The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ...ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.
Influenza A viruses evolve rapidly to escape host immunity, causing reinfection. The form and duration of protection after each influenza virus infection are poorly understood. We quantify the ...dynamics of protective immunity by fitting individual-level mechanistic models to longitudinal serology from children and adults. We find that most protection in children but not adults correlates with antibody titers to the hemagglutinin surface protein. Protection against circulating strains wanes to half of peak levels 3.5-7 years after infection in both age groups, and wanes faster against influenza A(H3N2) than A(H1N1)pdm09. Protection against H3N2 lasts longer in adults than in children. Our results suggest that influenza antibody responses shift focus with age from the mutable hemagglutinin head to other epitopes, consistent with the theory of original antigenic sin, and might affect protection. Imprinting, or primary infection with a subtype, has modest to no effect on the risk of non-medically attended infections in adults.
Despite the availability of vaccines, influenza remains a major public health challenge. A key reason is the virus capacity for immune escape: ongoing evolution allows the continual circulation of ...seasonal influenza, while novel influenza viruses invade the human population to cause a pandemic every few decades. Current vaccines have to be updated continually to keep up to date with this antigenic change, but emerging 'universal' vaccines-targeting more conserved components of the influenza virus-offer the potential to act across all influenza A strains and subtypes. Influenza vaccination programmes around the world are steadily increasing in their population coverage. In future, how might intensive, routine immunization with novel vaccines compare against similar mass programmes utilizing conventional vaccines? Specifically, how might novel and conventional vaccines compare, in terms of cumulative incidence and rates of antigenic evolution of seasonal influenza? What are their potential implications for the impact of pandemic emergence? Here we present a new mathematical model, capturing both transmission dynamics and antigenic evolution of influenza in a simple framework, to explore these questions. We find that, even when matched by per-dose efficacy, universal vaccines could dampen population-level transmission over several seasons to a greater extent than conventional vaccines. Moreover, by lowering opportunities for cross-protective immunity in the population, conventional vaccines could allow the increased spread of a novel pandemic strain. Conversely, universal vaccines could mitigate both seasonal and pandemic spread. However, where it is not possible to maintain annual, intensive vaccination coverage, the duration and breadth of immunity raised by universal vaccines are critical determinants of their performance relative to conventional vaccines. In future, conventional and novel vaccines are likely to play complementary roles in vaccination strategies against influenza: in this context, our results suggest important characteristics to monitor during the clinical development of emerging vaccine technologies.
This paper presents the development of a numerical optimization tool for the design of a passive U-tube type anti-roll tank (ART) system to mitigate the roll motions of a vessel. A Genetic Algorithm ...(GA) based optimization scheme has been developed to minimize the objective function, which in the present investigation is chosen to be the area under the roll response transfer function curve. A practical nonlinear time-domain based body-exact strip theory technique is used to solve the fully coupled ART–ship motion problem. In the optimization process, the GA is linked to the fluid solver to approach an optimum ART design. The optimization variables are chosen to be the principal dimensions of the anti-roll tank, which have bearing on the roll reduction characteristics of the vessel. The study is implemented in the case of a coastal research vessel requiring passive stabilization via an ART. The results are validated using laboratory scale models to quantify the tank dynamics and effectiveness in isolation as well as when deployed in the vessel model and subjected to waves. The results demonstrate the validity and efficiency of the entire computational scheme.
•An computational method has been developed to solve the coupled ship-ART problem.•The ART equations of motion have been derived using Lagrangian mechanics.•Scale model experiments have been conducted to validate computational model.•A Genetic Algorithm (GA) based (constrained) optimization routine has been developed.•The GA optimized ART form was found to reduce roll by approximately 12%.
A time-domain body exact strip theory is developed to predict maneuvering of a vessel in a seaway. A frame following the instantaneous position of the ship, by translating and rotating in the ...horizontal plane, is used to set up the boundary value problem (BVP) for the perturbation potentials. A boundary integral technique is used for solving the Laplace equation. Linearized free surface boundary conditions are used for stability and computational efficiency, and exact body boundary conditions are used to capture nonlinear effects. A nonlinear rigid body equation of motion solver is coupled to the hydrodynamic model to predict ship responses. Results are presented for the turning circle maneuver of the containership S-175 in calm water and in the presence of regular waves. The results are compared with available experimental results. The simulations are able to capture general qualitative aspects and overall physics of the problem.
•A time-domain body-exact strip theory is developed to predict maneuvering of a vessel in a seaway.•A translating and rotating frame following the ship, is used to set up the B.V.P for the perturbation potentials.•A blended method scheme is used to capture nonlinear aspects and maintain computational efficiency.•A fully nonlinear rigid body equation of motion solver is coupled to the hydrodynamic model to predict ship responses.•Turning circle maneuvers of containership S-175 have been simulated in calm water and waves.
Emerging viruses such as COVID-19 and dengue pose substantial public health risks in large cities, but their impact on host populations can be quite heterogeneous and hard to quantify using ...traditional mathematical models. I quantify the extent and impact of heterogeneity in infection status and in underlying transmission for both diseases. In my first chapter, I use a model that incorporates daily changes in testing capacity to precisely quantify the proportion of COVID-19 cases in New York City that were symptomatic during the initial epidemic wave. In my second chapter, I demonstrate that susceptible depletion on a city-wide aggregate level cannot explain the rapid re-emergence of dengue serotype DENV1 in the 1980s in Rio de Janeiro, Brazil, and suggest that inter-annual variation in climate, spatial heterogeneity within a large city, and coupling between cities may play an important role in dengue dynamics. In my third chapter, I use a panel of mechanistic models driven by cases from Rio to show that connectivity to the city of Rio played a crucial role in the spread of DENV4 through the Rio metropolitan area in 2012–2013, and that secondary movement hubs in the suburbs east of Rio could also be very important in facilitating the virus’ spread to more outlying areas. These essential fluxes could be incorporated into statistical models that can already capture inter-annual variation in climate and socio-economic variables or integrated with smaller-scale mechanistic models to provide a multi-scale understanding of dengue transmission and re-emergence.
Abstract
Background
While some immune-deficient persons (IDP) face higher risk for severe SARS-CoV-2 infection than the general population, little is known about their immune response to ...post-vaccination infections.
Methods
A cohort of 217 IDP and 54 healthy volunteers (HV) were followed from April 2021 to April 2023. Blood was collected at baseline, 1-, and 6-months post vaccination. Anti-spike IgG response was assessed by ELISA and the T cell receptor repertoire was sequenced. SARS-CoV-2 infection was actively monitored for 6 months post-vaccination; participants could self-report at any point.
Results
Thirty-six percent of IDP and 46% of healthy volunteers experienced a post-vaccination SARS-CoV-2 infection (p=0.21). Infections occurred from September 3, 2021 to March 25, 2023 and were primarily of the Omicron lineage. Clinical symptoms and severity did not significantly differ between groups, nor did the time from last vaccination to infection (IDP: 140 days, HV: 161 days, p=0.28). While ∼50% of both groups received ≥3 doses, IDP received more doses pre-infection than HV. Indeed, 30 IDP receiving ≥3 monovalent doses and 6 IDP receiving ≥4 monovalent doses were infected (Figure 1). Of the 84 (39%) IDP and 19 (35%) HV who received a bivalent booster, 9 (11%) IDP and 2 (11%) HV later experienced an infection (p=1). Among the 50 IDP who received Evusheld, 9 (18%) experienced an infection after its receipt. Infection increased anti-spike IgG relative to infection-naïve participants 6 months post-dose 2 through post-dose 4 in IDP and 6 months post-doses 2 and 3 in in HV; at later timepoints, IgG levels were the same (Figure 2). The diversity of the T cell repertoire was similar across the cohort; the magnitude of response was lower in IDP and had more variation by disorder.Figure 1.Swimmer plot of breakthrough infections relative to SARS-CoV-2 waves in the US.
The dates of dose 2 (open circle), dose 3 (open square), dose 4 (open diamond), dose 5 (crossed box), and 1st breakthrough infection (triangle) are shown for all 80 infected participants. Upright triangles represent IDP participants (n=60), and upside-down triangles represent HV participants (n=20). The color of the triangle corresponds to the known causative SARS-CoV-2 variant; infections for which the causative variant is unknown are shown in black. The background colors show the national SARS-CoV-2 variant sampling percentages from the CDC. The dotted line indicates the start of the study period, April 29, 2021.Figure 2.Spike IgG titers by SARS-CoV-2 status at sample
Immune Deficient Persons (IDP) who were SARS-CoV-2 positive had significantly higher titers at multiple timepoints, while Healthy Volunteers (HV) only showed different titers by SARS-CoV-2 status at 6 months post-doses 2 and 3.
Conclusion
Despite reporting high preventative behavior to avoid SARS-CoV-2, IDP experienced post-vaccination infections at a similar rate as HV, mostly during the Omicron period. Less than half of IDP have received a bivalent booster. Additional doses, especially the bivalent dose, enhances the immune response in this population.
This research was supported by the Division of Intramural Research, NIAID, NIH.
Disclosures
All Authors: No reported disclosures
Predicting arbovirus re-emergence remains challenging in regions with limited off-season transmission and intermittent epidemics. Current mathematical models treat the depletion and replenishment of ...susceptible (non-immune) hosts as the principal drivers of re-emergence, based on established understanding of highly transmissible childhood diseases with frequent epidemics. We extend an analytical approach to determine the number of ‘skip’ years preceding re-emergence for diseases with continuous seasonal transmission, population growth and under-reporting. Re-emergence times are shown to be highly sensitive to small changes in low
R
0
(secondary cases produced from a primary infection in a fully susceptible population). We then fit a stochastic Susceptible–Infected–Recovered (SIR) model to observed case data for the emergence of dengue serotype DENV1 in Rio de Janeiro. This aggregated city-level model substantially over-estimates observed re-emergence times either in terms of skips or outbreak probability under forward simulation. The inability of susceptible depletion and replenishment to explain re-emergence under ‘well-mixed’ conditions at a city-wide scale demonstrates a key limitation of SIR aggregated models, including those applied to other arboviruses. The predictive uncertainty and high skip sensitivity to epidemiological parameters suggest a need to investigate the relevant spatial scales of susceptible depletion and the scaling of microscale transmission dynamics to formulate simpler models that apply at coarse resolutions.
The rapid emergence of SARS-CoV-2 variants challenges vaccination strategies. Here, we collected 201 serum samples from persons with a single infection or multiple vaccine exposures, or both. We ...measured their neutralization titers against 15 natural variants and 7 variants with engineered spike mutations and analyzed antigenic diversity. Antigenic maps of primary infection sera showed that Omicron sublineages BA.2, BA.4/BA.5, and BA.2.12.1 are distinct from BA.1 and more similar to Beta/Gamma/Mu variants. Three mRNA COVID-19 vaccinations increased neutralization of BA.1 more than BA.4/BA.5 or BA.2.12.1. BA.1 post-vaccination infection elicited higher neutralization titers to all variants than three vaccinations alone, although with less neutralization to BA.2.12.1 and BA.4/BA.5. Those with BA.1 infection after two or three vaccinations had similar neutralization titer magnitude and antigenic recognition. Accounting for antigenic differences among variants when interpreting neutralization titers can aid the understanding of complex patterns in humoral immunity that informs the selection of future COVID-19 vaccine strains.
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•Antigenic cartography of convalescent sera shows BA.1 as the most distinct variant•SARS-CoV-2 convalescent or vaccinee sera distinguish BA.1 and BA.4/BA.5 variants•Third vaccine boosts BA.1 and BA.2 neutralization more than BA.2.12.1 and BA.4/BA.5•BA.1 infection after two or three vaccinations broadens neutralization similarly
Wang et al. show that SARS-CoV-2 Omicron BA.1 or BA.1.1 infection after a second or third mRNA COVID-19 vaccination broadens neutralizing antibody responses to all variants, including Omicron, more than three vaccinations alone. BA.2.12.1 and BA.4/BA.5 evade neutralization more than BA.1 and BA.2 after three vaccinations or Omicron infection post-vaccination.
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