A speed limit on serial strain replacement from original antigenic sin.

Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if [Formula: see text] is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.

Preliminary findings from the Dynamics of the Immune Responses to Repeat Influenza Vaccination Exposures (DRIVE I) Study: a Randomized Controlled Trial.

Background: Studies have reported that repeated annual vaccination may influence the effectiveness of the influenza vaccination in the current season. The mechanisms underlying these differences are unclear but might include "focusing" of the adaptive immune response to older strains. Methods: We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. Participants were randomized equally between five groups, with planned annual receipt of vaccination (V) or saline placebo (P) as follows: P-P-P-P-V, P-P-P-V-V, P-P-V-V-V, P-V-V-V-V, or V-V-V-VV. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera were tested by hemagglutination inhibition assays, focus reduction neutralization tests and enzyme-linked immunosorbent assays against vaccine strains. Results: From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. We selected sera from 95 participants at five timepoints from the first two study years for testing. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with substantial increases for first-time vaccinees and smaller increases for repeat vaccinees, who had higher pre-vaccination titers in year 2. There were statistically significant reductions in the proportion of participants achieving a four-fold greater rise in antibody titer for the repeat vaccinees for A(H1N1), B/Victoria and B/Yamagata, but not for influenza A(H3N2). There were no statistically significant differences between groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. Conclusions: In the first two years, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection. The vaccine strains of A(H1N1) and A(H3N2) were updated in year 2, providing an opportunity to explore antigenic distances between those strains in humans in subsequent years.

Reduced effectiveness of repeat influenza vaccination: distinguishing among within-season waning, recent clinical infection, and subclinical infection.

Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influenced individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.

High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains.

The high genetic diversity of influenza viruses means that traditional serological assays have too low throughput to measure serum antibody neutralization titers against all relevant strains. To overcome this challenge, we have developed a sequencing-based neutralization assay that simultaneously measures titers against many viral strains using small serum volumes via a workflow similar to traditional neutralization assays. The key innovation is to incorporate unique nucleotide barcodes into the hemagglutinin (HA) genomic segment, and then pool viruses with numerous different barcoded HA variants and quantify infectivity of all of them simultaneously using next-generation sequencing. With this approach, a single researcher performed the equivalent of 2,880 traditional neutralization assays (80 serum samples against 36 viral strains) in approximately one month. We applied the sequencing-based assay to quantify the impact of influenza vaccination on neutralization titers against recent human H1N1 strains for individuals who had or had not also received a vaccine in the previous year. We found that the viral strain specificities of the neutralizing antibodies elicited by vaccination vary among individuals, and that vaccination induced a smaller increase in titers for individuals who had also received a vaccine the previous year-although the titers six months after vaccination were similar in individuals with and without the previous-year vaccination. We also identified a subset of individuals with low titers to a subclade of recent H1N1 even after vaccination. This study demonstrates the utility of high-throughput sequencing-based neutralization assays that enable titers to be simultaneously measured against many different viral strains. We provide a detailed experimental protocol (DOI: https://dx.doi.org/10.17504/protocols.io.kqdg3xdmpg25/v1) and a computational pipeline (https://github.com/jbloomlab/seqneut-pipeline) for the sequencing-based neutralization assays to facilitate the use of this method by others.

A speed limit on serial strain replacement from original antigenic sin.

Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive new constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if R0 is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.

Measures of population immunity can predict the dominant clade of influenza A (H3N2) and reveal age-associated differences in susceptibility and specificity.

For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared to others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectional antibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season. We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains. The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titers to different HA and NA clades varied dramatically between individuals but showed significant associations with age, suggesting dependence on correlated past exposures. Despite this correlation, inter-individual variability in antibody titers to H3N2 strains increased gradually with age. This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.

Germline-encoded specificities and the predictability of the B cell response.

Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles' propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination.

Antigen-driven colonic inflammation is associated with development of dysplasia in primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is an immune-mediated disease of the bile ducts that co-occurs with inflammatory bowel disease (IBD) in almost 90% of cases. Colorectal cancer is a major complication of patients with PSC and IBD, and these patients are at a much greater risk compared to patients with IBD without concomitant PSC. Combining flow cytometry, bulk and single-cell transcriptomics, and T and B cell receptor repertoire analysis of right colon tissue from 65 patients with PSC, 108 patients with IBD and 48 healthy individuals we identified a unique adaptive inflammatory transcriptional signature associated with greater risk and shorter time to dysplasia in patients with PSC. This inflammatory signature is characterized by antigen-driven interleukin-17A (IL-17A)+ forkhead box P3 (FOXP3)+ CD4 T cells that express a pathogenic IL-17 signature, as well as an expansion of IgG-secreting plasma cells. These results suggest that the mechanisms that drive the emergence of dysplasia in PSC and IBD are distinct and provide molecular insights that could guide prevention of colorectal cancer in individuals with PSC.

Reduced effectiveness of repeat influenza vaccination: distinguishing among within-season waning, recent clinical infection, and subclinical infection.

Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influences individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.

Investigation of the Impact of Childhood Immune Imprinting on Birth Year-Specific Risk of Clinical Infection During Influenza A Virus Epidemics in Hong Kong.

Influenza imprinting reduces risks of influenza A virus clinical infection by 40%-90%, estimated from surveillance data in western countries. We analyzed surveillance data from 2010 to 2019 in Hong Kong. Based on the best model, which included hemagglutinin group-level imprinting, we estimated that individuals imprinted to H1N1 or H2N2 had a 17% (95% confidence interval [CI], 3%-28%) lower risk of H1N1 clinical infection, and individuals imprinted to H3N2 would have 12% (95% CI, -3% to 26%) lower risk of H3N2 clinical infection. These estimated imprinting protections were weaker than estimates in western countries. Identifying factors affecting imprinting protections is important for control policies and disease modeling.

COVID-19 and children.

There has been substantial research on adult COVID-19 and how to treat it. But how do severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections afflict children? The COVID-19 pandemic has yielded many surprises, not least that children generally develop less severe disease than older adults, which is unusual for a respiratory disease. However, some children can develop serious complications from COVID-19, such as multisystem inflammatory syndrome in children (MIS-C) and Long Covid, even after mild or asymptomatic COVID-19. Why this occurs in some and not others is an important question. Moreover, when children do contract COVID-19, understanding their role in transmission, especially in schools and at home, is crucial to ensuring effective mitigation measures. Therefore, in addition to nonpharmaceutical interventions, such as improved ventilation, there is a strong case to vaccinate children so as to reduce possible long-term effects from infection and to decrease transmission. But questions remain about whether vaccination might skew immune responses to variants in the long term. As the experts discuss below, more is being learned about these important issues, but much more research is needed to understand the long-term effects of COVID-19 in children.

Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA.

Public health indicators typically used for COVID-19 surveillance can be biased or lag changing community transmission patterns. In this study, we investigate whether sentinel surveillance of recently symptomatic individuals receiving outpatient diagnostic testing for SARS-CoV-2 could accurately assess the instantaneous reproductive number R(t) and provide early warning of changes in transmission. We use data from community-based diagnostic testing sites in the United States city of Chicago. Patients tested at community-based diagnostic testing sites between September 2020 and June 2021, and reporting symptom onset within four days preceding their test, formed the sentinel population. R(t) calculated from sentinel cases agreed well with R(t) from other indicators. Retrospectively, trends in sentinel cases did not precede trends in COVID-19 hospital admissions by any identifiable lead time. In deployment, sentinel surveillance held an operational recency advantage of nine days over hospital admissions. The promising performance of opportunistic sentinel surveillance suggests that deliberately designed outpatient sentinel surveillance would provide robust early warning of increasing transmission.

SARS-CoV-2 Infection Among Pregnant People at Labor and Delivery and Changes in Infection Rates in the General Population: Lessons Learned From Illinois.

OBJECTIVES: The Illinois Department of Public Health (IDPH) assessed whether increases in the SARS-CoV-2 test positivity rate among pregnant people at labor and delivery (L&D) could signal increases in SARS-CoV-2 prevalence in the general Illinois population earlier than current state metrics. MATERIALS AND METHODS: Twenty-six birthing hospitals universally testing for SARS-CoV-2 at L&D voluntarily submitted data from June 21, 2020 through January 23, 2021, to IDPH. Hospitals reported the daily number of people who delivered, SARS-CoV-2 tests, and test results as well as symptom status. We compared the test positivity rate at L&D with the test positivity rate of the general population and the number of hospital admissions for COVID-19-like illness by quantifying correlations in trends and identifying a lead time. RESULTS: Of 26 633 reported pregnant people who delivered, 96.8% (n = 25 772) were tested for SARS-CoV-2. The overall test positivity rate was 2.4% (n = 615); 77.7% (n = 478) were asymptomatic. In Chicago, the only region with a sufficient sample size for analysis, the test positivity rate at L&D (peak of 5% on December 7, 2020) was lower and more stable than the test positivity rate of the general population (peak of 14% on November 13, 2020) and lagged hospital admissions for COVID-19-like illness (peak of 118 on November 15, 2020) and the test positivity rate of the general population by about 10 days (Pearson correlation = 0.73 and 0.75, respectively). PRACTICE IMPLICATIONS: Trends in the test positivity rate at L&D did not provide an earlier signal of increases in Illinois's SARS-CoV-2 prevalence than current state metrics did. Nonetheless, the role of universal testing protocols in identifying asymptomatic infection is important for clinical decision making and patient education about infection prevention and control.

PARIS and SPARTA: Finding the Achilles' Heel of SARS-CoV-2.

To understand reinfection rates and correlates of protection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we established eight different longitudinal cohorts in 2020 under the umbrella of the PARIS (Protection Associated with Rapid Immunity to SARS-CoV-2)/SPARTA (SARS SeroPrevalence And Respiratory Tract Assessment) studies. Here, we describe the PARIS/SPARTA cohorts, the harmonized assays and analysis that are performed across the cohorts, as well as case definitions for SARS-CoV-2 infection and reinfection that have been established by the team of PARIS/SPARTA investigators. IMPORTANCE Determining reinfection rates and correlates of protection against SARS-CoV-2 infection induced by both natural infection and vaccination is of high significance for the prevention and control of coronavirus disease 2019 (COVID-19). Furthermore, understanding reinfections or infection after vaccination and the role immune escape plays in these scenarios will inform the need for updates of the current SARS-CoV-2 vaccines and help update guidelines suitable for the postpandemic world.

Incorporating temporal distribution of population-level viral load enables real-time estimation of COVID-19 transmission.

Many locations around the world have used real-time estimates of the time-varying effective reproductive number ([Formula: see text]) of COVID-19 to provide evidence of transmission intensity to inform control strategies. Estimates of [Formula: see text] are typically based on statistical models applied to case counts and typically suffer lags of more than a week because of the latent period and reporting delays. Noting that viral loads tend to decline over time since illness onset, analysis of the distribution of viral loads among confirmed cases can provide insights into epidemic trajectory. Here, we analyzed viral load data on confirmed cases during two local epidemics in Hong Kong, identifying a strong correlation between temporal changes in the distribution of viral loads (measured by RT-qPCR cycle threshold values) and estimates of [Formula: see text] based on case counts. We demonstrate that cycle threshold values could be used to improve real-time [Formula: see text] estimation, enabling more timely tracking of epidemic dynamics.

Modeling comparative cost-effectiveness of SARS-CoV-2 vaccine dose fractionation in India.

Given global Coronavirus Disease 2019 (COVID-19) vaccine shortages and inequity of vaccine distributions, fractionation of vaccine doses might be an effective strategy for reducing public health and economic burden, notwithstanding the emergence of new variants of concern. In this study, we developed a multi-scale model incorporating population-level transmission and individual-level vaccination to estimate the costs of hospitalization and vaccination and the economic benefits of reducing COVID-19 deaths due to dose-fractionation strategies in India. We used large-scale survey data of the willingness to pay together with data of vaccine and hospital admission costs to build the model. We found that fractional doses of vaccines could be an economically viable vaccination strategy compared to alternatives of either full-dose vaccination or no vaccination. Dose-sparing strategies could save a large number of lives, even with the emergence of new variants with higher transmissibility.

The Potential Beneficial Effects of Vaccination on Antigenically Evolving Pathogens.

AbstractAlthough vaccines against antigenically evolving pathogens such as seasonal influenza ; and are designed to protect against circulating strains by affecting the emergence and transmission of antigenically divergent strains, they might in theory also be able to change the rate of antigenic evolution. Vaccination might slow antigenic evolution by increasing immunity, reducing the overall prevalence or population size of the pathogen. This reduction could decrease the supply and growth rates of mutants and might thereby slow adaptation. But vaccination might accelerate antigenic evolution by increasing the transmission advantage of more antigenically diverged strains relative to less diverged strains (i.e., by positive selection). Such evolutionary effects could affect vaccination's direct benefits to individuals and indirect benefits to the host population (i.e., the private and social benefits). To investigate these potential impacts, we simulated vaccination against a continuously circulating influenza-like pathogen in a simple population. On average, more vaccination decreased the incidence of infection. Notably, this decrease was driven partly by a vaccine-induced decline in the rate of antigenic evolution. To understand how the evolutionary effects of vaccines might affect their social and private benefits, we fitted linear panel models to simulated data. By slowing evolution, vaccination increased the social benefit and decreased the private benefit. Thus, vaccination's potential social and private benefits may differ from current theory, which omits evolutionary effects. These results suggest that conventional vaccines against influenza and other antigenically evolving pathogens, if protective against transmission and given to the appropriate populations, could further reduce disease burden by slowing antigenic evolution.

Improvements in Severe Acute Respiratory Syndrome Coronavirus 2 Testing Cascade in the United States: Data From Serial Cross-sectional Assessments.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing is critical for monitoring case counts, early detection and containment of infection, clinical management, and surveillance of variants. However, community-based data on the access, uptake, and barriers to testing have been lacking. METHODS: We conducted serial cross-sectional online surveys covering demographics, coronavirus disease 2019 symptoms, and experiences around SARS-CoV-2 diagnostic testing to characterize the SARS-CoV-2 testing cascade and associated barriers across 10 US states (California, Florida, Illinois, Maryland, Massachusetts, Nebraska, North Dakota, South Dakota, Texas, and Wisconsin), from July 2020 to February 2021. RESULTS: In February 2021, across 10 US states, 895 respondents (11%) reported wanting a diagnostic test in the prior 2 weeks, 63% of whom were tested, with limited variability across states. Almost all (97%) who were tested received their results; 56% received their results within 2 days. In Maryland, Florida, and Illinois, where serial data were available at 4 time points, 56% were tested the same day they wanted or needed a test in February 2021, compared with 28% in July 2020, and 45% received results the same day, compared with 17% in July 2020. Wanting a test was significantly more common among younger, nonwhite respondents and participants with a history of symptoms or exposure. Logistical challenges, including not knowing where to go, were the most frequently cited barriers. CONCLUSIONS: There were significant improvements in access and turnaround times across US states, yet barriers to testing remained consistent across states, underscoring the importance of a continued focus on testing, even amidst mass vaccination campaigns.

Correction: Practical considerations for measuring the effective reproductive number, Rt.

[This corrects the article DOI: 10.1371/journal.pcbi.1008409.].

Of variants and vaccines.

In this issue of Cell, Bushman et al. show how more transmissible variants, even if they do not escape immunity, can be strongly selected during the early pandemic. This explains the dynamics of past SARS-CoV-2 variants, but as immunity increases, it is difficult to predict what will emerge next.