Time lines of infection and disease in human influenza: a review of volunteer challenge studies

Wastewater Surveillance to Confirm Differences in Influenza A Infection between Michigan, USA, and Ontario, Canada, September 2022-March 2023

Wastewater surveillance is an effective way to track the prevalence of infectious agents within a community and, potentially, the spread of pathogens between jurisdictions. We conducted a retrospective wastewater surveillance study of the 2022-23 influenza season in 2 communities, Detroit, Michigan, USA, and Windsor-Essex, Ontario, Canada, that form North America's largest cross-border conurbation. We observed a positive relationship between influenza-related hospitalizations and the influenza A virus (IAV) wastewater signal in Windsor-Essex (ρ = 0.785; p<0.001) and an association between influenza-related hospitalizations in Michigan and the IAV wastewater signal for Detroit (ρ = 0.769; p<0.001). Time-lagged cross correlation and qualitative examination of wastewater signal in the monitored sewersheds showed the peak of the IAV season in Detroit was delayed behind Windsor-Essex by 3 weeks. Wastewater surveillance for IAV reflects regional differences in infection dynamics which may be influenced by many factors, including the timing of vaccine administration between jurisdictions.

Modeling antigen-specific T cell dynamics following Hepatitis B Vaccination indicates differences between conventional and regulatory T cell dynamics

Our study aims to investigate the dynamics of conventional memory T cells (Tconv) and regulatory memory T cells (Treg) following activation, and to explore potential differences between these two cell types. To achieve this, we developed advanced statistical mixed models based on mathematical models of ordinary differential equations (ODE), which allowed us to transform post-vaccination immunological processes into mathematical formulas. These models were applied to in-house data from a de novo Hepatitis B vaccination trial. By accounting for inter- and intra-individual variability, our models provided good fits for both antigen-specific Tconv and Treg cells, overcoming the challenge of studying these complex processes. Our modeling approach provided a deeper understanding of the immunological processes underlying T cell development after vaccination. Specifically, our analysis revealed several important findings regarding the dynamics of Tconv and Treg cells, as well as their relationship to seropositivity for Herpes Simplex Virus Type 1 (HSV-1) and Epstein-Barr Virus (EBV), and the dynamics of antibody response to vaccination. Firstly, our modeling indicated that Tconv dynamics suggest the existence of two T cell types, in contrast to Treg dynamics where only one T cell type is predicted. Secondly, we found that individuals who converted to a positive antibody response to the vaccine earlier had lower decay rates for both Tregs and Tconv cells, which may have important implications for the development of more effective vaccination strategies. Additionally, our modeling showed that HSV-1 seropositivity negatively influenced Tconv cell expansion after the second vaccination, while EBV seropositivity was associated with higher Treg expansion rates after vaccination. Overall, this study provides a critical foundation for understanding the dynamic processes underlying T cell development after vaccination.

Evaluating equity-promoting interventions to prevent race-based inequities in influenza outcomes

Importance

Seasonal influenza hospitalizations pose a considerable burden in the United States, with BIPOC (Black, Indigenous, and other People of Color) communities being disproportionately affected.

Objective

To determine and quantify the effects of different types of mitigation strategies on inequities in influenza outcomes (symptomatic infections and hospitalizations).

Design

In this simulation study, we fit a race-stratified agent-based model of influenza transmission to demographic and hospitalization data of the United States.

Participants

We consider five racial-ethnic groups: non-Hispanic White persons, non- Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American Indian or Alaska Native persons, and Hispanic or Latino persons.

Setting

We tested five idealized equity-promoting interventions to determine their effectiveness in reducing inequity in influenza outcomes. The interventions assumed (i) equalized vaccination rates, (ii) equalized comorbidities, (iii) work-risk distribution proportional to the distribution of the population, (iv) reduced work contacts for all, or (v) a combination of equalizing vaccination rates and comorbidities and reducing work contacts.

Main Outcomes and Measures

Reduction in symptomatic or hospitalization risk ratios, defined as the ratio of the number of symptomatic infections (hospitalizations respectively) in each age- and racial-ethnic group and their corresponding white counterpart. We also evaluated the reduction in the absolute mean number of symptomatic infections or hospitalizations in each age- and racial-ethnic group compared to the fitted scenario (baseline).

Results

Our analysis suggests that symptomatic infections were equalized and reduced (by up to 17% in BIPOC adults aged 18-49) by strategies reducing work contacts or equalizing vaccination rates. Reducing comorbidities resulted in significant decreases in hospitalizations, with a reduction of over 40% in BIPOC groups. All tested interventions reduced the inequity in influenza hospitalizations in all racial-ethnic groups, but interventions reducing comorbidities in marginalized populations were the most effective. Notably, these interventions resulted in better outcomes across all racial-ethnic groups, not only those prioritized by the interventions.

Conclusions and Relevance

In this simulation modeling study, equalizing vaccination rates and reducing number of work contacts (which are relatively simple strategies to implement) reduced the both the inequity in hospitalizations and the absolute number of symptomatic infections and hospitalizations in all age and racial-ethnic groups.

Symptom propagation in respiratory pathogens of public health concern: a review of the evidence

Symptom propagation occurs when the symptom set an individual experiences is correlated with the symptom set of the individual who infected them. Symptom propagation may dramatically affect epidemiological outcomes, potentially causing clusters of severe disease. Conversely, it could result in chains of mild infection, generating widespread immunity with minimal cost to public health. Despite accumulating evidence that symptom propagation occurs for many respiratory pathogens, the underlying mechanisms are not well understood. Here, we conducted a scoping literature review for 14 respiratory pathogens to ascertain the extent of evidence for symptom propagation by two mechanisms: dose-severity relationships and route-severity relationships. We identify considerable heterogeneity between pathogens in the relative importance of the two mechanisms, highlighting the importance of pathogen-specific investigations. For almost all pathogens, including influenza and SARS-CoV-2, we found support for at least one of the two mechanisms. For some pathogens, including influenza, we found convincing evidence that both mechanisms contribute to symptom propagation. Furthermore, infectious disease models traditionally do not include symptom propagation. We summarize the present state of modelling advancements to address the methodological gap. We then investigate a simplified disease outbreak scenario, finding that under strong symptom propagation, isolating mildly infected individuals can have negative epidemiological implications.

Anti-Neuraminidase Antibodies Reduce the Susceptibility to and Infectivity of Influenza A/H3N2 Virus

Immune responses against neuraminidase (NA) are of great interest for developing more robust influenza vaccines, but the role of anti-NA antibodies on influenza infectivity has not been established. We conducted household transmission studies in Managua, Nicaragua to examine the impact of anti-NA antibodies on influenza A/H3N2 susceptibility and infectivity. Analyzing these data with mathematical models capturing household transmission dynamics and their drivers, we estimated that having higher preexisting antibody levels against the hemagglutinin (HA) head, HA stalk, and NA was associated with reduced susceptibility to infection (relative susceptibility 0.67, 95% Credible Interval [CrI] 0.50-0.92 for HA head; 0.59, 95% CrI 0.42-0.82 for HA stalk; and 0.56, 95% CrI 0.40-0.77 for NA). Only anti-NA antibodies were associated with reduced infectivity (relative infectivity 0.36, 95% CrI 0.23-0.55). These benefits from anti-NA immunity were observed even among individuals with preexisting anti-HA immunity. These results suggest that influenza vaccines designed to elicit NA immunity in addition to hemagglutinin immunity may not only contribute to protection against infection but reduce infectivity of vaccinated individuals upon infection.

Modeling the transmission mitigation impact of testing for infectious diseases

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model's flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.

A cost-effectiveness analysis of reduced viral transmission with baloxavir marboxil versus oseltamivir or no treatment for seasonal and pandemic influenza management in the United Kingdom

BACKGROUND

Baloxavir marboxil is an oral, single-dose, cap-dependent endonuclease inhibitor that reduces the duration of influenza symptoms and rapidly stops viral shedding. We developed a susceptible, exposed, infected, recovered (SEIR) model to inform a cost-effectiveness model (CEM) of baloxavir versus oseltamivir or no antiviral treatment in the UK.

RESEARCH DESIGN AND METHODS

The SEIR model estimated the attack rates among otherwise healthy and high-risk individuals in seasonal and pandemic settings. The CEM assumed that a proportion of infected patients would receive antiviral treatment. Results were reported at the population level (per 10,000 at risk of infection).

RESULTS

The SEIR model estimated greater reductions in infections with baloxavir. In a seasonal setting, baloxavir provided incremental cost-effectiveness ratios (ICERs) of £1884 per quality-adjusted life-year (QALY) gained versus oseltamivir and a dominant cost-effectiveness position versus no antiviral treatment in the total population; ICERs of £2574/QALY versus oseltamivir and £128/QALY versus no antiviral treatment were seen in the high-risk population. Baloxavir was also cost-effective versus oseltamivir or no antiviral treatment and reduced population-level health system occupancy concerns during a pandemic.

CONCLUSION

Baloxavir treatment resulted in the fewest influenza cases and was cost-effective versus oseltamivir or no antiviral treatment from a UK National Health Service perspective.

Resurgence of seasonal influenza driven by A/H3N2 and B/Victoria in succession during the 2023-2024 season in Beijing showing increased population susceptibility

During the COVID-19 pandemic, non-pharmaceutical interventions were introduced to reduce exposure to respiratory viruses. However, these measures may have led to an "immunity debt" that could make the population more vulnerable. The goal of this study was to examine the transmission dynamics of seasonal influenza in the years 2023-2024. Respiratory samples from patients with influenza-like illness were collected and tested for influenza A and B viruses. The electronic medical records of index cases from October 2023 to March 2024 were analyzed to determine their clinical and epidemiological characteristics. A total of 48984 positive cases were detected, with a pooled prevalence of 46.9% (95% CI 46.3-47.5). This season saw bimodal peaks of influenza activity, with influenza A peaked in week 48, 2023, and influenza B peaked in week 1, 2024. The pooled positive rates were 28.6% (95% CI 55.4-59.6) and 18.3% (95% CI 18.0-18.7) for influenza A and B viruses, respectively. The median values of instantaneous reproduction number were 5.5 (IQR 3.0-6.7) and 4.6 (IQR 2.4-5.5), respectively. The hospitalization rate for influenza A virus (2.2%, 95% CI 2.0-2.5) was significantly higher than that of influenza B virus (1.1%, 95% CI 0.9-1.4). Among the 17 clinical symptoms studied, odds ratios of 15 symptoms were below 1 when comparing influenza A and B positive inpatients, with headache, weakness, and myalgia showing significant differences. This study provides an overview of influenza dynamics and clinical symptoms, highlighting the importance for individuals to receive an annual influenza vaccine.

Nanopore sequencing of influenza A and B in Oxfordshire and the United Kingdom, 2022-23

OBJECTIVES

We evaluated Nanopore sequencing for influenza surveillance.

METHODS

Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification.

RESULTS

From 941 infections, successful sequencing was achieved in 292/388 (75 %) available Oxfordshire samples: 231 (79 %) A/H3N2, 53 (18 %) A/H1N1, and 8 (3 %) B/Victoria and in 53/113 (47 %) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141, 88 %); 36/39 (92 %) Illumina vs. Nanopore comparisons were identical, and 3 (8 %) differed by 1 variant. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941 (90 %) Oxfordshire infections were community-acquired. 63/88 (72 %) potentially healthcare-associated cases shared a hospital ward with ≥ 1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within ≤ 5 SNPs, of these, 5 (63 %) involved potential sources that were also hospital-acquired.

CONCLUSIONS

Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.

An IFNγ-dependent immune-endocrine circuit lowers blood glucose to potentiate the innate antiviral immune response

Viral infection makes us feel sick as the immune system alters systemic metabolism to better fight the pathogen. The extent of these changes is relative to the severity of disease. Whether blood glucose is subject to infection-induced modulation is mostly unknown. Here we show that strong, nonlethal infection restricts systemic glucose availability, which promotes the antiviral type I interferon (IFN-I) response. Following viral infection, we find that IFNγ produced by γδ T cells stimulates pancreatic β cells to increase glucose-induced insulin release. Subsequently, hyperinsulinemia lessens hepatic glucose output. Glucose restriction enhances IFN-I production by curtailing lactate-mediated inhibition of IRF3 and NF-κB signaling. Induced hyperglycemia constrained IFN-I production and increased mortality upon infection. Our findings identify glucose restriction as a physiological mechanism to bring the body into a heightened state of responsiveness to viral pathogens. This immune-endocrine circuit is disrupted in hyperglycemia, possibly explaining why patients with diabetes are more susceptible to viral infection.

The role of asymptomatic infections in influenza transmission: what do we really know

Before the COVID-19 pandemic, the role of asymptomatic influenza virus infections in influenza transmission was uncertain. However, the importance of asymptomatic infection with SARS-CoV-2 for onward transmission of COVID-19 has led experts to question whether the role of asymptomatic influenza virus infections in transmission had been underappreciated. We discuss the existing evidence on the frequency of asymptomatic influenza virus infections, the extent to which they contribute to infection transmission, and remaining knowledge gaps. We propose priority areas for further evaluation, study designs, and case definitions to address existing knowledge gaps.

Defining the balance between optimal immunity and immunopathology in influenza virus infection

Influenza A viruses remain a global threat to human health, with continued pandemic potential. In this Review, we discuss our current understanding of the optimal immune responses that drive recovery from influenza virus infection, highlighting the fine balance between protective immune mechanisms and detrimental immunopathology. We describe the contribution of innate and adaptive immune cells, inflammatory modulators and antibodies to influenza virus-specific immunity, inflammation and immunopathology. We highlight recent human influenza virus challenge studies that advance our understanding of susceptibility to influenza and determinants of symptomatic disease. We also describe studies of influenza virus-specific immunity in high-risk groups following infection and vaccination that inform the design of future vaccines to promote optimal antiviral immunity, particularly in vulnerable populations. Finally, we draw on lessons from the COVID-19 pandemic to refocus our attention to the ever-changing, highly mutable influenza A virus, predicted to cause future global pandemics.

Vaccines Induce Homeostatic Immunity, Generating Several Secondary Benefits

The optimal immune response eliminates invading pathogens, restoring immune equilibrium without inflicting undue harm to the host. However, when a cascade of immunological reactions is triggered, the immune response can sometimes go into overdrive, potentially leading to harmful long-term effects or even death. The immune system is triggered mostly by infections, allergens, or medical interventions such as vaccination. This review examines how these immune triggers differ and why certain infections may dysregulate immune homeostasis, leading to inflammatory or allergic pathology and exacerbation of pre-existing conditions. However, many vaccines generate an optimal immune response and protect against the consequences of pathogen-induced immunological aggressiveness, and from a small number of unrelated pathogens and autoimmune diseases. Here, we propose an "immuno-wave" model describing a vaccine-induced "Goldilocks immunity", which leaves fine imprints of both pro-inflammatory and anti-inflammatory milieus, derived from both the innate and the adaptive arms of the immune system, in the body. The resulting balanced, 'quiet alert' state of the immune system may provide a jump-start in the defense against pathogens and any associated pathological inflammatory or allergic responses, allowing vaccines to go above and beyond their call of duty. In closing, we recommend formally investigating and reaping many of the secondary benefits of vaccines with appropriate clinical studies.

Latest developments in early diagnosis and specific treatment of severe influenza infection

Influenza pandemics are unpredictable recurrent events with global health, economic, and social consequences. The objective of this review is to provide an update on the latest developments in early diagnosis and specific treatment of the disease and its complications, particularly with regard to respiratory organ failure. Despite advances in treatment, the rate of mortality in the intensive care unit remains approximately 30%. Therefore, early identification of potentially severe viral pneumonia is extremely important to optimize treatment in these patients. The pathogenesis of influenza virus infection depends on viral virulence and host response. Thus, in some patients, it is associated with an excessive systemic response mediated by an authentic cytokine storm. This process leads to severe primary pneumonia and acute respiratory distress syndrome. Initial prognostication in the emergency department based on comorbidities, vital signs, and biomarkers (e.g., procalcitonin, ferritin, human leukocyte antigen-DR, mid-regional proadrenomedullin, and lactate) is important. Identification of these biomarkers on admission may facilitate clinical decision-making to determine early admission to the hospital or the intensive care unit. These decisions are reached considering pathophysiological circumstances that are associated with a poor prognosis (e.g., bacterial co-infection, hyperinflammation, immune paralysis, severe endothelial damage, organ dysfunction, and septic shock). Moreover, early implementation is important to increase treatment efficacy. Based on a limited level of evidence, all current guidelines recommend using oseltamivir in this setting. The possibility of drug resistance should also be considered. Alternative options include other antiviral drugs and combination therapies with monoclonal antibodies. Importantly, it is not recommended to use corticosteroids in the initial treatment of these patients. Furthermore, the implementation of supportive measures for respiratory failure is essential. Current recommendations are limited, heterogeneous, and not regularly updated. Early intubation and mechanical ventilation is the basic treatment for patients with severe respiratory failure. Prone ventilation should be promptly performed in patients with acute respiratory distress syndrome, while early tracheostomy should be considered in case of planned prolonged mechanical ventilation. Clinical trials on antiviral treatment and respiratory support measures specifically for these patients, as well as specific recommendations for different at-risk populations, are necessary to improve outcomes.

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

Household Influenza Transmission and Healthcare Resource Utilization Among Patients Treated with Baloxavir vs Oseltamivir: A United States Outpatient Prospective Survey

INTRODUCTION

Influenza is a common, seasonal infectious disease with broad medical, economic, and social consequences. Real-world evidence on the effect of influenza treatment on household transmission and healthcare resource utilization is limited in outpatient settings in the USA. This study examined the real-world effectiveness of baloxavir vs oseltamivir in reducing influenza household transmission and healthcare resource utilization.

METHODS

This prospective electronic survey on patient-reported outcomes was conducted between October 2022 and May 2023 via CVS Pharmacy in the USA. Adult participants (≥ 18 years old) were eligible if they filled a prescription for baloxavir or oseltamivir at a CVS Pharmacy within 2 days of influenza symptom onset. Participant demographics, household transmission, and all-cause healthcare resource utilization were collected. Transmission and utilization outcomes were assessed using χ2 and Fisher exact tests.

RESULTS

Of 87,871 unique patients contacted, 1346 (1.5%) consented. Of 374 eligible patients, 286 (90 baloxavir- and 196 oseltamivir-treated patients) completed the survey and were included in the analysis. Mean age of participants was 45.4 years, 65.6% were female, and 86.7% were White. Lower household transmission was observed with baloxavir compared with oseltamivir therapy (17.8% vs 26.5%; relative risk = 0.67; 95% CI 0.41-1.11). Healthcare resource utilization, particularly emergency department visits (0.0% vs 4.6%), was also numerically lower in the baloxavir-treated group; no hospitalizations were reported in either cohort.

CONCLUSIONS

The findings from this real-world study suggest that antiviral treatment of influenza with baloxavir may decrease household transmission and reduce healthcare resource utilization compared with oseltamivir.

Use of Sentinel Surveillance Platforms for Monitoring SARS-CoV-2 Activity: Evidence From Analysis of Kenya Influenza Sentinel Surveillance Data

BACKGROUND

Little is known about the cocirculation of influenza and SARS-CoV-2 viruses during the COVID-19 pandemic and the use of respiratory disease sentinel surveillance platforms for monitoring SARS-CoV-2 activity in sub-Saharan Africa.

OBJECTIVE

We aimed to describe influenza and SARS-CoV-2 cocirculation in Kenya and how the SARS-CoV-2 data from influenza sentinel surveillance correlated with that of universal national surveillance.

METHODS

From April 2020 to March 2022, we enrolled 7349 patients with severe acute respiratory illness or influenza-like illness at 8 sentinel influenza surveillance sites in Kenya and collected demographic, clinical, underlying medical condition, vaccination, and exposure information, as well as respiratory specimens, from them. Respiratory specimens were tested for influenza and SARS-CoV-2 by real-time reverse transcription polymerase chain reaction. The universal national-level SARS-CoV-2 data were also obtained from the Kenya Ministry of Health. The universal national-level SARS-CoV-2 data were collected from all health facilities nationally, border entry points, and contact tracing in Kenya. Epidemic curves and Pearson r were used to describe the correlation between SARS-CoV-2 positivity in data from the 8 influenza sentinel sites in Kenya and that of the universal national SARS-CoV-2 surveillance data. A logistic regression model was used to assess the association between influenza and SARS-CoV-2 coinfection with severe clinical illness. We defined severe clinical illness as any of oxygen saturation <90%, in-hospital death, admission to intensive care unit or high dependence unit, mechanical ventilation, or a report of any danger sign (ie, inability to drink or eat, severe vomiting, grunting, stridor, or unconsciousness in children younger than 5 years) among patients with severe acute respiratory illness.

RESULTS

Of the 7349 patients from the influenza sentinel surveillance sites, 76.3% (n=5606) were younger than 5 years. We detected any influenza (A or B) in 8.7% (629/7224), SARS-CoV-2 in 10.7% (768/7199), and coinfection in 0.9% (63/7165) of samples tested. Although the number of samples tested for SARS-CoV-2 from the sentinel surveillance was only 0.2% (60 per week vs 36,000 per week) of the number tested in the universal national surveillance, SARS-CoV-2 positivity in the sentinel surveillance data significantly correlated with that of the universal national surveillance (Pearson r=0.58; P<.001). The adjusted odds ratios (aOR) of clinical severe illness among participants with coinfection were similar to those of patients with influenza only (aOR 0.91, 95% CI 0.47-1.79) and SARS-CoV-2 only (aOR 0.92, 95% CI 0.47-1.82).

CONCLUSIONS

Influenza substantially cocirculated with SARS-CoV-2 in Kenya. We found a significant correlation of SARS-CoV-2 positivity in the data from 8 influenza sentinel surveillance sites with that of the universal national SARS-CoV-2 surveillance data. Our findings indicate that the influenza sentinel surveillance system can be used as a sustainable platform for monitoring respiratory pathogens of pandemic potential or public health importance.

Influenza vaccine effectiveness against hospitalizations associated with influenza A(H3N2) in Hong Kong children aged 9 months to 17 years, June-November 2023

A test negative study was carried out from 13 June through to 15 November 2023 enrolling 3183 children hospitalized with acute respiratory illness in Hong Kong. Influenza A and B viruses were detected in 528 (16.6%) children, among which 419 (79.4%) were influenza A(H3N2). The overall vaccine effectiveness against hospitalization associated with any influenza virus infection was estimated as 22.4% (95% CI: -11.7%, 46.1%), and against influenza A(H3N2) specifically was 14.3% (95% CI: -29.2%, 43.2%). Despite the moderate to low VE estimated here, which could be a result of waning immunity and antigenic drift, influenza vaccination remains an important approach to reduce the impact of influenza in children.

Antigen identification strategies and preclinical evaluation models for advancing tuberculosis vaccine development

In its myriad devastating forms, Tuberculosis (TB) has existed for centuries, and humanity is still affected by it. Mycobacterium tuberculosis (M. tuberculosis), the causative agent of TB, was the foremost killer among infectious agents until the COVID-19 pandemic. One of the key healthcare strategies available to reduce the risk of TB is immunization with bacilli Calmette-Guerin (BCG). Although BCG has been widely used to protect against TB, reports show that BCG confers highly variable efficacy (0-80%) against adult pulmonary TB. Unwavering efforts have been made over the past 20 years to develop and evaluate new TB vaccine candidates. The failure of conventional preclinical animal models to fully recapitulate human response to TB, as also seen for the failure of MVA85A in clinical trials, signifies the need to develop better preclinical models for TB vaccine evaluation. In the present review article, we outline various approaches used to identify protective mycobacterial antigens and recent advancements in preclinical models for assessing the efficacy of candidate TB vaccines.

Modeling the Transmission Mitigation Impact of Testing for Infectious Diseases

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus (RSV), but delayed by up to 2d to control omicron-era SARS-CoV-2. Furthermore, while rapid tests are superior to RT-qPCR for control of founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Finally, we illustrate the model's flexibility by quantifying tradeoffs in the use of post-diagnosis testing to shorten isolation times.

Detecting changes in generation and serial intervals under varying pathogen biology, contact patterns and outbreak response

The epidemiological characteristics of SARS-CoV-2 transmission have changed over the pandemic due to emergence of new variants. A decrease in the generation or serial intervals would imply a shortened transmission timescale and, hence, outbreak response measures would need to expand at a faster rate. However, there are challenges in measuring these intervals. Alongside epidemiological changes, factors like varying delays in outbreak response, social contact patterns, dependence on the growth phase of an outbreak, and effects of exposure to multiple infectors can also influence measured generation or serial intervals. To guide real-time interpretation of variant data, we simulated concurrent changes in the aforementioned factors and estimated the statistical power to detect a change in the generation and serial interval. We compared our findings to the reported decrease or lack thereof in the generation and serial intervals of different SARS-CoV-2 variants. Our study helps to clarify contradictory outbreak observations and informs the required sample sizes under certain outbreak conditions to ensure that future studies of generation and serial intervals are adequately powered.

Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans

Viral pandemics and epidemics pose a significant global threat. While macaque models of viral disease are routinely used, it remains unclear how conserved antiviral responses are between macaques and humans. Therefore, we conducted a cross-species analysis of transcriptomic data from over 6,088 blood samples from macaques and humans infected with one of 31 viruses. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses that are consistent across infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Leveraging longitudinal data from experimental challenges, we identify virus-specific response kinetics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Our results underscore macaque studies as a powerful tool for understanding viral pathogenesis and immune responses that translate to humans, with implications for viral therapeutic development and pandemic preparedness.

Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis

Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.

Influenza transmission dynamics quantified from RNA in wastewater in Switzerland

INTRODUCTION

Influenza infections are challenging to monitor at the population level due to many mild and asymptomatic cases and similar symptoms to other common circulating respiratory diseases, including COVID-19. Methods for tracking cases outside of typical reporting infrastructure could improve monitoring of influenza transmission dynamics. Influenza shedding into wastewater represents a promising source of information where quantification is unbiased by testing or treatment-seeking behaviours.

METHODS

We quantified influenza A and B virus loads from influent at Switzerland's three largest wastewater treatment plants, serving about 14% of the Swiss population (1.2 million individuals). We estimated trends in infection incidence and the effective reproductive number (Re) in these catchments during a 2021/22 epidemic and compared our estimates to typical influenza surveillance data.

RESULTS

Wastewater data captured the same overall trends in infection incidence as laboratory-confirmed case data at the catchment level. However, the wastewater data were more sensitive in capturing a transient peak in incidence in December 2021 than the case data. The Re estimated from the wastewater data was roughly at or below the epidemic threshold of 1 during work-from-home measures in December 2021 but increased to at or above the epidemic threshold in two of the three catchments after the relaxation of these measures. The third catchment yielded qualitatively the same results but with wider confidence intervals. The confirmed case data at the catchment level yielded comparatively less precise R_e estimates before and during the work-from-home period, with confidence intervals that included one before and during the work-from-home period.

DISCUSSION

Overall, we show that influenza RNA in wastewater can help monitor nationwide influenza transmission dynamics. Based on this research, we developed an online dashboard for ongoing wastewater-based influenza surveillance in Switzerland.

Survey of exposure to stranded dolphins in Japan to investigate an outbreak of suspected infection with highly pathogenic avian influenza (H5N1) clade 2.3.4.4(b) in humans

Background

A highly pathogenic avian influenza (HPAI) A (H5N1) virus has been detected in domestic and wild animals worldwide. The incidence of HPAI infections in sea mammals has been increasing, as is the number of stranded marine mammals linked to H5N1 viral clade 2.3.4.4(b). In this study, we investigated a stranding event involving dolphins and human-dolphin contact, and investigated the potential risk of animal-to-human H5N1 transmission with a survey of exposure on the Tsurigasaki coast, Japan.

Methods

We performed a non-random, convenient-sample-based, survey on Tsurigasaki beach where around 30 melon-headed whales were stranded on April 3, 2023. Face-to-face (n = 25) and telephone (n = 1) interviews among surfers took place on April 7 and 8. A nasal swab for quick antigen testing was taken from those who wished to be tested (n = 13), to detect infections with influenza A virus.

Results

Although there was no confirmatory diagnosis of H5N1 in either humans or dolphins (while n = 3 dolphins were autopsied), we found that a large number of surfers had touched the dolphins with their bare hands while attempting to rescue them, and that some surfers were directly exposed to dolphin blood and body fluids in the ocean.

Conclusions

The adequate communication of risk is required to minimize the threat of viral transmission at this particular human-animal interface. Administrative and legal responses to cross-species transmission, including guidelines via one health frameworks, a rapid evaluation process of ethical approval, and the systematic involvement of experts in infectious disease, must be urgently formulated.

An agent-based nested model integrating within-host and between-host mechanisms to predict an epidemic

The COVID-19 pandemic has remarkably heightened concerns regarding the prediction of communicable disease spread. This study introduces an innovative agent-based modeling approach. In this model, the quantification of human-to-human transmission aligns with the dynamic variations in the viral load within an individual, termed "within-host" and adheres to the susceptible-infected-recovered (SIR) process, referred to as "between-host." Variations in the viral load over time affect the infectivity between individual agents. This model diverges from the traditional SIR model, which employs a constant transmission probability, by incorporating a dynamic, time-dependent transmission probability influenced by the viral load in a host agent. The proposed model retains the time-integrated transmission probability characteristic of the conventional SIR model. As observed in this model, the overall epidemic size remains consistent with the predictions of the standard SIR model. Nonetheless, compared to predictions based on the classical SIR process, notable differences existed in the peak number of the infected individuals and the timing of this peak. These nontrivial differences are induced by the direct correlation between the time-evolving transmission probability and the viral load within a host agent. The developed model can inform targeted intervention strategies and public health policies by providing detailed insights into disease spread dynamics, crucial for effectively managing epidemics.

Work Attendance with Acute Respiratory Illness Before and During COVID-19 Pandemic, United States, 2018-2022

Both SARS-CoV-2 and influenza virus can be transmitted by asymptomatic, presymptomatic, or symptomatic infected persons. We assessed effects on work attendance while ill before and during the COVID-19 pandemic in the United States by analyzing data collected prospectively from persons with acute respiratory illnesses enrolled in a multistate study during 2018-2022. Persons with previous hybrid work experience were significantly less likely to work onsite on the day before through the first 3 days of illness than those without that experience, an effect more pronounced during the COVID-19 pandemic than during prepandemic influenza seasons. Persons with influenza or COVID-19 were significantly less likely to work onsite than persons with other acute respiratory illnesses. Among persons with positive COVID-19 test results available by the second or third day of illness, few worked onsite. Hybrid and remote work policies might reduce workplace exposures and help reduce spread of respiratory viruses.

Population age and household structures shape transmission dynamics of emerging infectious diseases: a longitudinal microsimulation approach

Host population demographics and patterns of host-to-host interactions are important drivers of heterogeneity in infectious disease transmission. To improve our understanding of how population structures and changes therein influence disease transmission dynamics at the individual and population level, we model a dynamic age- and household-structured population using longitudinal microdata drawn from Belgian census and population registers. At different points in time, we simulate the spread of a close-contact infectious disease and vary the age profiles of infectiousness and susceptibility to reflect specific infections (e.g. influenza and SARS-CoV-2) using a two-level mixing model, which distinguishes between exposure to infection in the household and exposure in the community. We find that the strong relationship between age and household structures, in combination with social mixing patterns and epidemiological parameters, shape the spread of an emerging infection. Disease transmission in the adult population in particular is to a large degree explained by differential household compositions and not just household size. Moreover, we highlight how demographic processes alter population structures in an ageing population and how these in turn affect disease transmission dynamics across population groups.

The two-stage molecular scenery of SARS-CoV-2 infection with implications to disease severity: An in-silico quest

Introduction

The two-stage molecular profile of the progression of SARS-CoV-2 (SCOV2) infection is explored in terms of five key biological/clinical questions: (a) does SCOV2 exhibits a two-stage infection profile? (b) SARS-CoV-1 (SCOV1) vs. SCOV2: do they differ? (c) does and how SCOV2 differs from Influenza/INFL infection? (d) does low viral-load and (e) does COVID-19 early host response relate to the two-stage SCOV2 infection profile? We provide positive answers to the above questions by analyzing the time-series gene-expression profiles of preserved cell-lines infected with SCOV1/2 or, the gene-expression profiles of infected individuals with different viral-loads levels and different host-response phenotypes.

Methods

Our analytical methodology follows an in-silico quest organized around an elaborate multi-step analysis pipeline including: (a) utilization of fifteen gene-expression datasets from NCBI's gene expression omnibus/GEO repository; (b) thorough designation of SCOV1/2 and INFL progression stages and COVID-19 phenotypes; (c) identification of differentially expressed genes (DEGs) and enriched biological processes and pathways that contrast and differentiate between different infection stages and phenotypes; (d) employment of a graph-based clustering process for the induction of coherent groups of networked genes as the representative core molecular fingerprints that characterize the different SCOV2 progression stages and the different COVID-19 phenotypes. In addition, relying on a sensibly selected set of induced fingerprint genes and following a Machine Learning approach, we devised and assessed the performance of different classifier models for the differentiation of acute respiratory illness/ARI caused by SCOV2 or other infections (diagnostic classifiers), as well as for the prediction of COVID-19 disease severity (prognostic classifiers), with quite encouraging results.

Results

The central finding of our experiments demonstrates the down-regulation of type-I interferon genes (IFN-1), interferon induced genes (ISGs) and fundamental innate immune and defense biological processes and molecular pathways during the early SCOV2 infection stages, with the inverse to hold during the later ones. It is highlighted that upregulation of these genes and pathways early after infection may prove beneficial in preventing subsequent uncontrolled hyperinflammatory and potentially lethal events.

Discussion

The basic aim of our study was to utilize in an intuitive, efficient and productive way the most relevant and state-of-the-art bioinformatics methods to reveal the core molecular mechanisms which govern the progression of SCOV2 infection and the different COVID-19 phenotypes.

Exploring the impact of population ageing on the spread of emerging respiratory infections and the associated burden of mortality

BACKGROUND

Increasing life expectancy and persistently low fertility levels have led to old population age structures in most high-income countries, and population ageing is expected to continue or even accelerate in the coming decades. While older adults on average have few interactions that potentially could lead to disease transmission, their morbidity and mortality due to infectious diseases, respiratory infections in particular, remain substantial. We aim to explore how population ageing affects the future transmission dynamics and mortality burden of emerging respiratory infections.

METHODS

Using longitudinal individual-level data from population registers, we model the Belgian population with evolving age and household structures, and explicitly consider long-term care facilities (LTCFs). Three scenarios are presented for the future proportion of older adults living in LTCFs. For each demographic scenario, we simulate outbreaks of SARS-CoV-2 and a novel influenza A virus in 2020, 2030, 2040 and 2050 and distinguish between household and community transmission. We estimate attack rates by age and household size/type, as well as disease-related deaths and the associated quality-adjusted life-years (QALYs) lost.

RESULTS

As the population is ageing, small households and LTCFs become more prevalent. Additionally, families with children become smaller (i.e. low fertility, single-parent families). The overall attack rate slightly decreases as the population is ageing, but to a larger degree for influenza than for SARS-CoV-2 due to differential age-specific attack rates. Nevertheless, the number of deaths and QALY losses per 1,000 people is increasing for both infections and at a speed influenced by the share living in LTCFs.

CONCLUSION

Population ageing is associated with smaller outbreaks of COVID-19 and influenza, but at the same time it is causing a substantially larger burden of mortality, even if the proportion of LTCF residents were to decrease. These relationships are influenced by age patterns in epidemiological parameters. Not only the shift in the age distribution, but also the induced changes in the household structures are important to consider when assessing the potential impact of population ageing on the transmission and burden of emerging respiratory infections.

Vaccinating the German Population Aged 60 Years and Over with a Quadrivalent High-Dose Inactivated Influenza Vaccine Compared to Standard-Dose Vaccines: A Transmission and Budget Impact Model

BACKGROUND AND OBJECTIVE

In Germany, influenza vaccination is mainly advised for persons aged 60 years and over and individuals with health risks. Since 2021, an inactivated, quadrivalent high-dose influenza vaccine (IIV4-HD) has been recommended for persons aged 60 years and over. The aim of this study was to calculate the impact of vaccinating the German population aged 60 years and over with IIV4-HD compared to standard-dose influenza vaccines (IIV4-SD) with regard to health outcomes and costs.

METHODS

An age-stratified deterministic compartment model was built to simulate the course of influenza infection for the German population in the season 2019/20. Probabilities for health outcomes and cost data were searched from the literature and were used to compare the influenza-related health and economic effects for different scenarios. Perspectives were those of the statutory health insurance and the society. Deterministic sensitivity analyses were conducted.

RESULTS

From the statutory health insurance perspective, vaccinating the German population aged 60 years and over with IIV4-HD would have prevented 277,026 infections (- 1.1%) with an increase of overall direct costs of €224 million (+ 40.1%) compared with IIV4-SD. A separate analysis showed that increased vaccination of 75% (World Health Organization recommendation for older age groups) in persons aged 60 years and over using IIV4-SD only would prevent 1,289,648 infections (- 5.1%) and would save costs from a statutory health insurance perspective of €103 million (- 13.2%) compared with IIV4-HD at actual vaccination rates.

CONCLUSIONS

The modeling approach offers important insights into the epidemiological and budgetary impact of different vaccination scenarios. Achieving a higher vaccination coverage with IIV4-SD in persons aged 60 years and over would result in lower costs and fewer influenza infections compared with the scenario with IIV4-HD and actual vaccination rates.

No association between inactivated influenza vaccination and influenza viral load at diagnosis among young Japanese children: An observational study of the 2013/2014 through 2017/2018 influenza seasons

BACKGROUND

The association between inactivated influenza vaccination and viral load in young children remains unclear.

METHODS

During the 2013/2014 to 2017/2018 influenza seasons in Japan, children under 6 years of age with pre-defined influenza-like illness and influenza-positive status by real-time RT-PCR were recruited at pediatric clinics for this observational study. Influenza viral load was measured for the most predominant subtype/lineage in each season. Using median dichotomized viral load as an outcome, a multilevel logistic regression model was applied to estimate the multivariable adjusted odds ratio (MOR) and 95% confidence interval (CI) for higher viral load.

RESULTS

A total of 1,185 influenza-positive children were analyzed. The median log10 viral load copy number (copies per milliliter) was 5.5 (interquartile range, 4.6 to 6.1) and did not differ by vaccination status: 5.5 for unvaccinated, 5.7 for one dose, and 5.5 for two doses (p = 0.67). The MOR of vaccinated (one or two doses) versus unvaccinated children was 1.19 (95% CI: 0.86-1.64). Other factors showing significant associations with higher viral load were positive results for A(H1N1)pdm09 and A(H3N2) in comparison with B/Yamagata. The respective MORs were 3.25 (95% CI: 2.28-4.64) and 1.81 (95% CI: 1.32-2.49). Significantly elevated MORs against higher viral load were also observed for higher body temperature at influenza diagnosis and shorter duration from fever onset to specimen collection.

CONCLUSION

No association was observed between inactivated-influenza vaccination and viral load at influenza-positive diagnosis. Influenza subtype/lineage, body temperature, and time elapsed since fever onset were significantly associated with viral load.

Nosocomial influenza in a pediatric general ward: Effects of isolation and cohort placement of children with influenza

OBJECTIVE

Many studies have described nosocomial outbreaks of influenza in specialized wards. We evaluated nosocomial transmission of influenza in a pediatric general ward.

DESIGN

Retrospective observational study.

SETTING

Single secondary hospital.

PATIENTS

The study included 814 hospitalized children with influenza between September 2015 and August 2020.

METHODS

The medical records of the included children were retrospectively reviewed, and clinical characteristics of children with community-acquired (CA) influenza and hospital-acquired (HA) influenza were determined. The room of each included child during hospitalization was traced to identify the children exposed to them.

RESULTS

CA influenza and HA influenza were diagnosed in 789 (96.9%) and 25 (3.1%) children, respectively. Among children with CA influenza, 691 (87.6%) were isolated or place in a cohort on admission. In total, 98 children (12.4%) admitted to multibed rooms exposed 307 children with noninfluenza diseases to influenza during 772 patient days; 3 exposed children (1.0%) were diagnosed with HA influenza. Including these 3 children, 25 children (19 without definite in-hospital exposure to influenza and 3 exposed to other children with HA influenza) were diagnosed with HA influenza, and 11 (44.0%) exposed 31 children with noninfluenza diseases to influenza for 85 patient days. Also, 3 exposed children (9.7%) were diagnosed with HA influenza, a significantly higher rate than that for CA influenza (P = .005). The clinical characteristics were comparable between children with HA influenza and those with CA influenza.

CONCLUSIONS

Cohort placement of children with influenza in a pediatric general ward can be effective in controlling nosocomial transmission of influenza. However, control measures for children with HA influenza should be emphasized.

Block the Spread: Barriers to Transmission of Influenza Viruses

Respiratory viruses, such as influenza viruses, cause significant morbidity and mortality worldwide through seasonal epidemics and sporadic pandemics. Influenza viruses transmit through multiple modes including contact (either direct or through a contaminated surface) and inhalation of expelled aerosols. Successful human to human transmission requires an infected donor who expels virus into the environment, a susceptible recipient, and persistence of the expelled virus within the environment. The relative efficiency of each mode can be altered by viral features, environmental parameters, donor and recipient host characteristics, and viral persistence. Interventions to mitigate transmission of influenza viruses can target any of these factors. In this review, we discuss many aspects of influenza virus transmission, including the systems to study it, as well as the impact of natural barriers and various nonpharmaceutical and pharmaceutical interventions.

The potential cost-effectiveness of next generation influenza vaccines in England and Wales: A modelling analysis

Next generation influenza vaccines are in development and have the potential for widespread health and economic benefits. Determining the potential health and economic impact for these vaccines is needed to drive investment in bringing these vaccines to the market, and to inform which groups public health policies on influenza vaccination should target. We used a mathematical modelling approach to estimate the epidemiological impact and cost-effectiveness of next generation influenza vaccines in England and Wales. We used data from an existing fitted model, and evaluated new vaccines with different characteristics ranging from improved vaccines with increased efficacy duration and breadth of protection, to universal vaccines, defined in line with the World Health Organisation (WHO) Preferred Product Characteristics (PPC). We calculated the cost effectiveness of new vaccines in comparison to the current seasonal vaccination programme. We calculated and compared the Incremental Cost-Effectiveness Ratio and Incremental Net Monetary Benefit for each new vaccine type. All analysis was conducted in R. We show that next generation influenza vaccines may result in a 21% to 77% reduction in influenza infections, dependent on vaccine characteristics. Our economic modelling shows that using any of these next generation vaccines at 2019 coverage levels would be highly cost-effective at a willingness to pay threshold of £20,000 for a range of vaccine prices. The vaccine threshold price for the best next generation vaccines in £-2019 is £230 (95%CrI £192 - £269) per dose, but even minimally-improved influenza vaccines could be priced at £18 (95%CrI £16 - £21) per dose and still remain cost-effective. This evaluation demonstrates the promise of next generation influenza vaccines for impact on influenza epidemics, and likely cost-effectiveness profiles. We have provided evidence towards a full value of vaccines assessment which bolsters the investment case for development and roll-out of next-generation influenza vaccines.

Circulation of Respiratory Viruses in the City: Towards an Agent-Based Ecosystem model

Mathematical models play an important role in management of outbreaks of acute respiratory infections (ARI). While such models are generally used to study the spread of a solitary virus, in reality multiple viruses co-circulate in the population. These viruses have been studied in detail, including the course of infection and immune defense mechanisms. We developed an agent-based model, called ABM-ARI, assimilating heterogeneous data and theoretical knowledge into a biologically motivated system, that allows to reproduce the seasonal patterns of ARI incidence and simulate interventions. ABM-ARI uses city-specific data to create a synthetic population and to construct realistic contact networks in different activity settings. Characteristics of infection, immune protection and non-specific resistance were varied between individuals to account for the population heterogeneity. For the calibration, we minimised the normalised mean absolute error between simulated and observed epidemic curves. ABM-ARI was built based on the quantitative assessment of features of predominant respiratory viruses and epidemiological characteristics of the population. It provides a good fit to the observed epidemic curves for different age groups and viruses. We also simulated one-week school closures when student absences were at or above 10%, 20% or 30% and found that only 10% and 20% thresholds resulted in a reduction of the incidence. ABM-ARI has a great potential in tackling the challenge of emerging infections by simulating and evaluating the effectiveness of various interventions.

A Multicenter, Controlled Human Infection Study of Influenza A(H1N1)pdm09 in Healthy Adults

BACKGROUND

We evaluated the associations between baseline influenza virus-specific hemagglutination inhibition (HAI) and microneutralization (MN) titers and subsequent symptomatic influenza virus infection in a controlled human infection study.

METHODS

We inoculated unvaccinated healthy adults aged 18-49 years with an influenza A/California/04/2009/H1N1pdm-like virus (NCT04044352). We collected serial safety labs, serum for HAI and MN, and nasopharyngeal swabs for reverse-transcription polymerase chain reaction (RT-PCR) testing. Analyses used the putative seroprotective titer of ≥40 for HAI and MN. The primary clinical outcome was mild-to-moderate influenza disease (MMID), defined as ≥1 postchallenge positive qualitative RT-PCR test with a qualifying symptom/clinical finding.

RESULTS

Of 76 participants given influenza virus challenge, 54 (71.1%) experienced MMID. Clinical illness was generally very mild. MMID attack rates among participants with baseline titers ≥40 by HAI and MN were 64.9% and 67.9%, respectively, while MMID attack rates among participants with baseline titers <40 by HAI and MN were 76.9% and 78.3%, respectively. The estimated odds of developing MMID decreased by 19% (odds ratio, 0.81 [95% confidence interval, .62-1.06]; P = .126) for every 2-fold increase in baseline HAI. There were no significant adverse events.

CONCLUSIONS

We achieved a 71.1% attack rate of MMID. High baseline HAI and MN were associated with protection from illness. Clinical Trials Registration. NCT04044352.

Efficacy and effectiveness of influenza vaccination in healthy children. A review of current evidence

Influenza is common in healthy children and adolescents and is associated with a high rate of hospitalization in this group, especially for those <5 years. Although the WHO has recommended vaccination in children under 5 years of age since 2012, it is really implemented in few countries today. The aim of this paper was to review the available evidence on the efficacy/effectiveness of influenza vaccination in healthy children <18 years of age through a non-systematic search of studies conducted between 2010 and 2020. Despite the high variability in results due to differences in design, vaccine type and season included in the 41 selected studies, statistically significant studies show efficacy values for the influenza vaccine of between 25.6% and 74.2%, and effectiveness from 26% to 78.8%. Although a systematic review would be necessary to corroborate the evidence, this review suggests that paediatric vaccination is generally an effective measure for preventing influenza in healthy children in line with international organisms' recommendations.

Viral Determinants of Acute COVID-19 Symptoms in a Nonhospitalized Adult Population in the Pre-Omicron Era

Background

The influence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA level and presence of infectious virus on symptom occurrence is poorly understood, particularly among nonhospitalized individuals.

Methods

The study included 85 nonhospitalized, symptomatic adults, who were enrolled from September 2020 to November 2021. Data from a longitudinal cohort studied over 28 days was used to analyze the association of individual symptoms with SARS-CoV-2 viral RNA load, or the presence or level of infectious (culturable) virus. Presence of infectious virus and viral RNA load were assessed daily, depending on specimen availability, and amount of infectious virus was assessed on the day of maximum RNA load. Participants were surveyed for the start and end dates of 31 symptoms at enrollment and at days 9, 14, 21, and 28; daily symptom presence was determined analytically. We describe symptoms and investigate their possible association with viral determinants through a series of single or pooled (multiple days across acute period) cross-sectional analyses.

Results

There was an association between viral RNA load and the same-day presence of many individual symptoms. Additionally, individuals with infectious virus were more than three times as likely to have a concurrent fever than individuals without infectious virus, and more than two times as likely to have concurrent myalgia, chills, headache, or sore throat.

Conclusions

We found evidence to support the association of viral RNA load and infectious virus on some, but not all symptoms. Fever was most strongly associated with the presence of infectious virus; this may support the potential for symptom-based isolation guidance for COVID-19.

Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study

The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

Care-seeking correlates of acute respiratory illness among sheltered adults experiencing homelessness in Seattle, WA, 2019: a community-based cross-sectional study

Objective

Multifarious barriers to accessing healthcare services among people experiencing homelessness (PEH) lead to delays in seeking care for acute infections, including those caused by respiratory viruses. PEH are at high risk of acute respiratory illness (ARI)-related complications, especially in shelter settings that may facilitate virus spread, yet data characterizing healthcare utilization for ARI episodes among sheltered PEH remained limited.

Methods

We conducted a cross-sectional study of viral respiratory infection among adult residents at two homeless shelters in Seattle, Washington between January and May 2019. We assessed factors associated with seeking medical care for ARI via self-report. We collected illness questionnaires and nasal swabs were tested for respiratory viruses by reverse transcription quantitative real-time PCR (RT-qPCR).

Results

We observed 825 encounters from 649 unique participants; 241 (29.2%) encounters reported seeking healthcare for their ARI episode. Seasonal influenza vaccine receipt (adjusted prevalence ratio [aPR] 1.39, 95% CI 1.02-1.88), having health insurance (aPR 2.77, 95% CI 1.27-6.02), chronic lung conditions (aPR 1.55, 95% CI 1.12-2.15), and experiencing influenza-like-illness symptoms (aPR 1.63, 95% CI 1.20 - 2.20) were associated with increased likelihood of seeking care. Smoking (aPR 0.65, 95% CI 0.45-0.92) was associated with decreased likelihood of seeking care.

Discussion

Findings suggest that care seeking for viral respiratory illness among PEH may be supported by prior engagement with primary healthcare services. Strategies to increase healthcare utilization may lead to earlier detection of respiratory viruses.

Trauma History Predicts Decoupling of C-Reactive Protein and Somatic Symptoms: Results From a Cohort Study of Sexual and Gender Minority Youth

OBJECTIVE

Systemic inflammation can induce somatic symptoms (e.g., pain, nausea, fatigue) through neuroimmune signaling pathways. Previous research suggests that early-life adversity amplifies signaling between peripheral inflammation and the brain. We therefore hypothesized that greater lifetime trauma exposure at baseline would predict stronger associations between systemic inflammation and somatic symptoms at 2.5-year follow-up in a cohort study of sexual and gender minority youth assigned male at birth ( n = 694).

METHODS

We measured prior trauma exposure (lifetime count of traumatic event types reported at baseline), somatic symptoms (Brief Symptom Inventory somatization score), and systemic inflammation (C-reactive protein, interleukin 6, interleukin 1β, and tumor necrosis factor α). All models included age, gender, education, recent trauma exposure, substance use, body mass index, and HIV status as covariates.

RESULTS

Higher C-reactive protein concentrations were associated with greater somatic symptoms in the main effects model ( β = 0.019, 95% confidence interval [CI] = 0.006 to 0.031). Contrary to our hypothesis, we observed a negative interaction between prior trauma exposure and C-reactive protein levels in predicting somatic symptoms ( β = -0.017, 95% CI = -0.030 to -0.004). Higher C-reactive protein was associated with greater somatic symptoms only in participants without prior trauma exposure at baseline ( β = 0.044, 95% CI = 0.026 to 0.062). Specificity analyses revealed similar patterns when nonsomatic depressive symptoms were used as the outcome variable.

CONCLUSIONS

These results suggest that sexual and gender minority youth assigned male at birth who have a history of prior trauma exposure may experience decoupling of systemic inflammation and somatic symptoms. The absence of inflammation-related symptoms may prevent individuals from seeking necessary medical care by reducing interoceptive awareness of pathological states.

Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces

Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.

Evaluating Potential Impacts of a Preferential Vaccine Recommendation for Adults 65 Years of Age and Older on US Influenza Burden

BACKGROUND

High-dose, adjuvanted, and recombinant influenza vaccines may offer improved effectiveness among older adults compared with standard-dose, unadjuvanted, inactivated vaccines. However, the Advisory Committee on Immunization Practices (ACIP) only recently recommended preferential use of these "higher-dose or adjuvanted" vaccines. One concern was that individuals might delay or decline vaccination if a preferred vaccine is not readily available.

METHODS

We mathematically model how a recommendation for preferential use of higher-dose or adjuvanted vaccines in adults ≥65 years might impact influenza burden in the United States during exemplar "high-" and "low-"severity seasons. We assume higher-dose or adjuvanted vaccines are more effective than standard vaccines and that such a recommendation would increase uptake of the former but could cause (i) delays in administration of additional higher-dose or adjuvanted vaccines relative to standard vaccines and/or (ii) reductions in overall coverage if individuals only offered standard vaccines forego vaccination.

RESULTS

In a best-case scenario, assuming no delay or coverage reduction, a new recommendation could decrease hospitalizations and deaths in adults ≥65 years by 0%-4% compared with current uptake. However, intermediate and worst-case scenarios, with assumed delays of 3 or 6 weeks and/or 10% or 20% reductions in coverage, included projections in which hospitalizations and deaths increased by over 7%.

CONCLUSIONS

We estimate that increased use of higher-dose or adjuvanted vaccines could decrease influenza burden in adults ≥65 in the United States provided there is timely and adequate access to these vaccines, and that standard vaccines are administered when they are unavailable.

Return on Investment (ROI) of Three Vaccination Programmes in Italy: HPV at 12 Years, Herpes Zoster in Adults, and Influenza in the Elderly

The calculation of the return on investment (ROI) allows the estimation of the opportunity cost of a series of interventions and can therefore help to make allocative choices. The objective of this study is to estimate the ROI of three vaccinations (HPV for adolescents, HZ for adults, and influenza for the elderly) in the Italian context, considering the impact of increasing vaccination coverage based on target objectives of the National Immunization Plan (PNPV) 2017-2019 and accounting for different eligibility criteria of each vaccination. Three separate static cohort models were constructed, including the eligible population for these vaccinations on the basis of the PNPV 2017-2019 and following this population until death (lifetime horizon) or until vaccination waning. Each model compares the level of investment at current vaccine coverage rates (current VCRs scenario) with that of optimal NIP target VCRs with a non-vaccination scenario. The ROI for HPV vaccination was the highest among the programs compared and was always above 1 (range: 1.4-3.58), while lower values were estimated for influenza vaccination in the elderly (range 0.48-0.53) and for vaccination against HZ (range: 0.09-0.27). Our analysis showed that a significant proportion of savings generated by vaccination programs occurred outside the NHS perspective and might often not be estimated with other forms of economic evaluation.

A target-cell limited model can reproduce influenza infection dynamics in hosts with differing immune responses

We consider a hierarchy of ordinary differential equation models that describe the within-host viral kinetics of influenza infections: the IR model explicitly accounts for an immune response to the virus, while the simpler, target-cell limited TEIV and TV models do not. We show that when the IR model is fitted to pooled experimental murine data of the viral load, fraction of dead cells, and immune response levels, its parameters values can be determined. However, if, as is common, only viral load data are available, we can estimate parameters of the TEIV and TV models but not the IR model. These results are substantiated by a structural and practical identifiability analysis. We then use the IR model to generate synthetic data representing infections in hosts whose immune responses differ. We fit the TV model to these synthetic datasets and show that it can reproduce the characteristic exponential increase and decay of viral load generated by the IR model. Furthermore, the values of the fitted parameters of the TV model can be mapped from the immune response parameters in the IR model. We conclude that, if only viral load data are available, a simple target-cell limited model can reproduce influenza infection dynamics and distinguish between hosts with differing immune responses.

Cost-Effectiveness of Vaccination of Older Adults with an MF59®-Adjuvanted Quadrivalent Influenza Vaccine Compared to Standard-Dose and High-Dose Vaccines in Denmark, Norway, and Sweden

Individuals aged 65 years and above are at increased risk of complications and death from influenza compared with any other age group. Enhanced vaccines, as the MF59®-adjuvanted quadrivalent influenza vaccine (aQIV) and the high-dose quadrivalent influenza vaccine (HD-QIV), provide increased protection for older adults in comparison to the traditional standard-dose quadrivalent influenza vaccines (SD-QIV). This study aimed to assess the cost-effectiveness of aQIV compared to SD-QIV and HD-QIV in Denmark, Norway, and Sweden for adults aged ≥65 years. A static decision tree model was used to evaluate costs and outcomes of different vaccination strategies from healthcare payer and societal perspectives. This model projects that compared to SD-QIV, vaccination with aQIV could prevent a combined total of 18,772 symptomatic influenza infections, 925 hospitalizations, and 161 deaths in one influenza season across the three countries. From a healthcare payer perspective, the incremental costs per quality adjusted life year (QALY) gained with aQIV versus SD-QIV were EUR 10,170/QALY in Denmark, EUR 12,515/QALY in Norway, and EUR 9894/QALY in Sweden. The aQIV was cost saving compared with HD-QIV. This study found that introducing aQIV to the entire population aged ≥65 years may contribute to reducing the disease and economic burden associated with influenza in these countries.

Potential health and economic impact of paediatric vaccination using next-generation influenza vaccines in Kenya: a modelling study

BACKGROUND

Influenza is a major year-round cause of respiratory illness in Kenya, particularly in children under 5. Current influenza vaccines result in short-term, strain-specific immunity and were found in a previous study not to be cost-effective in Kenya. However, next-generation vaccines are in development that may have a greater impact and cost-effectiveness profile.

METHODS

We expanded a model previously used to evaluate the cost-effectiveness of seasonal influenza vaccines in Kenya to include next-generation vaccines by allowing for enhanced vaccine characteristics and multi-annual immunity. We specifically examined vaccinating children under 5 years of age with improved vaccines, evaluating vaccines with combinations of increased vaccine effectiveness, cross-protection between strains (breadth) and duration of immunity. We evaluated cost-effectiveness using incremental cost-effectiveness ratios (ICERs) and incremental net monetary benefits (INMBs) for a range of values for the willingness-to-pay (WTP) per DALY averted. Finally, we estimated threshold per-dose vaccine prices at which vaccination becomes cost-effective.

RESULTS

Next-generation vaccines can be cost-effective, dependent on the vaccine characteristics and assumed WTP thresholds. Universal vaccines (assumed to provide long-term and broad immunity) are most cost-effective in Kenya across three of four WTP thresholds evaluated, with the lowest median value of ICER per DALY averted ($263, 95% Credible Interval (CrI): $ - 1698, $1061) and the highest median INMBs. At a WTP of $623, universal vaccines are cost-effective at or below a median price of $5.16 per dose (95% CrI: $0.94, $18.57). We also show that the assumed mechanism underlying infection-derived immunity strongly impacts vaccine outcomes.

CONCLUSIONS

This evaluation provides evidence for country-level decision makers about future next-generation vaccine introduction, as well as global research funders about the potential market for these vaccines. Next-generation vaccines may offer a cost-effective intervention to reduce influenza burden in low-income countries with year-round seasonality like Kenya.

Aerosolized nicotine from e-cigarettes alters gene expression, increases lung protein permeability, and impairs viral clearance in murine influenza infection

E-cigarette use has rapidly increased as an alternative means of nicotine delivery by heated aerosolization. Recent studies demonstrate nicotine-containing e-cigarette aerosols can have immunosuppressive and pro-inflammatory effects, but it remains unclear how e-cigarettes and the constituents of e-liquids may impact acute lung injury and the development of acute respiratory distress syndrome caused by viral pneumonia. Therefore, in these studies, mice were exposed one hour per day over nine consecutive days to aerosol generated by the clinically-relevant tank-style Aspire Nautilus aerosolizing e-liquid containing a mixture of vegetable glycerin and propylene glycol (VG/PG) with or without nicotine. Exposure to the nicotine-containing aerosol resulted in clinically-relevant levels of plasma cotinine, a nicotine-derived metabolite, and an increase in the pro-inflammatory cytokines IL-17A, CXCL1, and MCP-1 in the distal airspaces. Following the e-cigarette exposure, mice were intranasally inoculated with influenza A virus (H1N1 PR8 strain). Exposure to aerosols generated from VG/PG with and without nicotine caused greater influenza-induced production in the distal airspaces of the pro-inflammatory cytokines IFN-γ, TNFα, IL-1β, IL-6, IL-17A, and MCP-1 at 7 days post inoculation (dpi). Compared to the aerosolized carrier VG/PG, in mice exposed to aerosolized nicotine there was a significantly lower amount of Mucin 5 subtype AC (MUC5AC) in the distal airspaces and significantly higher lung permeability to protein and viral load in lungs at 7 dpi with influenza. Additionally, nicotine caused relative downregulation of genes associated with ciliary function and fluid clearance and an increased expression of pro-inflammatory pathways at 7 dpi. These results show that (1) the e-liquid carrier VG/PG increases the pro-inflammatory immune responses to viral pneumonia and that (2) nicotine in an e-cigarette aerosol alters the transcriptomic response to pathogens, blunts host defense mechanisms, increases lung barrier permeability, and reduces viral clearance during influenza infection. In conclusion, acute exposure to aerosolized nicotine can impair clearance of viral infection and exacerbate lung injury, findings that have implications for the regulation of e-cigarette products.

SARS-CoV-2 viral load and shedding kinetics

SARS-CoV-2 viral load and detection of infectious virus in the respiratory tract are the two key parameters for estimating infectiousness. As shedding of infectious virus is required for onward transmission, understanding shedding characteristics is relevant for public health interventions. Viral shedding is influenced by biological characteristics of the virus, host factors and pre-existing immunity (previous infection or vaccination) of the infected individual. Although the process of human-to-human transmission is multifactorial, viral load substantially contributed to human-to-human transmission, with higher viral load posing a greater risk for onward transmission. Emerging SARS-CoV-2 variants of concern have further complicated the picture of virus shedding. As underlying immunity in the population through previous infection, vaccination or a combination of both has rapidly increased on a global scale after almost 3 years of the pandemic, viral shedding patterns have become more distinct from those of ancestral SARS-CoV-2. Understanding the factors and mechanisms that influence infectious virus shedding and the period during which individuals infected with SARS-CoV-2 are contagious is crucial to guide public health measures and limit transmission. Furthermore, diagnostic tools to demonstrate the presence of infectious virus from routine diagnostic specimens are needed.