Assessment of Humoral Immune Responses to Repeated Influenza Vaccination in a Multiyear Cohort: A 5-Year Follow-up.

The long-term effects of host factors on vaccine-elicited immune responses have not been well studied, and the interactions of host factors with annual influenza vaccinations are yet to be explored. We analyzed data from a cohort of 386 individuals who received the standard-dose influenza vaccine and enrolled in ≥2 seasons from 2016 to 2020. Our analyses indicated disparate vaccine-elicited immune responses between males and females in adults when they were repeatedly vaccinated for at least 2 seasons. Notably, we found interactive effects between age and body mass index (BMI) on overall immune responses, and between sex at birth and BMI in adults.

A data-driven semi-parametric model of SARS-CoV-2 transmission in the United States.

To support decision-making and policy for managing epidemics of emerging pathogens, we present a model for inference and scenario analysis of SARS-CoV-2 transmission in the USA. The stochastic SEIR-type model includes compartments for latent, asymptomatic, detected and undetected symptomatic individuals, and hospitalized cases, and features realistic interval distributions for presymptomatic and symptomatic periods, time varying rates of case detection, diagnosis, and mortality. The model accounts for the effects on transmission of human mobility using anonymized mobility data collected from cellular devices, and of difficult to quantify environmental and behavioral factors using a latent process. The baseline transmission rate is the product of a human mobility metric obtained from data and this fitted latent process. We fit the model to incident case and death reports for each state in the USA and Washington D.C., using likelihood Maximization by Iterated particle Filtering (MIF). Observations (daily case and death reports) are modeled as arising from a negative binomial reporting process. We estimate time-varying transmission rate, parameters of a sigmoidal time-varying fraction of hospitalized cases that result in death, extra-demographic process noise, two dispersion parameters of the observation process, and the initial sizes of the latent, asymptomatic, and symptomatic classes. In a retrospective analysis covering March-December 2020, we show how mobility and transmission strength became decoupled across two distinct phases of the pandemic. The decoupling demonstrates the need for flexible, semi-parametric approaches for modeling infectious disease dynamics in real-time.

Effect of Norovirus Inoculum Dose on Virus Kinetics, Shedding, and Symptoms.

The effect of norovirus dose on outcomes such as virus shedding and symptoms after initial infection is not well understood. We performed a secondary analysis of a human challenge study by using Bayesian mixed-effects models. As the dose increased from 4.8 to 4,800 reverse transcription PCR units, the total amount of shed virus in feces increased from 4.5 × 1011 to 3.4 × 1012 genomic equivalent copies; in vomit, virus increased from 6.4 × 105 to 3.0 × 107 genomic equivalent copies. Onset time of viral shedding in feces decreased from 1.4 to 0.8 days, and time of peak viral shedding decreased from 2.3 to 1.5 days. Time to symptom onset decreased from 1.5 to 0.8 days. One type of symptom score increased. An increase in norovirus dose was associated with more rapid shedding and symptom onset and possibly increased severity. However, the effect on virus load and shedding was inconclusive.

Dominant protection from HLA-linked autoimmunity by antigen-specific regulatory T cells.

Susceptibility and protection against human autoimmune diseases, including type I diabetes, multiple sclerosis, and Goodpasture disease, is associated with particular human leukocyte antigen (HLA) alleles. However, the mechanisms underpinning such HLA-mediated effects on self-tolerance remain unclear. Here we investigate the molecular mechanism of Goodpasture disease, an HLA-linked autoimmune renal disorder characterized by an immunodominant CD4+ T-cell self-epitope derived from the α3 chain of type IV collagen (α3135-145). While HLA-DR15 confers a markedly increased disease risk, the protective HLA-DR1 allele is dominantly protective in trans with HLA-DR15 (ref. 2). We show that autoreactive α3135-145-specific T cells expand in patients with Goodpasture disease and, in α3135-145-immunized HLA-DR15 transgenic mice, α3135-145-specific T cells infiltrate the kidney and mice develop Goodpasture disease. HLA-DR15 and HLA-DR1 exhibit distinct peptide repertoires and binding preferences and present the α3135-145 epitope in different binding registers. HLA-DR15-α3135-145 tetramer+ T cells in HLA-DR15 transgenic mice exhibit a conventional T-cell phenotype (Tconv) that secretes pro-inflammatory cytokines. In contrast, HLA-DR1-α3135-145 tetramer+ T cells in HLA-DR1 and HLA-DR15/DR1 transgenic mice are predominantly CD4+Foxp3+ regulatory T cells (Treg cells) expressing tolerogenic cytokines. HLA-DR1-induced Treg cells confer resistance to disease in HLA-DR15/DR1 transgenic mice. HLA-DR15+ and HLA-DR1+ healthy human donors display altered α3135-145-specific T-cell antigen receptor usage, HLA-DR15-α3135-145 tetramer+ Foxp3- Tconv and HLA-DR1-α3135-145 tetramer+ Foxp3+CD25hiCD127lo Treg dominant phenotypes. Moreover, patients with Goodpasture disease display a clonally expanded α3135-145-specific CD4+ T-cell repertoire. Accordingly, we provide a mechanistic basis for the dominantly protective effect of HLA in autoimmune disease, whereby HLA polymorphism shapes the relative abundance of self-epitope specific Treg cells that leads to protection or causation of autoimmunity.

Five approaches to the suppression of SARS-CoV-2 without intensive social distancing.

Initial efforts to mitigate transmission of SARS-CoV-2 relied on intensive social distancing measures such as school and workplace closures, shelter-in-place orders and prohibitions on the gathering of people. Other non-pharmaceutical interventions for suppressing transmission include active case finding, contact tracing, quarantine, immunity or health certification, and a wide range of personal protective measures. Here we investigate the potential effectiveness of these alternative approaches to suppression. We introduce a conceptual framework represented by two mathematical models that differ in strategy. We find both strategies may be effective, although both require extensive testing and work within a relatively narrow range of conditions. Generalized protective measures such as wearing face masks, improved hygiene and local reductions in density are found to significantly increase the effectiveness of targeted interventions.

Heterogeneity and longevity of antibody memory to viruses and vaccines.

Determining the duration of protective immunity requires quantifying the magnitude and rate of loss of antibodies to different virus and vaccine antigens. A key complication is heterogeneity in both the magnitude and decay rate of responses of different individuals to a given vaccine, as well as of a given individual to different vaccines. We analyzed longitudinal data on antibody titers in 45 individuals to characterize the extent of this heterogeneity and used models to determine how it affected the longevity of protective immunity to measles, rubella, vaccinia, tetanus, and diphtheria. Our analysis showed that the magnitude of responses in different individuals varied between 12- and 200-fold (95% coverage) depending on the antigen. Heterogeneity in the magnitude and decay rate contribute comparably to variation in the longevity of protective immunity between different individuals. We found that some individuals have, on average, slightly longer-lasting memory than others-on average, they have higher antibody levels with slower decay rates. We identified different patterns for the loss of protective levels of antibodies to different vaccine and virus antigens. Specifically, we found that for the first 25 to 50 years, virtually all individuals have protective antibody titers against diphtheria and tetanus, respectively, but about 10% of the population subsequently lose protective immunity per decade. In contrast, at the outset, not all individuals had protective titers against measles, rubella, and vaccinia. However, these antibody titers wane much more slowly, with a loss of protective immunity in only 1% to 3% of the population per decade. Our results highlight the importance of long-term longitudinal studies for estimating the duration of protective immunity and suggest both how vaccines might be improved and how boosting schedules might be reevaluated.

Community drivers of tuberculosis diagnostic delay in Kampala, Uganda: a retrospective cohort study.

BACKGROUND: Recent approaches to TB control have focused on identifying and treating active cases to halt further transmission. Patients with TB symptoms often delay to seek care, get appropriate diagnosis, and initiate effective treatment. These delays are partly influenced by whom the patients contact within their community network. We aimed to evaluate the community drivers of diagnostic delay in an urban setting in Uganda. METHODS: In this study we analyze data from a retrospective cohort of 194 TB patients in Kampala, Uganda. We characterized the patterns of contacts made by patients seeking care for TB symptoms. The main outcome of interest was total community contact delay, defined as the time patients spent seeking care before visiting a provider capable of diagnosing TB. RESULTS: Visits to health providers without access to appropriate diagnostic services accounted for 56% of contacts made by cohort members, and were significantly associated with community contact delay, as were symptoms common to other prevalent illnesses, such as bone and joint pain. CONCLUSIONS: Education programs aimed at primary care providers, as well as other community members, may benefit case identification, by informing them of rarer symptoms of TB, potential for co-infections of TB and other prevalent diseases, and the availability of diagnostic services.

Characterizing Norovirus Transmission from Outbreak Data, United States.

Norovirus is the leading cause of acute gastroenteritis outbreaks in the United States. We estimated the basic (R0) and effective (Re) reproduction numbers for 7,094 norovirus outbreaks reported to the National Outbreak Reporting System (NORS) during 2009-2017 and used regression models to assess whether transmission varied by outbreak setting. The median R0 was 2.75 (interquartile range [IQR] 2.38-3.65), and median Re was 1.29 (IQR 1.12-1.74). Long-term care and assisted living facilities had an R0 of 3.35 (95% CI 3.26-3.45), but R0 did not differ substantially for outbreaks in other settings, except for outbreaks in schools, colleges, and universities, which had an R0 of 2.92 (95% CI 2.82-3.03). Seasonally, R0 was lowest (3.11 [95% CI 2.97-3.25]) in summer and peaked in fall and winter. Overall, we saw little variability in transmission across different outbreaks settings in the United States.

A software package for immunologists to learn simulation modeling.

BACKGROUND: As immunology continues to become more quantitative, increasingly sophisticated computational tools are commonly used. One useful toolset are simulation models. Becoming familiar with such models and their uses generally requires writing computer code early in the learning process. This poses a barrier for individuals who do not have prior coding experience. RESULTS: To help reduce this barrier, I wrote software that teaches the use of mechanistic simulation models to study infection and immune response dynamics, without the need to read or write computer code. The software, called Dynamical Systems Approach to Immune Response Modeling (DSAIRM), is implemented as a freely available package for the R programming language. The target audience are immunologists and other scientists with no or little coding experience. DSAIRM provides a hands-on introduction to simulation models, teaches the basics of those models and what they can be used for. Here, I describe the DSAIRM R package, explain the different ways the package can be used, and provide a few introductory examples. CONCLUSIONS: Working through DSAIRM will equip individuals with the knowledge needed to critically assess studies using simulation models in the published literature and will help them understand when such a modeling approach might be suitable for their own research. DSAIRM also provides users a potential starting point towards development and use of simulation models in their own research.

Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of influenza patients.

Communicable diseases are often virulent, i.e. they cause morbidity symptoms in those infected. While some symptoms may be transmission-enhancing, other symptoms are likely to reduce transmission potential. For human diseases, the reduction in transmission opportunities is commonly caused by reduced activity. There is limited data regarding the potential impact of virulence on transmission potential. We performed an exploratory data analysis of 324 influenza patients at a university health centre during the 2016/2017 influenza season. We classified symptoms as infectiousness-related or morbidity-related and calculated two scores. The scores were used to explore the relationship between infectiousness, morbidity (virulence), and activity level. We found a decrease in the activity level with increasing morbidity scores. There was no consistent pattern between an activity level and an infectiousness score. We also found a positive correlation between morbidity and infectiousness scores. Overall, we find that increasing virulence leads to increased infectiousness and reduced activity, suggesting a trade-off that can impact overall transmission potential. Our findings indicate that a reduction of systemic symptoms may increase host activity without reducing infectiousness. Therefore, interventions should target both systemic- and infectiousness-related symptoms to reduce overall transmission potential. Our findings can also inform simulation models that investigate the impact of different interventions on transmission.

Varying Inoculum Dose to Assess the Roles of the Immune Response and Target Cell Depletion by the Pathogen in Control of Acute Viral Infections.

It is difficult to determine whether an immune response or target cell depletion by the infectious agent is most responsible for the control of acute primary infection. Both mechanisms can explain the basic dynamics of an acute infection-exponential growth of the pathogen followed by control and clearance-and can also be represented by many different differential equation models. Consequently, traditional model comparison techniques using time series data can be ambiguous or inconclusive. We propose that varying the inoculum dose and measuring the subsequent infectious load can rule out target cell depletion by the pathogen as the main control mechanism. Infectious load can be any measure that is proportional to the number of infected cells, such as viraemia. We show that a twofold or greater change in infectious load is unlikely when target cell depletion controls infection, regardless of the model details. Analyzing previously published data from mice infected with influenza, we find the proportion of lung epithelial cells infected was 21-fold greater (95% confidence interval 14-32) in the highest dose group than in the lowest. This provides evidence in favor of an alternative to target cell depletion, such as innate immunity, in controlling influenza infections in this experimental system. Data from other experimental animal models of acute primary infection have a similar pattern.

A Risk Classification Model to Predict Mortality Among Laboratory-Confirmed Avian Influenza A H7N9 Patients: A Population-Based Observational Cohort Study.

BACKGROUND: Avian influenza A H7N9 (A/H7N9) is characterized by rapid progressive pneumonia and respiratory failure. Mortality among laboratory-confirmed cases is above 30%; however, the clinical course of disease is variable and patients at high risk for death are not well characterized. METHODS: We obtained demographic, clinical, and laboratory information on all A/H7N9 patients in Zhejiang province from China Centers for Disease Control and Prevention electronic databases. Risk factors for death were identified using logistic regression and a risk score was created using regression coefficients from multivariable models. We externally validated this score in an independent cohort from Jiangsu province. RESULTS: Among 305 A/H7N9 patients, 115 (37.7%) died. Four independent predictors of death were identified: older age, diabetes, bilateral lung infection, and neutrophil percentage. We constructed a score with 0-13 points. Mortality rates in low- (0-3), medium- (4-6), and high-risk (7-13) groups were 4.6%, 32.1%, and 62.7% (Ptrend < .0001). In a validation cohort of 111 A/H7N9 patients, 61 (55%) died. Mortality rates in low-, medium-, and high-risk groups were 35.5%, 55.8, and 67.4% (Ptrend = .0063). CONCLUSIONS: We developed and validated a simple-to-use, predictive risk score for clinical use, identifying patients at high mortality risk.

Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design.

Vaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose. We illustrate the concept of using data and models to inform inoculum dose determination for vaccines, wby fitting a mathematical model to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) infection of cotton rats at different inoculum doses. We use the model to map inoculum dose to the level of immune protection and morbidity and to explore how such a framework might be used to determine an optimal inoculum dose. We show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. Our findings illustrate that the impact of inoculum dose on immune protection and morbidity can depend on the specific pathogen and that both protection and morbidity do not necessarily increase monotonically with increasing inoculum dose. Once vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework can help in the rational design of vaccines and determination of the optimal amount of inoculum.

Heightened self-reactivity associated with selective survival, but not expansion, of naïve virus-specific CD8+ T cells in aged mice.

In advanced age, decreased CD8(+) cytotoxic T-lymphocyte (CTL) responses to novel pathogens and cancer is paralleled by a decline in the number and function of naïve CTL precursors (CTLp). Although the age-related fall in CD8(+) T-cell numbers is well established, neither the underlying mechanisms nor the extent of variation for different epitope specificities have been defined. Furthermore, naïve CD8(+) T cells expressing high levels of CD44 accumulate with age, but it is unknown whether this accumulation reflects their preferential survival or an age-dependent driver of CD8(+) T-cell proliferation. Here, we track the number and phenotype of four influenza A virus (IAV)-specific CTLp populations in naïve C57BL/6 (B6) mice during aging, and compare T-cell receptor (TCR) clonal diversity for the CD44hi and CD44lo subsets of one such population. We show differential onset of decline for several IAV-specific CD8(+) T-cell populations with advanced age that parallel age-associated changes in the B6 immunodominance hierarchy, suggestive of distinct impacts of aging on different epitope-specific populations. Despite finding no evidence of clonal expansions in an aged, epitope-specific TCR repertoire, nonrandom alterations in TCR usage were observed, along with elevated CD5 and CD8 coreceptor expression. Collectively, these data demonstrate that naïve CD8(+) T cells expressing markers of heightened self-recognition are selectively retained, but not clonally expanded, during aging.

Reproducible selection of high avidity CD8+ T-cell clones following secondary acute virus infection.

The recall of memory CD8(+) cytotoxic T lymphocytes (CTLs), elicited by prior virus infection or vaccination, is critical for immune protection. The extent to which this arises as a consequence of stochastic clonal expansion vs. active selection of particular clones remains unclear. Using a parallel adoptive transfer protocol in combination with single cell analysis to define the complementarity determining region (CDR) 3α and CDR3ß regions of individual T-cell receptor (TCR) heterodimers, we characterized the antigen-driven recall of the same memory CTL population in three individual recipients. This high-resolution analysis showed reproducible enrichment (or diminution) of particular TCR clonotypes across all challenged animals. These changes in clonal composition were TCRα- and ß chain-dependent and were directly related to the avidity of the TCR for the virus-derived peptide (p) + major histocompatibility complex class I molecule. Despite this shift in clonotype representation indicative of differential selection, there was no evidence of overall repertoire narrowing, suggesting a strategy to optimize CTL responses while safeguarding TCR diversity.

Recognition of distinct cross-reactive virus-specific CD8+ T cells reveals a unique TCR signature in a clinical setting.

Human CMV still remains problematic in immunocompromised patients, particularly after solid organ transplantation. CMV primary disease and reactivation greatly increase the risks associated with incidences of chronic allograft rejection and decreased survival in transplant recipients. But whether this is due to direct viral effects, indirect viral effects including cross-reactive antiviral T cell immunopathology, or a combination of both remains undetermined. In this article, we report the novel TCR signature of cross-reactive HLA-A*02:01 (A2) CMV (NLVPMVATV [NLV])-specific CD8(+) T cells recognizing a specific array of HLA-B27 alleles using technical advancements that combine both IFN-γ secretion and multiplex nested RT-PCR for determining paired CDR3α/ß sequences from a single cell. This study represents the first evidence, to our knowledge, of the same A2-restricted cross-reactive NLV-specific TCR-α/ß signature (TRAV3TRAJ31_TRBV12-4TRBJ1-1) in two genetically distinct individuals. Longitudinal posttransplant monitoring of a lung transplant recipient (A2, CMV seropositive) who received a HLA-B27 bilateral lung allograft showed a dynamic expansion of the cross-reactive NLV-specific TCR repertoire before CMV reactivation. After resolution of the active viral infection, the frequency of cross-reactive NLV-specific CD8(+) T cells reduced to previremia levels, thereby demonstrating immune modulation of the T cell repertoire due to antigenic pressure. The dynamic changes in TCR repertoire, at a time when CMV reactivation was subclinical, illustrates that prospective monitoring in susceptible patients can reveal nuances in immune profiles that may be clinically relevant.

Ecological analysis of antigen-specific CTL repertoires defines the relationship between naive and immune T-cell populations.

Ecology is typically thought of as the study of interactions organisms have with each other and their environment and is focused on the distribution and abundance of organisms both within and between environments. On a molecular level, the capacity to probe analogous questions in the field of T-cell immunology is imperative as we acquire substantial datasets both on epitope-specific T-cell populations through high-resolution analyses of T-cell receptor (TCR) use and on global T-cell populations analyzed via high-throughput DNA sequencing. Here, we present the innovative application of existing statistical measures (used typically in the field of ecology), together with unique statistical analyses, to comprehensively assess how the naïve epitope-specific CD8(+) cytotoxic T lymphocyte (CTL) repertoire translates to that found following an influenza-virus-specific immune response. Such interrogation of our extensive, cumulated TCR CDR3ß sequence datasets, derived from both naïve and immune CD8(+) T-cell populations specific for four different influenza-derived epitopes (D(b)NP(366), influenza nucleoprotein amino acid residues 366-374; D(b)PA(224), influenza acid polymerase amino acid residues 224-233; D(b)PB1-F2(62), influenza polymerase B 1 reading frame 2 amino acid residues 62-70; K(b)NS2(114), and influenza nonstructural protein 2 amino acid residues 114-121), demonstrates that epitope-specific TCR use in an antiviral immune response is the consequence of a complex interplay between the intrinsic characteristics of the naïve cytotoxic T lymphocyte precursor pool and extrinsic (likely antigen driven) influences, the contribution of which varies in an epitope-specific fashion.

Four Degrees of Separation: Social Contacts and Health Providers Influence the Steps to Final Diagnosis of Active Tuberculosis Patients in Urban Uganda.

BACKGROUND: Delay in tuberculosis (TB) diagnosis adversely affects patients' outcomes and prolongs transmission in the community. The influence of social contacts on steps taken by active pulmonary TB patients to seek a diagnosis has not been well examined. METHODS: A retrospective study design was use to enroll TB patients on treatment for 3 months or less and aged ≥18 years from 3 public clinics in Kampala, Uganda, from March to July 2014. Social network analysis was used to collect information about social contacts and health providers visited by patients to measure the number of steps and time between onset of symptoms and final diagnosis of TB. RESULTS: Of 294 TB patients, 58 % were male and median age was 30 (IQR: 24-38) years. The median number of steps was 4 (IQR: 3, 7) corresponding to 70 (IQR: 28,140) days to diagnosis. New patients had more steps and time to diagnosis compared retreatment patients (5 vs. 3, P < 0.0001; 84 vs. 46 days P < 0.0001). Fifty-eight percent of patients first contacted persons in their social network. The first step to initiate seeking care accounted for 41 % of the patients' time to diagnosis while visits to non-TB providers and TB providers (without a TB diagnosis) accounted for 34 % and 11 % respectively. New TB patients vs. retreatment (HR: 0.66, 95 % CI; 1.11, 1.99), those who first contacted a non-TB health provider vs. contacting social network (HR: 0.72 95 % CI; 0.55, 0.95) and HIV seronegative vs. seropositive patients (HR: 0.70, 95 % CI; 0.53, 0.92) had a significantly lower likelihood of a timely final diagnosis. CONCLUSIONS: There were four degrees of separation between the onset of symptoms in a TB patient and a final diagnosis. Both social and provider networks of patients influenced the diagnostic pathways. Most delays occurred in the first step which represents decisions to seek help, and through interactions with non-TB health providers. TB control programs should strengthen education and active screening in the community and in health care settings to ensure timely diagnosis of TB.

Trade-offs between and within scales: environmental persistence and within-host fitness of avian influenza viruses.

Trade-offs between different components of a pathogen's replication and transmission cycle are thought to be common. A number of studies have identified trade-offs that emerge across scales, reflecting the tension between strategies that optimize within-host proliferation and large-scale population spread. Most of these studies are theoretical in nature, with direct experimental tests of such cross-scale trade-offs still rare. Here, we report an analysis of avian influenza A viruses across scales, focusing on the phenotype of temperature-dependent viral persistence. Taking advantage of a unique dataset that reports both environmental virus decay rates and strain-specific viral kinetics from duck challenge experiments, we show that the temperature-dependent environmental decay rate of a strain does not impact within-host virus load. Hence, for this phenotype, the scales of within-host infection dynamics and between-host environmental persistence do not seem to interact: viral fitness may be optimized on each scale without cross-scale trade-offs. Instead, we confirm the existence of a temperature-dependent persistence trade-off on a single scale, with some strains favouring environmental persistence in water at low temperatures while others reduce sensitivity to increasing temperatures. We show that this temperature-dependent trade-off is a robust phenomenon and does not depend on the details of data analysis. Our findings suggest that viruses might employ different environmental persistence strategies, which facilitates the coexistence of diverse strains in ecological niches. We conclude that a better understanding of the transmission and evolutionary dynamics of influenza A viruses probably requires empirical information regarding both within-host dynamics and environmental traits, integrated within a combined ecological and within-host framework.