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

Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission

SARS-CoV-2 vaccine clinical trials assess efficacy against disease (VEDIS), the ability to block symptomatic COVID-19. They only partially discriminate whether VEDIS is mediated by preventing infection completely, which is defined as detection of virus in the airways (VESUSC), or by preventing symptoms despite infection (VESYMP). Vaccine efficacy against transmissibility given infection (VEINF), the decrease in secondary transmissions from infected vaccine recipients, is also not measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna (mRNA-1273QS) and Pfizer-BioNTech (BNT162b2) vaccines, which demonstrated VEDIS > 90% in clinical trials, mediate VEDIS by VESUSC, then a limited fourth epidemic wave of infections with the highly infectious B.1.1.7 variant would have been predicted in spring 2021 assuming rapid vaccine roll out. If high VEDIS is explained by VESYMP, then high VEINF would have also been necessary to limit the extent of this fourth wave. Vaccines which completely protect against infection or secondary transmission also substantially lower the number of people who must be vaccinated before the herd immunity threshold is reached. The limited extent of the fourth wave suggests that the vaccines have either high VESUSC or both high VESYMP and high VEINF against B.1.1.7. Finally, using a separate intra-host mathematical model of viral kinetics, we demonstrate that a 0.6 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve 50% VEINF, which suggests that human challenge studies with a relatively low number of infected participants could be employed to estimate all three vaccine efficacy metrics.

Airborne transmission of respiratory viruses

The COVID-19 pandemic has revealed critical knowledge gaps in our understanding of and a need to update the traditional view of transmission pathways for respiratory viruses. The long-standing definitions of droplet and airborne transmission do not account for the mechanisms by which virus-laden respiratory droplets and aerosols travel through the air and lead to infection. In this Review, we discuss current evidence regarding the transmission of respiratory viruses by aerosols-how they are generated, transported, and deposited, as well as the factors affecting the relative contributions of droplet-spray deposition versus aerosol inhalation as modes of transmission. Improved understanding of aerosol transmission brought about by studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requires a reevaluation of the major transmission pathways for other respiratory viruses, which will allow better-informed controls to reduce airborne transmission.

Airborne transmission of respiratory viruses

The COVID-19 pandemic has revealed critical knowledge gaps in our understanding of and a need to update the traditional view of transmission pathways for respiratory viruses. The long-standing definitions of droplet and airborne transmission do not account for the mechanisms by which virus-laden respiratory droplets and aerosols travel through the air and lead to infection. In this Review, we discuss current evidence regarding the transmission of respiratory viruses by aerosols-how they are generated, transported, and deposited, as well as the factors affecting the relative contributions of droplet-spray deposition versus aerosol inhalation as modes of transmission. Improved understanding of aerosol transmission brought about by studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requires a reevaluation of the major transmission pathways for other respiratory viruses, which will allow better-informed controls to reduce airborne transmission.

Dynamically linking influenza virus infection kinetics, lung injury, inflammation, and disease severity

Influenza viruses cause a significant amount of morbidity and mortality. Understanding host immune control efficacy and how different factors influence lung injury and disease severity are critical. We established and validated dynamical connections between viral loads, infected cells, CD8⁺ T cells, lung injury, inflammation, and disease severity using an integrative mathematical model-experiment exchange. Our results showed that the dynamics of inflammation and virus-inflicted lung injury are distinct and nonlinearly related to disease severity, and that these two pathologic measurements can be independently predicted using the model-derived infected cell dynamics. Our findings further indicated that the relative CD8⁺ T cell dynamics paralleled the percent of the lung that had resolved with the rate of CD8⁺ T cell-mediated clearance rapidly accelerating by over 48,000 times in 2 days. This complimented our analyses showing a negative correlation between the efficacy of innate and adaptive immune-mediated infected cell clearance, and that infection duration was driven by CD8⁺ T cell magnitude rather than efficacy and could be significantly prolonged if the ratio of CD8⁺ T cells to infected cells was sufficiently low. These links between important pathogen kinetics and host pathology enhance our ability to forecast disease progression, potential complications, and therapeutic efficacy.

Characteristics and outcomes of family-practice patients with coronavirus disease 2019: a case series

BACKGROUND

The clinical history and outcomes of coronavirus disease 2019 among people not hospitalized is not yet well characterized. To better inform clinical evaluation, we set out to characterize the natural history of coronavirus disease 2019 in primary health care.

METHODS

Case series of all patients rostered to physicians at a university-affiliated Family Medicine clinic. Cases met the Centers for Disease Control and Prevention definition of coronavirus disease 2019 from March 1 to May 21 2020.

RESULTS

In total, 89 patients meeting Centers for Disease Control and Prevention criteria for coronavirus disease 2019 were documented. Their average age was 55.6 years (range 6-95 years), and all but one was symptomatic. Fifty-seven cases (64%) had a polymerase chain reaction test for coronavirus disease 2019, of whom 77.2% tested positive. Thirty cases (33.7%) reported contact with a confirmed or probable case of coronavirus disease 2019. Based on the Charlson Comorbidity Index, 28 cases (31.5%) had no comorbid conditions. The median number of days from symptom onset to first polymerase chain reaction test was 6 days (interquartile range 2.3-11 days). The median duration of fever was 3.5 days (interquartile range 1-7 days). Twenty-four cases (27%) visited the Emergency Department, and 10 were admitted to hospital. The median number of days between symptom onset and first Emergency Department visit was 8 days (interquartile range 3.5-27 days).

CONCLUSIONS

At the start of this pandemic, the implementation of basic measures such as diagnostic testing was delayed. If we are to improve our control over the spread of coronavirus disease 2019, we will need to substantially reduce the time from symptom onset to diagnostic testing, and subsequent contact tracing. To minimize unnecessary Emergency Department visits, we propose a testable strategy for Family Medicine to engage with coronavirus disease 2019 patients in the acute phase of their illness.

Reducing influenza virus transmission: the value of antiviral treatment

Prompt antiviral treatment has the potential to reduce influenza virus transmission to close contacts, but rigorous data on the magnitude of treatment effects on transmission are limited. Animal model data indicate that rapid reductions in viral replication after antiviral treatment reduce the risk of transmission. Observational and clinical trial data with oseltamivir and other neuraminidase inhibitors indicate that prompt treatment of household index patients seems to reduce the risk of illness in contacts, although the magnitude of the reported effects has varied widely across studies. In addition, the potential risk of transmitting drug-resistant variants exists with all approved classes of influenza antivirals. A controlled trial examining baloxavir treatment efficacy to reduce transmission, including the risk of transmitting virus with reduced baloxavir susceptibility, is currently in progress. If reduced transmission risk is confirmed, modeling studies indicate that early treatment could have major epidemiologic benefits in seasonal and pandemic influenza.

Influenza virus and SARS-CoV-2: pathogenesis and host responses in the respiratory tract

Influenza viruses cause annual epidemics and occasional pandemics of respiratory tract infections that produce a wide spectrum of clinical disease severity in humans. The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 and has since caused a pandemic. Both viral and host factors determine the extent and severity of virus-induced lung damage. The host's response to viral infection is necessary for viral clearance but may be deleterious and contribute to severe disease phenotypes. Similarly, tissue repair mechanisms are required for recovery from infection across the spectrum of disease severity; however, dysregulated repair responses may lead to chronic lung dysfunction. Understanding of the mechanisms of immunopathology and tissue repair following viral lower respiratory tract infection may broaden treatment options. In this Review, we discuss the pathogenesis, the contribution of the host response to severe clinical phenotypes and highlight early and late epithelial repair mechanisms following influenza virus infection, each of which has been well characterized. Although we are still learning about SARS-CoV-2 and its disease manifestations in humans, throughout the Review we discuss what is known about SARS-CoV-2 in the context of this broad knowledge of influenza virus, highlighting the similarities and differences between the respiratory viruses.

COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit

This paper describes a data-driven simulation study that explores the relative impact of several low-cost and practical non-pharmaceutical interventions on the spread of COVID-19 in an outpatient hospital dialysis unit. The interventions considered include: (i) voluntary self-isolation of healthcare personnel (HCPs) with symptoms; (ii) a program of active syndromic surveillance and compulsory isolation of HCPs; (iii) the use of masks or respirators by patients and HCPs; (iv) improved social distancing among HCPs; (v) increased physical separation of dialysis stations; and (vi) patient isolation combined with preemptive isolation of exposed HCPs. Our simulations show that under conditions that existed prior to the COVID-19 outbreak, extremely high rates of COVID-19 infection can result in a dialysis unit. In simulations under worst-case modeling assumptions, a combination of relatively inexpensive interventions such as requiring surgical masks for everyone, encouraging social distancing between healthcare professionals (HCPs), slightly increasing the physical distance between dialysis stations, and-once the first symptomatic patient is detected-isolating that patient, replacing the HCP having had the most exposure to that patient, and relatively short-term use of N95 respirators by other HCPs can lead to a substantial reduction in both the attack rate and the likelihood of any spread beyond patient zero. For example, in a scenario with R0 = 3.0, 60% presymptomatic viral shedding, and a dialysis patient being the infection source, the attack rate falls from 87.8% at baseline to 34.6% with this intervention bundle. Furthermore, the likelihood of having no additional infections increases from 6.2% at baseline to 32.4% with this intervention bundle.

Pharmacokinetic and pharmacodynamic analysis of baloxavir marboxil, a novel cap-dependent endonuclease inhibitor, in a murine model of influenza virus infection

Background

Baloxavir acid, the active form of the orally available prodrug baloxavir marboxil, is a novel cap-dependent endonuclease inhibitor of influenza virus. Baloxavir marboxil has been shown to rapidly reduce virus titres compared with oseltamivir in clinical studies.

Objectives

We investigated the relationship between pharmacokinetic (PK) parameters and antiviral activity of baloxavir acid based on virus titre reduction in lungs of infected mice.

Methods

BALB/c mice infected with a sub-lethal dose of influenza A(H1N1), A(H1N1)pdm09, A(H3N2) or type B virus were treated on day 5 with oral baloxavir marboxil (0.5–50 mg/kg q12h), subcutaneous baloxavir acid (0.25–8 mg/kg/day), oseltamivir phosphate (5 or 50 eq mg/kg q12h) or other antivirals for 1 day. Lung virus titres were assessed 24 h after initial antiviral dosing. PK testing was performed at up to 24 h post-dosing of baloxavir marboxil or baloxavir acid in A/WSN/33-infected mice and the PK/pharmacodynamic (PD) relationship was evaluated for baloxavir acid.

Results

Oral baloxavir marboxil administration showed dose-dependent virus titre reductions in lungs of mice infected with the different types/subtypes of influenza viruses 24 h post-dosing. Baloxavir marboxil at 15 mg/kg q12h resulted in ≥100-fold and ≥10-fold reductions in influenza A and B virus titres, respectively, compared with oseltamivir phosphate. PK/PD analysis showed that the plasma concentration at the end of the dosing interval (C_τ) or the plasma concentration at 24 h after initial dosing (C₂₄) was the PK parameter predicting the virus titres at 24 h post-dosing of baloxavir acid.

Conclusions

PK/PD analysis of baloxavir acid based on virus titre reduction in this mouse model could be helpful in predicting and maximizing virological outcomes in clinical settings.

Anomalous influenza seasonality in the United States and the emergence of novel influenza B viruses

The 2019/2020 influenza season in the United States began earlier than any season since the 2009 H1N1 pandemic, with an increase in influenza-like illnesses observed as early as August. Also noteworthy was the numerical domination of influenza B cases early in this influenza season, in contrast to their typically later peak in the past. Here, we dissect the 2019/2020 influenza season not only with regard to its unusually early activity, but also with regard to the relative dynamics of type A and type B cases. We propose that the recent expansion of a novel influenza B/Victoria clade may be associated with this shift in the composition and kinetics of the influenza season in the United States. We use epidemiological transmission models to explore whether changes in the effective reproduction number or short-term cross-immunity between these viruses can explain the dynamics of influenza A and B seasonality. We find support for an increase in the effective reproduction number of influenza B, rather than support for cross-type immunity-driven dynamics. Our findings have clear implications for optimal vaccination strategies.

Australia's notifiable disease status, 2016: Annual report of the National Notifiable Diseases Surveillance System

Abstract

In 2016, a total of 67 diseases and conditions were nationally notifiable in Australia. The states and territories reported 330,387 notifications of communicable diseases to the National Notifiable Diseases Surveillance System. Notifications have remained stable between 2015 and 2016. In 2016, the most frequently notified diseases were vaccine preventable diseases (139,687 notifications, 42% of total notifications); sexually transmissible infections (112,714 notifications, 34% of total notifications); and gastrointestinal diseases (49,885 notifications, 15% of total notifications). Additionally, there were 18,595 notifications of bloodborne diseases; 6,760 notifications of vectorborne diseases; 2,020 notifications of other bacterial infections; 725 notifications of zoonoses and one notification of a quarantinable disease.

Using video-analysis technology to estimate social mixing and simulate influenza transmission at a mass gathering

Mass gatherings create settings conducive to infectious disease transmission. Empirical data to model infectious disease transmission at mass gatherings are limited. Video-analysis technology could be used to generate data on social mixing patterns needed for simulating influenza transmission at mass gatherings. We analyzed short video recordings of persons attending the GameFest event at a university in Troy, New York, in April 2013 to demonstrate the feasibility of this approach. Attendees were identified and tracked during three randomly selected time periods using an object-tracking algorithm. Tracks were analyzed to calculate the number and duration of unique pairwise contacts. A contact occurred each time two attendees were within 2 m of each other. We built and tested an agent-based stochastic influenza simulation model assuming two scenarios of mixing patterns in a geospatially accurate representation of the event venue -one calibrated to the mean cumulative contact duration estimated from GameFest video recordings and the other using a uniform mixing pattern. We compared one-hour attack rates (i.e., becoming infected) generated from these two scenarios following the introduction of a single infectious seed. Across the video recordings, 278 attendees were identified and tracked, resulting in 1,247 unique pairwise contacts with a cumulative mean contact duration of 74.76 s (SD: 80.71). The one-hour simulated mean attack rates were 2.17 % (95 % CI:1.45 - 2.82) and 0.21 % (95 % CI: 0.14 - 0.28) in the calibrated and uniform mixing model scenarios, respectively. We simulated influenza transmission at the GameFest event using social mixing data objectively captured through video-analysis technology. Microlevel geospatially accurate simulations can be used to assess the layout of event venues on social mixing and disease transmission. Future work can expand on this demonstration project to larger spatial and temporal scenes in more diverse settings.

Secondary attack rates from asymptomatic and symptomatic influenza virus shedders in hospitals: Results from the TransFLUas influenza transmission study

Objective:

Nosocomial transmission of influenza is a major concern for infection control. We aimed to dissect transmission dynamics of influenza, including asymptomatic transmission events, in acute care.

Design:

Prospective surveillance study during 2 influenza seasons.

Setting:

Tertiary-care hospital.

Participants:

Volunteer sample of inpatients on medical wards and healthcare workers (HCWs).

Methods:

Participants provided daily illness diaries and nasal swabs for influenza A and B detection and whole-genome sequencing for phylogenetic analyses. Contacts between study participants were tracked. Secondary influenza attack rates were calculated based on spatial and temporal proximity and phylogenetic evidence for transmission.

Results:

In total, 152 HCWs and 542 inpatients were included; 16 HCWs (10.5%) and 19 inpatients (3.5%) tested positive for influenza on 109 study days. Study participants had symptoms of disease on most of the days they tested positive for influenza (83.1% and 91.9% for HCWs and inpatients, respectively). Also, 11(15.5%) of 71 influenza-positive swabs among HCWs and 3 (7.9%) of 38 influenza-positive swabs among inpatients were collected on days without symptoms; 2 (12.5%) of 16 HCWs and 2 (10.5%) of 19 inpatients remained fully asymptomatic. The secondary attack rate was low: we recorded 1 transmission event over 159 contact days (0.6%) that originated from a symptomatic case. No transmission event occurred in 61 monitored days of contacts with asymptomatic influenza-positive individuals.

Conclusions:

Influenza in acute care is common, and individuals regularly shed influenza virus without harboring symptoms. Nevertheless, both symptomatic and asymptomatic transmission events proved rare. We suggest that healthcare-associated influenza prevention strategies that are based on preseason vaccination and barrier precautions for symptomatic individuals seem to be effective.

Healthcare Resource Use and Burden Associated with Influenza Transmission Among Household Members with a Primary Infection: Commercial Claims Data Analysis

PURPOSE

To assess the burden of influenza transmission and care-seeking patterns over 3 influenza seasons among commercially insured households with a primary influenza infection.

PATIENTS AND METHODS

This retrospective cohort study used commercial claims data from the US MarketScan® Commercial and Medicare Supplemental databases for the 2014, 2015, and 2016 influenza seasons. Patients with a billed diagnosis of influenza and with coverage for at least 1 household member under the same health plan policy were included. A secondary diagnosed case was defined as a diagnosis of influenza in a second household member occurring within 14 days of the index case in a household.

RESULTS

Among 1,224,808 households with ≥2 members and a primary case of influenza, a secondary case of influenza was reported in 119,883 households (9.8%). A secondary diagnosed case of influenza occurred within 4 days of the primary diagnosis in 93,883 (78.3%) of those households. Both primary and secondary diagnosed influenza cases occurred most often among children (~60%). Household size was positively correlated to both the risk of a second case (6.4% of households with 2 or 3 members versus 12.6% of households with ≥4 members, P < 0.001) and the time to diagnosis of a second case (Spearman rank correlation coefficient = 0.09; P < 0.001).

CONCLUSION

Claims data for 3 influenza seasons (2014, 2015, 2016) showed that intrahousehold transmission of influenza occurs in approximately 10% of households with a primary case and poses a higher burden on larger households. Intrahousehold transmission of influenza represents a large healthcare resource use burden, with an unmet need for interventions that limit transmission.

Duration of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infectivity: When Is It Safe to Discontinue Isolation?

Defining the duration of infectivity of SARS-CoV-2 has major implications for public health and infection control practice in healthcare facilities. Early in the pandemic, most hospitals required two negative RT-PCR tests before discontinuing isolation in patients with Covid-19. Many patients, however, have persistently positive RT-PCR tests for weeks to months following clinical recovery and multiple studies now indicate that persistently positive RT-PCRs generally do not reflect replication-competent virus. SARS-CoV-2 appears to be most contagious around the time of symptom onset and infectivity rapidly decreases thereafter to near-zero after about 10 days in mild-moderately ill patients and 15 days in severely-critically ill and immunocompromised patients. The longest interval associated with replication-competent virus thus far is 20 days from symptom onset. This review summarizes evidence-to-date on the duration of infectivity of SARS-CoV-2 and how this has informed evolving public health recommendations on when it is safe to discontinue isolation precautions.

Waning of Measured Influenza Vaccine Effectiveness Over Time: The Potential Contribution of Leaky Vaccine Effect

BACKGROUND

Several observational studies have shown decreases in measured influenza vaccine effectiveness (mVE) during influenza seasons. One study found decreases of 6-11%/month during the 2011-2012 to 2014-2015 seasons. These findings could indicate waning immunity but could also occur if vaccine effectiveness is stable and vaccine provides partial protection in all vaccinees ("leaky") rather than complete protection in a subset of vaccinees. Since it is unknown whether influenza vaccine is leaky, we simulated the 2011-2012 to 2014-2015 influenza seasons to estimate the potential contribution of leaky vaccine effect to the observed decline in mVE.

METHODS

We used available data to estimate daily numbers of vaccinations and infections with A/H1N1, A/H3N2, and B viruses. We assumed that vaccine effect was leaky, calculated mVE as 1 minus the Mantel-Haenszel relative risk of vaccine on incident cases, and determined the mean mVE change per 30 days since vaccination. Because change in mVE was highly dependent on infection rates, we performed simulations using low (15%) and high (31%) total (including symptomatic and asymptomatic) seasonal infection rates.

RESULTS

For the low infection rate, decreases (absolute) in mVE per 30 days after vaccination were 2% for A/H1N1 and 1% for A/H3N2and B viruses. For the high infection rate, decreases were 5% for A/H1N1, 4% for A/H3, and 3% for B viruses.

CONCLUSIONS

The leaky vaccine bias could account for some, but probably not all, of the observed intraseasonal decreases in mVE. These results underscore the need for strategies to deal with intraseasonal vaccine effectiveness decline.

Person-to-Person Transmission of Avian Influenza A (H7N9) Among Family Members in Eastern China, 2016

Objective:

Human infections with avian influenza A (H7N9) virus are associated with exposure to poultry and live poultry markets, but the evidence of person-to-person transmission remains limited. This study reports a suspected person-to-person transmission of H7N9 virus, and explores what factors influenced this transmission.

Methods:

We interviewed 2 patients with H7N9 infection and their family members as well as health-care workers. Samples from the patients and environments were tested by real-time reverse transcription-polymerase chain reaction.

Results:

The index patient became ill 5 to 6 days after his last exposure to the poultry bought in the market of Weimiao town. The second patient, the sister of the index patient, who had sustained intensive and unprotected close contact with the index patient, had no exposure to poultry. This study documents that the H7N9 virus was transmitted directly from the index patient to his sister.

Conclusions:

Our findings suggest that person-to-person transmission may be associated with sustained close contact with the patient during his onset of early stage, when the H7N9 viral shedding increases sharply.

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19

Background

Non-pharmaceutical interventions such as social distancing, school closures and travel restrictions are often implemented to control outbreaks of infectious diseases. For influenza in schools, the Center of Disease Control (CDC) recommends that febrile students remain isolated at home until they have been fever-free for at least one day and a related policy is recommended for SARS-CoV-2 (COVID-19). Other authors proposed using a school week of four or fewer days of in-person instruction for all students to reduce transmission. However, there is limited evidence supporting the effectiveness of these interventions.

Methods

We introduced a mathematical model of school outbreaks that considers both intervention methods. Our model accounts for the school structure and schedule, as well as the time-progression of fever symptoms and viral shedding. The model was validated on outbreaks of seasonal and pandemic influenza and COVID-19 in schools. It was then used to estimate the outbreak curves and the proportion of the population infected (attack rate) under the proposed interventions.

Results

For influenza, the CDC-recommended one day of post-fever isolation can reduce the attack rate by a median (interquartile range) of 29 (13–59)%. With 2 days of post-fever isolation the attack rate could be reduced by 70 (55–85)%. Alternatively, shortening the school week to 4 and 3 days reduces the attack rate by 73 (64–88)% and 93 (91–97)%, respectively. For COVID-19, application of post-fever isolation policy was found to be less effective and reduced the attack rate by 10 (5–17)% for a 2-day isolation policy and by 14 (5–26)% for 14 days. A 4-day school week would reduce the median attack rate in a COVID-19 outbreak by 57 (52–64)%, while a 3-day school week would reduce it by 81 (79–83)%. In both infections, shortening the school week significantly reduced the duration of outbreaks.

Conclusions

Shortening the school week could be an important tool for controlling influenza and COVID-19 in schools and similar settings. Additionally, the CDC-recommended post-fever isolation policy for influenza could be enhanced by requiring two days of isolation instead of one.

Early oseltamivir treatment improves survival in critically ill patients with influenza pneumonia

Background

The relationship between early oseltamivir treatment (within 48 h of symptom onset) and mortality in patients admitted to intensive care units (ICUs) with severe influenza is disputed. This study aimed to investigate the association between early oseltamivir treatment and ICU mortality in critically ill patients with influenza pneumonia.

Methods

This was an observational study of patients with influenza pneumonia admitted to 184 ICUs in Spain during 2009-2018. The primary outcome was to evaluate the association between early oseltamivir treatment and ICU mortality compared with later treatment. Secondary outcomes were to compare the duration of mechanical ventilation and ICU length of stay between the early and later oseltamivir treatment groups. To reduce biases related to observational studies, propensity score matching and a competing risk analysis were performed.

Results

During the study period, 2124 patients met the inclusion criteria. All patients had influenza pneumonia and received oseltamivir before ICU admission. Of these, 529 (24.9%) received early oseltamivir treatment. In the multivariate analysis, early treatment was associated with reduced ICU mortality (OR 0.69, 95% CI 0.51-0.95). After propensity score matching, early oseltamivir treatment was associated with improved survival rates in the Cox regression (hazard ratio 0.77, 95% CI 0.61-0.99) and competing risk (subdistribution hazard ratio 0.67, 95% CI 0.53-0.85) analyses. The ICU length of stay and duration of mechanical ventilation were shorter in patients receiving early treatment.

Conclusions

Early oseltamivir treatment is associated with improved survival rates in critically ill patients with influenza pneumonia, and may decrease ICU length of stay and mechanical ventilation duration.

Paid Leave and Access to Telework as Work Attendance Determinants during Acute Respiratory Illness, United States, 2017-2018

We assessed determinants of work attendance during the first 3 days after onset of acute respiratory illness (ARI) among workers 19-64 years of age who had medically attended ARI or influenza during the 2017-2018 influenza season. The total number of days worked included days worked at the usual workplace and days teleworked. Access to paid leave was associated with fewer days worked overall and at the usual workplace during illness. Participants who indicated that employees were discouraged from coming to work with influenza-like symptoms were less likely to attend their usual workplace. Compared with workers without a telework option, those with telework access worked more days during illness overall, but there was no difference in days worked at the usual workplace. Both paid leave benefits and business practices that actively encourage employees to stay home while sick are necessary to reduce the transmission of ARI and influenza in workplaces.

Symptoms, Infection Duration, and Hemagglutinin Inhibition Antibody Response in Influenza A Infections

BACKGROUND

Many influenza studies assume that symptomatic and asymptomatic cases have equivalent antibody responses.

METHODS

This study examines the relationship between influenza symptoms and serological response. Influenza-positive index cases and household members in Managua, Nicaragua, during 2012-2017 were categorized by symptom status.

RESULTS

Antibody response was assessed using hemagglutination inhibition assays (HAI). Among 510 cases, 74.5% had ≥4-fold increase in HAI antibodies, and 75.3% had febrile illness. In a logistic regression model, febrile cases had 2.17 times higher odds of a ≥4-fold titer rise compared to asymptomatic cases (95% confidence interval, 1.02-4.64).

CONCLUSIONS

Studies relying on serological assays may not generalize to asymptomatic infections.

Health inequities in influenza transmission and surveillance

The lower an individual's socioeconomic position, the higher their risk of poor health in low-, middle-, and high-income settings alike. As health inequities grow, it is imperative that we develop an empirically-driven mechanistic understanding of the determinants of health disparities, and capture disease burden in at-risk populations to prevent exacerbation of disparities. Past work has been limited in data or scope and has thus fallen short of generalizable insights. Here, we integrate empirical data from observational studies and large-scale healthcare data with models to characterize the dynamics and spatial heterogeneity of health disparities in an infectious disease case study: influenza. We find that variation in social and healthcare-based determinants exacerbates influenza epidemics, and that low socioeconomic status (SES) individuals disproportionately bear the burden of infection. We also identify geographical hotspots of influenza burden in low SES populations, much of which is overlooked in traditional influenza surveillance, and find that these differences are most predicted by variation in susceptibility and access to sickness absenteeism. Our results highlight that the effect of overlapping factors is synergistic and that reducing this intersectionality can significantly reduce inequities. Additionally, health disparities are expressed geographically, and targeting public health efforts spatially may be an efficient use of resources to abate inequities. The association between health and socioeconomic prosperity has a long history in the epidemiological literature; addressing health inequities in respiratory-transmitted infectious disease burden is an important step towards social justice in public health, and ignoring them promises to pose a serious threat.

What Role Does Pathogen-Avoidance Psychology Play in Pandemics?

A substantial body of research has illuminated psychological adaptations motivating pathogen avoidance, mechanisms collectively known as the behavioral immune system. Can knowledge about these mechanisms inform how people respond to widespread disease outbreaks, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [coronavirus disease 2019 (COVID-19)] pandemic? We review evidence suggesting that the evolutionary history of the behavioral immune system, and the cues that activate it, are distinct in many ways from modern human experiences with pandemics. Moreover, the behaviors engaged by this system may have limited utility for combating pandemic diseases like COVID-19. A better understanding of the points of distinction and points of overlap between our evolved pathogen-avoidance psychology and responses to pandemics may help us realize a more precise and intervention-ready science.

Understanding the outcomes of COVID-19 - does the current model of an acute respiratory infection really fit?

Although coronavirus disease 2019 (COVID-19) is regarded as an acute, resolving infection followed by the development of protective immunity, recent systematic literature review documents evidence for often highly prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in respiratory and faecal samples, periodic recurrence of PCR positivity in a substantial proportion of individuals and increasingly documented instances of reinfection associated with a lack of protective immunity. This pattern of infection is quite distinct from the acute/resolving nature of other human pathogenic respiratory viruses, such as influenza A virus and respiratory syncytial virus. Prolonged shedding of SARS-CoV-2 furthermore occurs irrespective of disease severity or development of virus-neutralizing antibodies. SARS-CoV-2 possesses an intensely structured RNA genome, an attribute shared with other human and veterinary coronaviruses and with other mammalian RNA viruses such as hepatitis C virus. These are capable of long-term persistence, possibly through poorly understood RNA structure-mediated effects on innate and adaptive host immune responses. The assumption that resolution of COVID-19 and the appearance of anti-SARS-CoV-2 IgG antibodies represents virus clearance and protection from reinfection, implicit for example in the susceptible-infected-recovered (SIR) model used for epidemic prediction, should be rigorously re-evaluated.

Performance of BioFire array or QuickVue influenza A + B test versus a validation qPCR assay for detection of influenza A during a volunteer A/California/2009/H1N1 challenge study

Background

Influenza places a significant burden on global health and economics. Individual case management and public health efforts to mitigate the spread of influenza are both strongly impacted by our ability to accurately and efficiently detect influenza viruses in clinical samples. Therefore, it is important to understand the performance characteristics of available assays to detect influenza in a variety of settings. We provide the first report of relative performance between two products marketed to streamline detection of influenza virus in the context of a highly controlled volunteer influenza challenge study.

Methods

Nasopharyngeal swab samples were collected during a controlled A/California/2009/H1N1 influenza challenge study and analyzed for detection of virus shedding using a validated qRT-PCR (qPCR) assay, a sample-to-answer qRT-PCR device (BioMerieux BioFire FilmArray RP), and an immunoassay based rapid test kit (Quidel QuickVue Influenza A + B Test).

Results

Relative to qPCR, the sensitivity and specificity of the BioFire assay was 72.1% [63.7–79.5%, 95% confidence interval (CI)] and 93.5% (89.3–96.4%, 95% CI) respectively. For the QuickVue rapid test the sensitivity was 8.5% (4.8–13.7%, 95% CI) and specificity was 99.2% (95.6–100%, 95% CI).

Conclusion

Relative to qPCR, the BioFire assay had superior performance compared to rapid test in the context of a controlled influenza challenge study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-021-01516-0.

Vaccines That Reduce Viral Shedding Do Not Prevent Transmission of H1N1 Pandemic 2009 Swine Influenza A Virus Infection to Unvaccinated Pigs

Swine influenza A virus (swIAV) infection causes substantial economic loss and disease burden in humans and animals. The 2009 pandemic H1N1 (pH1N1) influenza A virus is now endemic in both populations. In this study, we evaluated the efficacy of different vaccines in reducing nasal shedding in pigs following pH1N1 virus challenge. We also assessed transmission from immunized and challenged pigs to naive, directly in-contact pigs. Pigs were immunized with either adjuvanted, whole inactivated virus (WIV) vaccines or virus-vectored (ChAdOx1 and MVA) vaccines expressing either the homologous or heterologous influenza A virus hemagglutinin (HA) glycoprotein, as well as an influenza virus pseudotype (S-FLU) vaccine expressing heterologous HA. Only two vaccines containing homologous HA, which also induced high hemagglutination inhibitory antibody titers, significantly reduced virus shedding in challenged animals. Nevertheless, virus transmission from challenged to naive, in-contact animals occurred in all groups, although it was delayed in groups of vaccinated animals with reduced virus shedding.IMPORTANCE This study was designed to determine whether vaccination of pigs with conventional WIV or virus-vectored vaccines reduces pH1N1 swine influenza A virus shedding following challenge and can prevent transmission to naive in-contact animals. Even when viral shedding was significantly reduced following challenge, infection was transmissible to susceptible cohoused recipients. This knowledge is important to inform disease surveillance and control strategies and to determine the vaccine coverage required in a population, thereby defining disease moderation or herd protection. WIV or virus-vectored vaccines homologous to the challenge strain significantly reduced virus shedding from directly infected pigs, but vaccination did not completely prevent transmission to cohoused naive pigs.

Estimating and interpreting secondary attack risk: Binomial considered biased

The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. Estimation of the SAR is an important part of understanding and controlling the transmission of infectious diseases. In practice, it is most often estimated using binomial models such as logistic regression, which implicitly attribute all secondary infections in a household to the primary case. In the simplest case, the number of secondary infections in a household with m susceptibles and a single primary case is modeled as a binomial(m, p) random variable where p is the SAR. Although it has long been understood that transmission within households is not binomial, it is thought that multiple generations of transmission can be neglected safely when p is small. We use probability generating functions and simulations to show that this is a mistake. The proportion of susceptible household members infected can be substantially larger than the SAR even when p is small. As a result, binomial estimates of the SAR are biased upward and their confidence intervals have poor coverage probabilities even if adjusted for clustering. Accurate point and interval estimates of the SAR can be obtained using longitudinal chain binomial models or pairwise survival analysis, which account for multiple generations of transmission within households, the ongoing risk of infection from outside the household, and incomplete follow-up. We illustrate the practical implications of these results in an analysis of household surveillance data collected by the Los Angeles County Department of Public Health during the 2009 influenza A (H1N1) pandemic.

The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. The most common statistical models used to estimate the SAR are binomial models such as logistic regression, which implicitly assume that all secondary infections in a household are infected by the primary case. Here, we use analytical calculations and simulations to show that estimation of the SAR must account for multiple generations of transmission within households. As an example, we show that binomial models and statistical models that account for multiple generations of within-household transmission reach different conclusions about the household SAR for 2009 influenza A (H1N1) in Los Angeles County, with the latter models fitting the data better. In an epidemic, accurate estimation of the SAR allows rigorous evaluation of the effectiveness of public health interventions such as social distancing, prophylaxis or treatment, and vaccination.

Efficacy comparison of oseltamivir alone and oseltamivir-antibiotic combination for early resolution of symptoms of severe influenza-A and influenza-B hospitalized patients

Objectives:

To assess the comparative efficacy of oseltamivir alone and oseltamivir-antibiotic therapy for early relief of symptoms associated with severe influenza-A (non-H1N1) and influenza-B infection hospitalized patients.

Methods:

In this retrospective multicenter study conducted from 2016-2019, enrolled patients were divided into 2 treatment groups. Group 1 patients were started on Antiviral drug (oseltamivir) alone therapy. Group 2 patients were initiated on Antiviral drug (oseltamivir) in combination with Antibiotic therapy. Using acute respiratory illness scoring, symptom severity score was assessed daily for 8 symptoms namely, fever, fatigue, headache, cough, sore throat, wheezing, muscle ache and nasal congestion. For each symptom the severity was scored from scale 0-3.

Results:

Overall mean ARI severity score was statistically significantly lower (p<0.05) on day 2 (14.65-vs-13.68), day 3 (12.95-vs-11.67) and day 4 (10.31-vs-9.12 ) for influenza-A (non-H1N1) while day 3 (12.52-vs-11.87) and day 4 (11.21-vs-10.18) for influenza-B patients for patients who were initiated on oseltamivir-antibiotic combination therapy. Fever, cough and nasal congestion showed statistically significant improvement within 4 days of initiation of combination treatment. Fatigue, sore throat and muscle ache improvement pattern was same for both treatment protocols.

Conclusion:

Oseltamivir-antibiotic combination treatment showed early resolution of some symptoms with cumulatively reduced mean symptom severity score in severe influenza infection hospitalized patients.

Multi-route respiratory infection: When a transmission route may dominate

The exact transmission route of many respiratory infectious diseases remains a subject for debate to date. The relative contribution ratio of each transmission route is largely undetermined, which is affected by environmental conditions, human behaviour, the host and the microorganism. In this study, a detailed mathematical model is developed to investigate the relative contributions of different transmission routes to a multi-route transmitted respiratory infection. The following transmission routes are considered: long-range airborne transmission, short-range airborne transmission, direction inhalation of medium droplets or droplet nuclei, direct deposition of droplets of all sizes, direct and indirect contact route. It is illustrated that all transmission routes can dominate the total transmission risk under different scenarios. Influential parameters considered include the dose-response rate of different routes, droplet governing size that determines pathogen content in droplets, exposure distance, and pathogen dose transported to the hand of infector. Our multi-route transmission model provided a comprehensive but straightforward method to evaluate the probability of respiratory diseases transmission via different routes. It also established a basis for predicting the impact of individual-level intervention methods such as increasing close-contact distance and wearing protective masks.

Mitigation of biases in estimating hazard ratios under non-sensitive and non-specific observation of outcomes-applications to influenza vaccine effectiveness

Background

Non-sensitive and non-specific observation of outcomes in time-to-event data affects event counts as well as the risk sets, thus, biasing the estimation of hazard ratios. We investigate how imperfect observation of incident events affects the estimation of vaccine effectiveness based on hazard ratios.

Methods

Imperfect time-to-event data contain two classes of events: a portion of the true events of interest; and false-positive events mistakenly recorded as events of interest. We develop an estimation method utilising a weighted partial likelihood and probabilistic deletion of false-positive events and assuming the sensitivity and the false-positive rate are known. The performance of the method is evaluated using simulated and Finnish register data.

Results

The novel method enables unbiased semiparametric estimation of hazard ratios from imperfect time-to-event data. False-positive rates that are small can be approximated to be zero without inducing bias. The method is robust to misspecification of the sensitivity as long as the ratio of the sensitivity in the vaccinated and the unvaccinated is specified correctly and the cumulative risk of the true event is small.

Conclusions

The weighted partial likelihood can be used to adjust for outcome measurement errors in the estimation of hazard ratios and effectiveness but requires specifying the sensitivity and the false-positive rate. In absence of exact information about these parameters, the method works as a tool for assessing the potential magnitude of bias given a range of likely parameter values.

Influenza A Reinfection in Sequential Human Challenge: Implications for Protective Immunity and "Universal" Vaccine Development

BACKGROUND

Identification of correlates of protection against human influenza A virus infection is important in development of broadly protective ("universal") influenza vaccines. Certain assumptions underlie current vaccine developmental strategies, including that infection with a particular influenza A virus should offer long-term or lifelong protection against that strain, preventing reinfection. In this study we report observations made when 7 volunteers participated in sequential influenza challenge studies where they were challenged intranasally using the identical influenza A(H1N1)pdm09 virus approximately 1 year apart. We evaluate and describe the outcomes of these 7 rechallenge participants and discuss what these results may suggest about correlates of protection and development of more broadly protective influenza vaccines.

METHODS

Seven participants were enrolled in 2 viral challenge studies at 7.5- to 18.5-month intervals. Both challenge studies used the identical lot of influenza A (H1N1)pdm09 virus administered intranasally. We evaluated pre- and postchallenge hemagglutination inhibition, neuraminidase inhibition, and stalk antibody titers; peripheral blood leukocyte host gene expression response profiles; daily viral detection via nasal wash; and clinical signs and symptoms.

RESULTS

At least 3 of 7 participants demonstrated confirmed laboratory evidence of sequential infection, with 5 of 7 demonstrating clinical evidence.

CONCLUSIONS

The data presented in this report demonstrate that sequential infection with the identical influenza A virus can occur and suggest it may not be rare. These data raise questions about immune memory responses in an acute superficial respiratory mucosal infection and their implications in development of broadly protective influenza vaccines. Further investigation of these observations is warranted.

CLINICAL TRIALS REGISTRATION

NCT01646138; NCT01971255.

Prevention of Respiratory Syncytial Virus Infection in Healthy Adults by a Single Immunization of Ad26.RSV.preF in a Human Challenge Study

BACKGROUND

Respiratory syncytial virus (RSV) is a significant cause of severe lower respiratory tract disease in children and older adults, but has no approved vaccine. This study assessed the potential of Ad26.RSV.preF to protect against RSV infection and disease in an RSV human challenge model.

METHODS

In this double-blind, placebo-controlled study, healthy adults aged 18-50 years were randomized 1:1 to receive 1x1011 vp Ad26.RSV.preF or placebo intramuscularly. Twenty-eight days post-immunization, volunteers were challenged intranasally with RSV-A (Memphis 37b). Assesments included viral load (VL), RSV infections, clinical symptom score (CSS), safety and immunogenicity.

RESULTS

Post-challenge, VL, RSV infections and disease severity were lower in Ad26.RSV.preF (n=27) versus placebo (n=26) recipients: median VL-AUC (area under the curve) qRT-PCR: 0.0 versus 236.0 (P=.012; predefined primary endpoint); median VL-AUC quantitative culture: 0.0 versus 109; RSV infections 11 (40.7%) versus 17 (65.4%); median RSV AUC-CSS 35 versus 167, respectively. From baseline to 28 days post-immunization, geometric mean fold-increases in RSV A2 neutralizing antibody titers of 5.8 and 0.9 were observed in Ad26.RSV.preF and placebo, respectively. Ad26.RSV.preF was well tolerated.

CONCLUSIONS

Ad26.RSV.preF demonstrated protection from RSV infection through immunization in a human challenge model, and therefore could potentially protect against natural RSV infection and disease.

CLINICAL TRIALS REGISTRATION

NCT03334695.

Cost-Effectiveness of Quadrivalent Versus Trivalent Influenza Vaccination in the Dutch National Influenza Prevention Program

OBJECTIVES

As of 2019, quadrivalent influenza vaccine (QIV) has replaced trivalent influenza vaccine (TIV) in the national immunization program in The Netherlands. Target groups are individuals of 60+ years of age and those with chronic diseases. The objective was to estimate the incremental break-even price of QIV over TIV at a threshold of €20 000 per quality-adjusted life-year (QALY).

METHODS

An age-structured compartmental dynamic model was adapted for The Netherlands to assess health outcomes and associated costs of vaccinating all individuals at higher risk for influenza with QIV instead of TIV over the seasons 2010 to 2018. Influenza incidence rates were derived from a global database. Other parameters (probabilities, QALYs and costs) were extracted from the literature and applied according to Dutch guidelines. A threshold of €20 000 per QALY was applied to estimate the incremental break-even prices of QIV versus TIV. Sensitivity analyses were performed to test the robustness of the model outcomes.

RESULTS

Retrospectively, vaccination with QIV instead of TIV could have prevented on average 9500 symptomatic influenza cases, 2130 outpatient visits, 84 hospitalizations, and 38 deaths per year over the seasons 2010 to 2018. This translates into 385 QALYs and 398 life-years potentially gained. On average, totals of €431 527 direct and €2 388 810 indirect costs could have been saved each year.

CONCLUSION

Using QIV over TIV during the influenza seasons 2010 to 2018 would have been cost-effective at an incremental price of maximally €3.81 (95% confidence interval, €3.26-4.31). Sensitivity analysis showed consistent findings on the incremental break-even price in the same range.

Influenza A (H3) illness and viral aerosol shedding from symptomatic naturally infected and experimentally infected cases

BACKGROUND

It has long been known that nasal inoculation with influenza A virus produces asymptomatic to febrile infections. Uncertainty persists about whether these infections are sufficiently similar to natural infections for studying human-to-human transmission.

METHODS

We compared influenza A viral aerosol shedding from volunteers nasally inoculated with A/Wisconsin/2005 (H3N2) and college community adults naturally infected with influenza A/H3N2 (2012-2013), selected for influenza-like illness with objectively measured fever or a positive Quidel QuickVue A&B test. Propensity scores were used to control for differences in symptom presentation observed between experimentally and naturally infected groups.

RESULTS

Eleven (28%) experimental and 71 (86%) natural cases shed into fine particle aerosols (P < .001). The geometric mean (geometric standard deviation) for viral positive fine aerosol samples from experimental and natural cases was 5.1E + 3 (4.72) and 3.9E + 4 (15.12) RNA copies/half hour, respectively. The 95th percentile shedding rate was 2.4 log10 greater for naturally infected cases (1.4E + 07 vs 7.4E + 04). Certain influenza-like illness-related symptoms were associated with viral aerosol shedding. The almost complete lack of symptom severity distributional overlap between groups did not support propensity score-adjusted shedding comparisons.

CONCLUSIONS

Due to selection bias, the natural and experimental infections had limited symptom severity distributional overlap precluding valid, propensity score-adjusted comparison. Relative to the symptomatic naturally infected cases, where high aerosol shedders were found, experimental cases did not produce high aerosol shedders. Studying the frequency of aerosol shedding at the highest observed levels in natural infections without selection on symptoms or fever would support helpful comparisons.

Cost-effectiveness of the cell-based quadrivalent versus the standard egg-based quadrivalent influenza vaccine in Germany

BACKGROUND

Standard influenza vaccines are produced using egg-based manufacturing methods. Through the process, the resulting egg-adapted viral strains may differ from the selected vaccine strain. Cell-derived influenza vaccine manufacturing prevents egg-adaptation of the antigen which can improve vaccine effectiveness. We evaluated the cost-effectiveness of quadrivalent cell-derived influenza vaccine (QIVc) versus an egg-based quadrivalent influenza vaccine (QIVe) in preventing seasonal influenza from German societal and payer perspectives.

METHODS

Adapted version of the individual-based dynamic 4Flu transmission model was combined with a decision-tree to calculate the impact of QIVc versus QIVe on influenza over 20 seasons in Germany. Egg-adaptation, resulting in lower effectiveness of QIVe versus QIVc towards the H3N2 influenza strain, is sourced from a US retrospective study and assumed in 100% (base case) or 55% (conservative scenario) of years. Influenza-related probabilities of outpatient visits, hospitalizations, productivity loss, and mortality, with associated (dis)utilities/costs, were extracted from literature. Costs and outcomes were discounted 3.0%/year.

RESULTS

Replacing QIVe with QIVc in subjects aged ≥ 9 years can annually prevent 167,265 symptomatic cases, 51,114 outpatient visits, 2,091 hospitalizations, and 103 deaths in Germany. The annual number of quality-adjusted life-years (QALYs) increased by 1,628 and healthcare costs decreased by €178 M from societal perspective. From payer perspective, the incremental cost-effectiveness ratio was €2,285 per QALY. Scenario analyses confirmed results robustness.

CONCLUSIONS

The use of QIVc compared to QIVe, in the German Immunization Program, could significantly prevent outpatient visits and hospitalizations and would enable substantial savings from a societal perspective.

Influenza B, C and D Viruses (Orthomyxoviridae)

This article summarizes current knowledge on the related influenza B and C viruses and considers the few studies on the recently identified influenza D virus. We focus on the particular viral genome organizations, the viral propagation cycles, as well as structural and functional insight into the encoded viral gene products. This is complemented with comprehensive sections that address the evolutionary strategies and the epidemiological significance of these influenza virus types, as well as the current state of interventions available for their control.

Cost-Effectiveness of Pediatric Influenza Vaccination in The Netherlands

OBJECTIVE

This study evaluates the cost-effectiveness of extending the Dutch influenza vaccination program for elderly and medical high-risk groups to include pediatric influenza vaccination, taking indirect protection into account.

METHODS

An age-structured dynamic transmission model was used that was calibrated to influenza-associated GP visits over 4 seasons (2010-2011 to 2013-2014). The clinical and economic impact of different pediatric vaccination strategies were compared over 20 years, varying the targeted age range, the vaccine type for children or elderly and high-risk groups. Outcome measures include averted symptomatic infections and deaths, societal costs and quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Costs and QALYs were discounted at 4% and 1.5% annually.

RESULTS

At an assumed coverage of 50%, adding pediatric vaccination for 2- to 17-year-olds with quadrivalent live-attenuated vaccine to the current vaccination program for elderly and medical high-groups with quadrivalent inactivated vaccine was estimated to avert, on average, 401 820 symptomatic cases and 72 deaths per year. Approximately half of averted symptomatic cases and 99% of averted deaths were prevented in other age groups than 2- to 17-year-olds due to herd immunity. The cumulative discounted 20-year economic impact was 35 068 QALYs gained and €1687 million saved, that is, the intervention was cost-saving. This vaccination strategy had the highest probability of being the most cost-effective strategy considered, dominating pediatric strategies targeting 2- to 6-year-olds or 2- to 12-year-olds or strategies with trivalent inactivated vaccine.

CONCLUSION

Modeling indicates that introducing pediatric influenza vaccination in The Netherlands is cost-saving, reducing the influenza-related disease burden substantially.

Cost-Effectiveness of Routine Childhood Vaccination Against Seasonal Influenza in Germany

OBJECTIVES

In Germany, routine influenza vaccination with quadrivalent influenza vaccines (QIV) is recommended and reimbursed for individuals ≥60 years of age and individuals with underlying chronic conditions. The present study examines the cost-effectiveness of a possible extension of the recommendation to include strategies of childhood vaccination against seasonal influenza using QIV.

METHODS

A dynamic transmission model was used to examine the epidemiological impact of different childhood vaccination strategies. The outputs were used in a health economic decision tree to calculate the costs per quality-adjusted life year (QALY) gained from a societal and a third-party payer (TPP) perspective. Strain-specific epidemiology, vaccine uptake, and vaccine efficacy data from the 10 non-pandemic seasons from 2003/2004 to 2013/2014 were used, and cost data were drawn mainly from a health insurance claims data analysis and supplemented by estimates from literature. Uncertainty is explored via scenario, deterministic, and probabilistic sensitivity analyses.

RESULTS

Vaccinating 2- to 9-year-olds with QIV assuming a vaccine uptake of 40% is cost-saving with a benefit-cost ratio of 1.66 from a societal perspective and an incremental cost-effectiveness ratio of €998/QALY from a TPP perspective. Lower and higher vaccine uptakes show marginal effects, while extending the target group to 2- to 17-year-olds further increases the health benefits while still being below the willingness-to-pay (WTP) threshold. Assuming no vaccine-induced herd protection has a negative effect on the cost-effectiveness ratio, but childhood vaccination remains cost-effective.

CONCLUSION

Routine childhood vaccination against seasonal influenza in Germany is most likely to be cost-saving from a societal perspective and highly cost-effective from a TPP perspective.

A method for estimating the transmissibility of influenza using serial cross-sectional seroepidemiological data

BACKGROUND

Seroepidemiological surveillance data has been demonstrated to be useful for estimating the cumulative incidence of influenza, and measures the difference between pre- and post-epidemic seropositive fractions. Despite this, such studies relied on a chosen cut-off value for seropositivity. The aim of the present study is to develop a method to analyze distributions of serial cross-sectional seroepidemiological surveillance datasets using an epidemiological model so that the transmission potential can be estimated without imposing a cut-off value.

METHODS

A mathematical model of influenza transmission with a discrete antibody titer level was constructed. The final size equation for pre- and post-epidemic titer levels was derived. Subsequently, using the estimated distribution of the dilution increase caused by infection and the measurement error distribution, the model parameters were optimized using the maximum likelihood method. A bootstrap-based confidence interval calculation and sensitivity analysis were also performed.

RESULTS

Without imposing a cut-off value, the cumulative incidence was quantified, thereby yielding an estimate of the basic reproduction number. For the purpose of exposition, the proposed method was applied to influenza A/Victoria/3/75(H3N2) data, and serological data between 1975 and 1976 were compared. The estimated reproduction number was greater than that using the cut-off value of the hemagglutination inhibition level with titer level 20 (dilution 1:20) or above to define positives.

CONCLUSION

The proposed method without a cut-off value offers an unbiased approach to estimating the cumulative incidence along with the reproduction number. If a cut-off value is required, the results imply that titer level 20 or above may better represent a reasonable cut-off value for calculating the incidence, but it could underestimate the basic reproduction number.

What drives disease flows between locations?

Communicable diseases 'flow' between locations. These flows dictate where and when certain communities will be affected. While the prediction of disease flows is essential for the timely intervention of epidemics, few studies have addressed this critical issue. This study predicts disease flows during an epidemic by considering the epidemiological, network, and temporal contextual factors using a deep learning approach. A series of scenario analyses helps identify the effects of these contextual factors on disease flows. Results show that the extended spatial-temporal effect of the epidemiological factors stimulates disease flows. The compound effects of the network factors enhance the transmission efficiency of these flows. Lastly, the temporal effect accelerates the combined effects of epidemiological and network factors on the flows. Findings of this study reveal the intricate nature of disease flows and lay a solid foundation for real-time surveillance of epidemics and pandemics to inform timely interventions for a broad range of communicable diseases.

Longitudinal sampling is required to maximize detection of intrahost A/H3N2 virus variants

Seasonal human influenza viruses continually change antigenically to escape from neutralizing antibodies. It remains unclear how genetic variation in the intrahost virus population and selection at the level of individual hosts translates to the fast-paced evolution observed at the global level because emerging intrahost antigenic variants are rarely detected. We tracked intrahost variants in the hemagglutinin and neuraminidase surface proteins using longitudinally collected samples from 52 patients infected by A/H3N2 influenza virus, mostly young children, who received oseltamivir treatment. We identified emerging putative antigenic variants and oseltamivir-resistant variants, most of which remained detectable in samples collected at subsequent days, and identified variants that emerged intrahost immediately prior to increases in global rates. In contrast to most putative antigenic variants, oseltamivir-resistant variants rapidly increased to high frequencies in the virus population. Importantly, the majority of putative antigenic variants and oseltamivir-resistant variants were first detectable four or more days after onset of symptoms or start of treatment, respectively. Our observations demonstrate that de novo variants emerge, and may be positively selected, during the course of infection. Additionally, based on the 4–7 days post-treatment delay in emergence of oseltamivir-resistant variants in six out of the eight individuals with such variants, we find that limiting sample collection for routine surveillance and diagnostic testing to early timepoints after onset of symptoms can potentially preclude detection of emerging, positively selected variants.

Quantifying mechanistic traits of influenza viral dynamics using in vitro data

When analysing in vitro data, growth kinetics of influenza virus strains are often compared by computing their growth rates, which are sometimes used as proxies for fitness. However, analogous to mathematical models for epidemics, the growth rate can be defined as a function of mechanistic traits: the basic reproduction number (the average number of cells each infected cell infects) and the mean generation time (the average length of a replication cycle). Fitting a model to previously published and newly generated data from experiments in human lung cells, we compared estimates of growth rate, reproduction number and generation time for six influenza A strains. Of four strains in previously published data, A/Canada/RV733/2003 (seasonal H1N1) had the lowest basic reproduction number, followed by A/Mexico/INDRE4487/2009 (pandemic H1N1), then A/Indonesia/05/2005 (spill-over H5N1) and A/Anhui/1/2013 (spill-over H7N9). This ordering of strains was preserved for both generation time and growth rate, suggesting a positive biological correlation between these quantities which have not been previously observed. We further investigated these potential correlations using data from reassortant viruses with different internal proteins (from A/England/195/2009 (pandemic H1N1) and A/Turkey/05/2005 (H5N1)), and the same surface proteins (from A/Puerto Rico/8/34 (lab-adapted H1N1)). Similar correlations between traits were observed for these viruses, confirming our initial findings and suggesting that these patterns were related to the degree of human adaptation of internal genes. Also, the model predicted that strains with a smaller basic reproduction number, shorter generation time and slower growth rate underwent more replication cycles by the time of peak viral load, potentially accumulating mutations more quickly. These results illustrate the utility of mathematical models in inferring traits driving observed differences in in vitro growth of influenza strains.

Effectiveness of Isolation Policies in Schools: Evidence from a Mathematical Model of Influenza and COVID-19

Background

Non-pharmaceutical interventions such as social distancing, school closures and travel restrictions are often implemented to control outbreaks of infectious diseases. For influenza in schools, the Center of Disease Control (CDC) recommends that febrile students remain isolated at home until they have been fever-free for at least one day and a related policy is recommended for SARS-CoV2 (COVID-19). Other authors proposed using a school week of four or fewer days of in-person instruction for all students to reduce transmission. However, there is limited evidence supporting the effectiveness of these interventions.

Methods

We introduced a mathematical model of school outbreaks that considers both intervention methods. Our model accounts for the school structure and schedule, as well as the time-progression of fever symptoms and viral shedding. The model was validated on outbreaks of seasonal and pandemic influenza and COVID-19 in schools. It was then used to estimate the outbreak curves and the proportion of the population infected (attack rate) under the proposed interventions.

Results

For influenza, the CDC-recommended one day of post-fever isolation can reduce the attack rate by a median (interquartile range) of 29 (13 - 59)%. With two days of post-fever isolation the attack rate could be reduced by 70 (55 - 85)%. Alternatively, shortening the school week to four and three days reduces the attack rate by 73 (64 - 88)% and 93 (91 - 97)%, respectively. For COVID-19, application of post-fever isolation policy was found to be less effective and reduced the attack rate by 10 (5 - 17)% for a two-day isolation policy and by 14 (5 - 26)% for 14 days. A four-day school week would reduce the median attack rate in a COVID-19 outbreak by 57 (52 - 64)%, while a three-day school week would reduce it by 81 (79 - 83)%. In both infections, shortening the school week significantly reduced the duration of outbreaks.

Conclusions

Shortening the school week could be an important tool for controlling influenza and COVID-19 in schools and similar settings. Additionally, the CDC-recommended post-fever isolation policy for influenza could be enhanced by requiring two days of isolation instead of one.

Influenza-associated cardiovascular mortality in older adults in Beijing, China: a population-based time-series study

OBJECTIVE

This study comprehensively estimated the excess cardiovascular disease (CVD) mortality attributable to influenza in an older (age ≥65 years) population.

DESIGN

Ecological study.

SETTING

Aggregated data from administrative systems on CVD mortality, influenza surveillance and meteorological data in Beijing, China.

MAIN OUTCOME MEASURE

Excess overall CVD, and separately for ischaemic heart disease (IHD), ischaemic stroke, haemorrhagic stroke mortality attributable to influenza, adjusting for influenza activity, time trend, seasonality and ambient temperature.

RESULTS

CVD (risk ratio (RR) 1.02, 95% CI 1.01, 1.02), IHD (RR 1.01, 95% CI 1.01, 1.02), ischaemic stroke (RR=1.03, 95% CI 1.02, 1.04), but not haemorrhagic stroke (RR=1.00, 95% CI 0.99, 1.01) mortality, were significantly associated with every 10% increase in influenza activity. An increase in circulating A(H1N1)09pdm, A(H3N2) and B type virus were all significantly associated with CVD and ischaemic stroke mortality, but only A(H3N2) and B type virus with IHD mortality. The strongest increase in disease mortality was in the same week as the increase in influenza activity. Annual excess CVD mortality rate attributable to influenza ranged from 54 to 96 per 100 000 population. The 3%-6% CVD mortality attributable to influenza activity was related to an annual excess of 916-1640 CVD deaths in Beijing, China.

CONCLUSIONS

Influenza activity has moderate to strong associations with CVD, IHD and ischaemic stroke mortality in older adults in China. Promoting influenza vaccination could have major health benefit in this population.

BACKGROUND

Influenza may trigger serious CVD events. An estimation of excess CVD mortality attributable to influenza has particular relevance in China where vaccination is low and CVD burden is high.

METHODS

This study analysed data at the population level (age ≥65 years) using linked aggregated data from administrative systems on CVD mortality, influenza surveillance and meteorological data during 2011 to 2018. Quasi-Poisson regression models were used to estimate the excess overall CVD, and separately for IHD, ischaemic stroke, haemorrhagic stroke mortality attributable to influenza, adjusting for influenza activity, time trend, seasonality and ambient temperature. Analyses were also undertaken for influenza subtypes (A(H1N1)09pdm, A(H3N2) and B viruses), and mortality risk with time lags of 1-5 weeks following influenza activity in the current week.

Landscape of coordinated immune responses to H1N1 challenge in humans

Influenza is a significant cause of morbidity and mortality worldwide. Here we show changes in the abundance and activation states of more than 50 immune cell subsets in 35 individuals over 11 time points during human A/California/2009 (H1N1) virus challenge monitored using mass cytometry along with other clinical assessments. Peak change in monocyte, B cell, and T cell subset frequencies coincided with peak virus shedding, followed by marked activation of T and NK cells. Results led to the identification of CD38 as a critical regulator of plasmacytoid dendritic cell function in response to influenza virus. Machine learning using study-derived clinical parameters and single-cell data effectively classified and predicted susceptibility to infection. The coordinated immune cell dynamics defined in this study provide a framework for identifying novel correlates of protection in the evaluation of future influenza therapeutics.

Associations Between Relative Viral Load at Diagnosis and Influenza A Symptoms and Recovery

BACKGROUND

Rapid point-of-care polymerase chain reaction (PCR) diagnostic tests generally provide a qualitative result of positive or negative only. Additional information about the relative viral load could be calculated. Such quantitative information might be useful for making treatment decisions.

METHODS

We enrolled students at a university health center who presented with cough and 1 additional flu-like symptom from December 2016 to February 2017. Data were collected before, during, and 5 days after the clinic visit. All those enrolled in the study received a point-of-care PCR test (cobas Liat). For those patients that tested positive for influenza A, we investigated correlations between the relative viral load and measures of disease severity and recovery.

RESULTS

One hundred thirty-five students tested positive for influenza A. We found a positive correlation between viral load and body temperature. Time since symptom onset seemed to have a negative correlation but was not statistically significant. We did not find any correlations between viral load and overall symptom severity or outcomes related to recovery.

CONCLUSIONS

Although we found a correlation between relative viral load and body temperature, for our study population of young, overall healthy adults, we did not find that relative viral load provided additional information that could help in determining treatment and disease outcomes. It could be that viral load does provide useful additional information for other groups of patients, such as young children or older adults. Further studies on those populations are warranted.

Pharmacological targets and emerging treatments for respiratory syncytial virus bronchiolitis

RSV infection of the lower respiratory tract in infants is the leading cause of pediatric hospitalizations and second to malaria in causing infant deaths worldwide. RSV also causes substantial morbidity in immunocompromised and elderly populations. The only available therapeutic is a prophylactic drug called Palivizumab that is a humanized monoclonal antibody, given to high-risk infants. However, this intervention is expensive and has a limited impact on annual hospitalization rates caused by RSV. No vaccine is available, nor are efficacious antivirals to treat an active infection, and there is still no consensus on how infants with bronchiolitis should be treated during hospital admission. In this comprehensive review, we briefly outline the function of the RSV proteins and their suitability as therapeutic targets. We then discuss the most promising drug candidates, their inhibitory mechanisms, and whether they are in the process of clinical trials. We also briefly discuss the reasons for some of the failures in RSV therapeutics and vaccines. In summary, we provide insight into current antiviral development and the considerations toward producing licensed antivirals and therapeutics.

The epidemiology and estimated etiology of pathogens detected from the upper respiratory tract of adults with severe acute respiratory infections in multiple countries, 2014-2015

INTRODUCTION

Etiology studies of severe acute respiratory infections (SARI) in adults are limited. We studied potential etiologies of SARI among adults in six countries using multi-pathogen diagnostics.

METHODS

We enrolled both adults with SARI (acute respiratory illness onset with fever and cough requiring hospitalization) and asymptomatic adults (adults hospitalized with non-infectious illnesses, non-household members accompanying SARI patients, adults enrolled from outpatient departments, and community members) in each country. Demographics, clinical data, and nasopharyngeal and oropharyngeal specimens were collected from both SARI patients and asymptomatic adults. Specimens were tested for presence of 29 pathogens utilizing the Taqman® Array Card platform. We applied a non-parametric Bayesian regression extension of a partially latent class model approach to estimate proportions of SARI caused by specific pathogens.

RESULTS

We enrolled 2,388 SARI patients and 1,135 asymptomatic adults from October 2013 through October 2015. We detected ≥1 pathogen in 76% of SARI patients and 67% of asymptomatic adults. Haemophilus influenzae and Streptococcus pneumoniae were most commonly detected (≥23% of SARI patients and asymptomatic adults). Through modeling, etiology was attributed to a pathogen in most SARI patients (range among countries: 57.3-93.2%); pathogens commonly attributed to SARI etiology included influenza A (14.4-54.4%), influenza B (1.9-19.1%), rhino/enterovirus (1.8-42.6%), and RSV (3.6-14.6%).

CONCLUSIONS

Use of multi-pathogen diagnostics and modeling enabled attribution of etiology in most adult SARI patients, despite frequent detection of multiple pathogens in the upper respiratory tract. Seasonal flu vaccination and development of RSV vaccine would likely reduce the burden of SARI in these populations.