sufficient protective efficacy and production efficiency in the past. In recent decades, novel influenza vaccines, characterized by efficient and scalable production, advanced platforms, and new adjuvant technologies, have overcome some of these weaknesses and have been widely licensed. Furthermore, researchers are actively pursuing the development of next-generation and universal influenza vaccines to provide comprehensive protection against potential pandemic subtypes or strains. However, new challenges have emerged as these novel vaccines undergo evaluation and authorization. In this review, we primarily outline the critical challenges and advancements in research and development (R&D) and highlight the improvements in regulatory responses for influenza vaccines.

SARS-CoV-2 Surveillance Through China Influenza Surveillance Information System — China, December 1, 2022 to February 12, 2023

Introduction

The World Health Organization (WHO) proposed using influenza surveillance systems to carry out coronavirus disease 2019 (COVID-19) surveillance due to the similarity between the two diseases in some respiratory symptoms. To assess the prevalence of COVID-19, we analyzed the influenza-like illness (ILI) and positive rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detections in ILI patients reported to the influenza Surveillance Information System (CNISIS) since late 2022.

Methods

Data related to ILI were reported by national surveillance sentinel hospitals. Positive testing for SARS-CoV-2 and influenza viruses was conducted using real-time reverse transcription polymerase chain reaction (rRT-PCR) detection by the national influenza surveillance network laboratories. Surveillance data were reported to CNISIS.

Results

Beginning on December 12, 2022 (Week 50), the ILI percentage increased dramatically, peaking in Week 51 at 12.1%. Subsequently, the ILI percentage began to decline rapidly from Week 52, 2022, and by Week 6, 2023 (February 6-12), the ILI and ILI percentage had returned to the levels observed at the beginning of December 2022. From December 1, 2022 to February 12, 2023, 115,844 specimens were tested for both SARS-CoV-2 and influenza virus. Of these, 30,381 (26.2%) were positive for SARS-CoV-2 and 1,763 (1.5%) were positive for influenza virus. The positive rate of SARS-CoV-2 tests peaked at 74.1% around December 23 and 25.

Conclusions

Sentinel-based surveillance, previously established for influenza, is an effective way to track the circulation trend of SARS-CoV-2 during community-level epidemics. There was no co-prevalence of SARS-CoV-2 and influenza virus during the outbreak of SARS-CoV-2, even during the winter influenza season. However, it is important to remain vigilant for the potential rise of influenza activities following the COVID-19 epidemic.