Factors associated with SARS-CoV-2 infection in unvaccinated children and young adults.

BACKGROUND AND OBJECTIVES: Pediatric COVID-19 cases are often mild or asymptomatic, which has complicated estimations of disease burden using existing testing practices. We aimed to determine the age-specific population seropositivity and risk factors of SARS-CoV-2 seropositivity among children and young adults during the pandemic in British Columbia (BC). METHODS: We conducted two cross-sectional serosurveys: phase 1 enrolled children and adults < 25 years between November 2020-May 2021 and phase 2 enrolled children < 10 years between June 2021-May 2022 in BC. Participants completed electronic surveys and self-collected finger-prick dried blood spot (DBS) samples. Samples were tested for immunoglobulin G antibodies against ancestral spike protein (S). Descriptive statistics from survey data were reported and two multivariable analyses were conducted to evaluate factors associated with seropositivity. RESULTS: A total of 2864 participants were enrolled, of which 95/2167 (4.4%) participants were S-seropositive in phase 1 across all ages, and 61/697 (8.8%) unvaccinated children aged under ten years were S-seropositive in phase 2. Overall, South Asian participants had a higher seropositivity than other ethnicities (13.5% vs. 5.2%). Of 156 seropositive participants in both phases, 120 had no prior positive SARS-CoV-2 test. Young infants and young adults had the highest reported seropositivity rates (7.0% and 7.2% respectively vs. 3.0-5.6% across other age groups). CONCLUSIONS: SARS-CoV-2 seropositivity among unvaccinated children and young adults was low in May 2022, and South Asians were disproportionately infected. This work demonstrates the need for improved diagnostics and reporting strategies that account for age-specific differences in pandemic dynamics and acceptability of testing mechanisms.

Examining the dynamics of Epstein-Barr virus shedding in the tonsils and the impact of HIV-1 coinfection on daily saliva viral loads.

Epstein-Barr virus (EBV) is transmitted by saliva and is a major cause of cancer, particularly in people living with HIV/AIDS. Here, we describe the frequency and quantity of EBV detection in the saliva of Ugandan adults with and without HIV-1 infection and use these data to develop a novel mathematical model of EBV infection in the tonsils. Eligible cohort participants were not taking antiviral medications, and those with HIV-1 infection had a CD4 count >200 cells/mm3. Over a 4-week period, participants provided daily oral swabs that we analysed for the presence and quantity of EBV. Compared with HIV-1 uninfected participants, HIV-1 coinfected participants had an increased risk of EBV detection in their saliva (IRR = 1.27, 95% CI = 1.10-1.47) and higher viral loads in positive samples. We used these data to develop a stochastic, mechanistic mathematical model that describes the dynamics of EBV, infected cells, and immune response within the tonsillar epithelium to analyse potential factors that may cause EBV infection to be more severe in HIV-1 coinfected participants. The model, fit using Approximate Bayesian Computation, showed high fidelity to daily oral shedding data and matched key summary statistics. When evaluating how model parameters differed among participants with and without HIV-1 coinfection, results suggest HIV-1 coinfected individuals have higher rates of B cell reactivation, which can seed new infection in the tonsils and lower rates of an EBV-specific immune response. Subsequently, both these traits may explain higher and more frequent EBV detection in the saliva of HIV-1 coinfected individuals.

Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing.

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing, with the timing of distancing measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia (BC), Canada, and five other jurisdictions, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimated the impact that physical distancing (social distancing) has had on the contact rate and examined the projected impact of relaxing distancing measures. We found that, as of April 11 2020, distancing had a strong impact in BC, consistent with declines in reported cases and in hospitalization and intensive care unit numbers; individuals practising physical distancing experienced approximately 0.22 (0.11-0.34 90% CI [credible interval]) of their normal contact rate. The threshold above which prevalence was expected to grow was 0.55. We define the "contact ratio" to be the ratio of the estimated contact rate to the threshold rate at which cases are expected to grow; we estimated this contact ratio to be 0.40 (0.19-0.60) in BC. We developed an R package 'covidseir' to make our model available, and used it to quantify the impact of distancing in five additional jurisdictions. As of May 7, 2020, we estimated that New Zealand was well below its threshold value (contact ratio of 0.22 [0.11-0.34]), New York (0.60 [0.43-0.74]), Washington (0.84 [0.79-0.90]) and Florida (0.86 [0.76-0.96]) were progressively closer to theirs yet still below, but California (1.15 [1.07-1.23]) was above its threshold overall, with cases still rising. Accordingly, we found that BC, New Zealand, and New York may have had more room to relax distancing measures than the other jurisdictions, though this would need to be done cautiously and with total case volumes in mind. Our projections indicate that intermittent distancing measures-if sufficiently strong and robustly followed-could control COVID-19 transmission. This approach provides a useful tool for jurisdictions to monitor and assess current levels of distancing relative to their threshold, which will continue to be essential through subsequent waves of this pandemic.

Diffusion analysis of single particle trajectories in a Bayesian nonparametrics framework.

Single particle tracking (SPT), where individual molecules are fluorescently labelled and followed over time, is an important tool that allows the spatiotemporal dynamics of subcellular biological systems to be studied at very fine temporal and spatial resolution. Mathematical models of particle motion are typically based on Brownian diffusion, reflecting the noisy environment that biomolecules inhabit. In order to study changes in particle behaviour within individual tracks, Hidden Markov models (HMM) featuring multiple diffusive states have been used as a descriptive tool for SPT data. However, such models are typically specified with an a priori defined number of particle states and it has not been clear how such assumptions have affected their outcomes. Here, we propose a method for simultaneously inferring the number of diffusive states alongside the dynamic parameters governing particle motion. Our method is an infinite HMM (iHMM) with the general framework of Bayesian nonparametric models. We directly extend previous applications of these concepts in molecular biophysics to the SPT framework and propose and test an additional constraint with the goal of accelerating convergence and reducing computational time. We test our iHMM using simulated data and apply it to a previously analyzed large SPT dataset for B cell receptor motion on the plasma membrane of B cells of the immune system.

Modeling COVID-19 and Its Impacts on U.S. Immigration and Customs Enforcement (ICE) Detention Facilities, 2020.

U.S. Immigration and Customs Enforcement (ICE) facilities house thousands of undocumented immigrants in environments discordant with the public health recommendations to reduce the transmission of 2019 novel coronavirus (COVID-19). Using ICE detainee population data obtained from the ICE Enforcement and Removal Operations (ERO) website as of March 2, 2020, we implemented a simple stochastic susceptible-exposed-infected-recovered model to estimate the rate of COVID-19 transmission within 111 ICE detention facilities and then examined impacts on regional hospital intensive care unit (ICU) capacity. Models considered three scenarios of transmission (optimistic, moderate, pessimistic) over 30-, 60-, and 90-day time horizons across a range of facility sizes. We found that 72% of individuals are expected to be infected by day 90 under the optimistic scenario (R0 = 2.5), while nearly 100% of individuals are expected to be infected by day 90 under a more pessimistic (R0 = 7) scenario. Although asynchronous outbreaks are more likely, day 90 estimates provide an approximation of total positive cases after all ICE facility outbreaks. We determined that, in the most optimistic scenario, coronavirus outbreaks among a minimum of 65 ICE facilities (59%) would overwhelm ICU beds within a 10-mile radius and outbreaks among a minimum of 8 ICE facilities (7%) would overwhelm local ICU beds within a 50-mile radius over a 90-day period, provided every ICU bed was made available for sick detainees. As policymakers seek to rapidly implement interventions that ensure the continued availability of life-saving medical resources across the USA, they may be overlooking the pressing need to slow the spread of COVID-19 infection in ICE's detention facilities. Preventing the rapid spread necessitates intervention measures such as granting ICE detainees widespread release from an unsafe environment by returning them to the community.

Applied stretch initiates directional invasion through the action of Rap1 GTPase as a tension sensor.

Although it is known that a stiffening of the stroma and the rearrangement of collagen fibers within the extracellular matrix facilitate the movement of tumor cells away from the primary lesion, the underlying mechanisms responsible are not fully understood. We now show that this invasion, which can be initiated by applying tensional loads to a three-dimensional collagen gel matrix in culture, is dependent on the Rap1 GTPases (Rap1a and Rap1b, referred to collectively as Rap1). Under these conditions Rap1 activity stimulates the formation of focal adhesion structures that align with the tensional axis as single tumor cells move into the matrix. These effects are mediated by the ability of Rap1 to induce the polarized polymerization and retrograde flow of actin, which stabilizes integrins and recruits vinculin to preformed adhesions, particularly those near the leading edge of invasive cells. Rap1 activity also contributes to the tension-induced collective invasive elongation of tumor cell clusters and it enhances tumor cell growth in vivo Thus, Rap1 mediates the effects of increased extracellular tension in multiple ways that are capable of contributing to tumor progression when dysregulated.

Dependence of T cell antigen recognition on T cell receptor-peptide MHC confinement time.

T cell receptor (TCR) binding to diverse peptide-major histocompatibility complex (pMHC) ligands results in various degrees of T cell activation. Here we analyze which binding properties of the TCR-pMHC interaction are responsible for this variation in pMHC activation potency. We have analyzed activation of the 1G4 cytotoxic T lymphocyte clone by cognate pMHC variants and performed thorough correlation analysis of T cell activation with 1G4 TCR-pMHC binding properties measured in solution. We found that both the on rate (k(on)) and off rate (k(off)) contribute to activation potency. Based on our results, we propose a model in which rapid TCR rebinding to the same pMHC after chemical dissociation increases the effective half-life or "confinement time" of a TCR-pMHC interaction. This confinement time model clarifies the role of k(on) in T cell activation and reconciles apparently contradictory reports on the role of TCR-pMHC binding kinetics and affinity in T cell activation.

Effects of spatiotemporal HSV-2 lesion dynamics and antiviral treatment on the risk of HIV-1 acquisition.

Patients with Herpes Simplex Virus-2 (HSV-2) infection face a significantly higher risk of contracting HIV-1. This is thought to be due to herpetic lesions serving as entry points for HIV-1 and tissue-resident CD4+ T cell counts increasing during HSV-2 lesional events. We have created a stochastic and spatial mathematical model describing the dynamics of HSV-2 infection and immune response in the genital mucosa. Using our model, we first study the dynamics of a developing HSV-2 lesion. We then use our model to quantify the risk of infection with HIV-1 following sexual exposure in HSV-2 positive women. Untreated, we find that HSV-2 infected women are up to 8.6 times more likely to acquire HIV-1 than healthy patients. However, when including the effects of the HSV-2 antiviral drug, pritelivir, the risk of HIV-1 infection is predicted to decrease by up to 35%, depending on drug dosage. We estimate the relative importance of decreased tissue damage versus decreased CD4+ cell presence in determining the effectiveness of pritelivir in reducing HIV-1 infection. Our results suggest that clinical trials should be performed to evaluate the effectiveness of pritelivir or similar agents in preventing HIV-1 infection in HSV-2 positive women.

Stochastic Dynamics of the Latently Infected Cell Reservoir During HIV Infection.

The presence of cells latently infected with HIV is currently considered to be a major barrier to viral eradication within a patient. Here, we consider birth-death-immigration models for the latent cell population in a single patient, and present analytical results for the size of this population in the absence of treatment. We provide results both at steady state (viral set point), and during the non-equilibrium setting of early infection. We obtain semi-analytic results showing how latency-reversing drugs might be expected to affect the size of the latent pool over time. We also analyze the probability of rare mutant viral strains joining the latent cell population, allowing for steady-state and dynamic viral populations within the host.

In vivo regulation of integrin turnover by outside-in activation.

The development of three-dimensional tissue architecture requires precise control over the attachment of cells to the extracellular matrix (ECM). Integrins, the main ECM-binding receptors in animals, are regulated in multiple ways to modulate cell-ECM adhesion. One example is the conformational activation of integrins by extracellular signals ('outside-in activation') or by intracellular signals ('inside-out activation'), whereas another is the modulation of integrin turnover. We demonstrate that outside-in activation regulates integrin turnover to stabilize tissue architecture in vivo Treating Drosophila embryos with Mg(2+) and Mn(2+), known to induce outside-in activation, resulted in decreased integrin turnover. Mathematical modeling combined with mutational analysis provides mechanistic insight into the stabilization of integrins at the membrane. We show that as tissues mature, outside-in activation is crucial for regulating the stabilization of integrin-mediated adhesions. This data identifies a new in vivo role for outside-in activation and sheds light on the key transition between tissue morphogenesis and maintenance.

Sustained Reduction in Sexual Behavior that May Pose a Risk of HIV Transmission Following Diagnosis During Early HIV Infection Among Gay Men in Vancouver, British Columbia.

Increased viral load during early HIV infection (EHI) disproportionately contributes to HIV transmission among gay men. We examined changes in sexual behavior that may pose a risk of HIV transmission (condomless anal sex (AS) with a serodiscordant or unknown status partner, CAS-SDU) in a cohort of 25 gay men newly diagnosed during EHI who provided information on 241 sexual partners at six time points following diagnosis. Twenty-two (88%) participants reported ≥1 AS partner (median time to first AS 80 days) and 12 (55%) reported ≥1 partnership involving CAS-SDU (median 116 days). In hierarchical generalized linear mixed effects models, AS was significantly less likely in all time periods following diagnosis and more likely with serodiscordant partners. The likelihood of CAS-SDU decreased three months after diagnosis and was higher in recently versus acutely infected participants. Most men in our study abstained from sex immediately after diagnosis with sustained longer-term reduction in CAS-SDU, confirming the importance of timely diagnosis during EHI.

Conditions for eradicating hepatitis C in people who inject drugs: A fibrosis aware model of hepatitis C virus transmission.

It is estimated that 80% of new hepatitis C virus (HCV) infections occur among people who inject drugs (PWID). Eradicating HCV from this population is key for the complete eradication of the disease, and the advent of simple to use, high efficacy treatments could conceivably make this scenario possible. This paper presents a mathematical model where transmission of HCV is studied in a simulated population of PWID where fibrosis progression is explicitly tracked. The stability thresholds that determine whether HCV will remain endemic or become eradicated were established numerically, and analytically on a reduced version of the model. Conditions on testing and treatment rates for eradication to occur were determined, within the context of the new high efficacy therapies. The results show that HCV eradication in the PWID population of the Vancouver, BC test scenario is achievable, but testing and especially treatment rates will need to increase significantly from current rates. Parameter estimates were drawn from published data.

Design Parameters for Granzyme-Mediated Cytotoxic Lymphocyte Target-Cell Killing and Specificity.

Cytotoxic lymphocytes are key elements of the immune system that are primarily responsible for targeting cells infected with intracellular pathogens, or cells that have become malignantly transformed. Target cells are killed mainly via lymphocyte exocytosis of specialized lysosomes containing perforin, a pore-forming protein, and granzymes, which are proteases that induce apoptosis. Due to its central role in lymphocyte biology, as well as its implication in a host of pathologies from cancer to autoimmunity, the granzyme-perforin pathway has been the subject of extensive investigation. Nevertheless, the details of exactly how granzyme and perforin cooperate to induce target-cell death remain controversial. To further investigate this system, we developed a biophysical model of the immunological synapse between a cytotoxic lymphocyte and a target cell using a spatial stochastic simulation algorithm. We used this model to calculate the spatiotemporal evolution of granzyme B and perforin from the time of their exocytosis to granzyme internalization by the target cell. We used a metric of granzyme internalization to delineate which biological processes were critical for successful target-cell lysis. We found that the high aspect ratio of the immunological synapse was insufficient in this regard, and that molecular crowding within the synapse is critical to preserve sufficient concentrations of perforin and granzyme for consistent pore formation and granzyme transfer to target cells. However, even when pore formation occurs in our model, a large amount of both granzyme and perforin still escape from the synapse. We argue that a tight seal between the cytotoxic lymphocyte and its target cell is not required to avoid bystander killing. Instead, we propose that the requirement for spatiotemporal colocalization of granzyme and perforin acts as an effective bimolecular filter to ensure target specificity.

Asymptotic analysis of first passage time problems inspired by ecology.

A hybrid asymptotic-numerical method is formulated and implemented to accurately calculate the mean first passage time (MFPT) for the expected time needed for a predator to locate small patches of prey in a 2-D landscape. In our analysis, the movement of the predator can have both a random and a directed component, where the diffusivity of the predator is isotropic but possibly spatially heterogeneous. Our singular perturbation methodology, which is based on the assumption that the ratio [Formula: see text] of the radius of a typical prey patch to that of the overall landscape is asymptotically small, leads to the derivation of an algebraic system that determines the MFPT in terms of parameters characterizing the shapes of the small prey patches together with a certain Green's function, which in general must be computed numerically. The expected error in approximating the MFPT by our semi-analytical procedure is smaller than any power of [Formula: see text], so that our approximation of the MFPT is still rather accurate at only moderately small prey patch radii. Overall, our hybrid approach has the advantage of eliminating the difficulty with resolving small spatial scales in a full numerical treatment of the partial differential equation (PDE). Similar semi-analytical methods are also developed and implemented to accurately calculate related quantities such as the variance of the mean first passage time (VMFPT) and the splitting probability. Results for the MFPT, the VMFPT, and splitting probability obtained from our hybrid methodology are validated with corresponding results computed from full numerical simulations of the underlying PDEs.

Assessing the optimal virulence of malaria-targeting mosquito pathogens: a mathematical study of engineered Metarhizium anisopliae.

BACKGROUND: Metarhizium anisopliae is a naturally occurring fungal pathogen of mosquitoes. Recently, Metarhizium has been engineered to act against malaria by directly killing the disease agent within mosquito vectors and also effectively blocking onward transmission. It has been proposed that efforts should be made to minimize the virulence of the fungal pathogen, in order to slow the development of resistant mosquitoes following an actual deployment. RESULTS: Two mathematical models were developed and analysed to examine the efficacy of the fungal pathogen. It was found that, in many plausible scenarios, the best effects are achieved with a reduced or minimal pathogen virulence, even if the likelihood of resistance to the fungus is negligible. The results for both models depend on the interplay between two main effects: the ability of the fungus to reduce the mosquito population, and the ability of fungus-infected mosquitoes to compete for resources with non-fungus-infected mosquitoes. CONCLUSIONS: The results indicate that there is no obvious choice of virulence for engineered Metarhizium or similar pathogens, and that all available information regarding the population ecology of the combined mosquito-fungus system should be carefully considered. The models provide a basic framework for examination of anti-malarial mosquito pathogens that should be extended and improved as new laboratory and field data become available.

Estimating the total utilization of take home naloxone during an unregulated drug toxicity crisis: A Bayesian modeling approach.

BACKGROUND: British Columbia (BC) Canada has a large take-home naloxone (THN) program, implemented as part of the provincial response to the ongoing toxic unregulated drug supply emergency. Ascertaining the rate of use of THN kits is vital to understanding the full impact of the program. However, this is a challenging problem due to under-reporting of kit distribution. This study aims to estimate the total number of THN kits used based on the number of THN kits shipped, the number of THN kits reported as distributed, and the number of THN kits reported as used. METHODS: We used BC THN shipment and distribution records (February 2015 to August 2023) to inform a simple Bayesian model of naloxone kit distribution and use. A logistic regression term by health region and distribution site type was incorporated to account for variable under-reporting, and a convolution term was incorporated to account for kit distribution. RESULTS: We find the number of THN kits reported as used, and the number of total THN kits distributed, are largely under-reported. An estimated 1,500 (95 % CrI: 1,430 - 1,590) THN kits per 10,000 BC population were used, of which 288 per 10,000 had been reported as used. Of all the THN kits shipped, the model estimated that 43 % (95 % CrI: 41-45 %) of kits were used. We also found variation in both distribution and use by distribution site type, with kits distributed from overdose prevention sites having the highest rate of use (56 %; 95 % CrI: 53-59 %). CONCLUSION: Across all sites, kit use is approximately five times higher than has been reported. Our framework can also be applied to other localities where THN programs operate, in order to better estimate the true reach and impact of take home naloxone distribution.

SARS-CoV-2 cross-sectional seroprevalence study among public school staff in Metro Vancouver after the first Omicron wave in British Columbia, Canada.

OBJECTIVE: To determine the SARS-CoV-2 seroprevalence among school workers within the Greater Vancouver area, British Columbia, Canada, after the first Omicron wave. DESIGN: Cross-sectional study by online questionnaire, with blood serology testing. SETTING: Three main school districts (Vancouver, Richmond and Delta) in the Vancouver metropolitan area. PARTICIPANTS: Active school staff enrolled from January to April 2022, with serology testing between 27 January and 8 April 2022. Seroprevalence estimates were compared with data obtained from Canadian blood donors weighted over the same sampling period, age, sex and postal code distribution. PRIMARY AND SECONDARY OUTCOMES: SARS-CoV-2 nucleocapsid antibody testing results adjusted for test sensitivity and specificity, and regional variation across school districts using Bayesian models. RESULTS: Of 1850 school staff enrolled, 65.8% (1214/1845) reported close contact with a COVID-19 case outside the household. Of those close contacts, 51.5% (625/1214) were a student and 54.9% (666/1214) were a coworker. Cumulative incidence of COVID-19 positive testing by self-reported nucleic acid or rapid antigen testing since the beginning of the pandemic was 15.8% (291/1845). In a representative sample of 1620 school staff who completed serology testing (87.6%), the adjusted seroprevalence was 26.5% (95% CrI 23.9% to 29.3%), compared with 32.4% (95% CrI 30.6% to 34.5%) among 7164 blood donors. CONCLUSION: Despite frequent COVID-19 exposures reported, SARS-CoV-2 seroprevalence among school staff in this setting remained no greater than the community reference group. Results are consistent with the premise that many infections were acquired outside the school setting, even with Omicron.

Mechanical modulation of receptor-ligand interactions at cell-cell interfaces.

Cell surface receptors have been extensively studied because they initiate and regulate signal transduction cascades leading to a variety of functional cellular outcomes. An important class of immune receptors (e.g., T-cell antigen receptors) whose ligands are anchored to the surfaces of other cells remain poorly understood. The mechanism by which ligand binding initiates receptor phosphorylation, a process termed "receptor triggering", remains controversial. Recently, direct measurements of the (two-dimensional) receptor-ligand complex lifetimes at cell-cell interface were found to be smaller than (three-dimensional) lifetimes in solution but the underlying mechanism is unknown. At the cell-cell interface, the receptor-ligand complex spans a short intermembrane distance (15 nm) compared to long surface molecules (LSMs) whose ectodomains span >40 nm and these LSMs include phosphatases (e.g., CD45) that dephosphorylate the receptor. It has been proposed that size-based segregation of LSMs from a receptor-ligand complex is a mechanism of receptor triggering but it is unclear whether the mechanochemistry supports such small-scale segregation. Here we present a nanometer-scale mathematical model that couples membrane elasticity with the compressional stiffness and lateral mobility of LSMs. We find robust supradiffusive segregation of LSMs from a single receptor-ligand complex. The model predicts that LSM redistribution will result in a time-dependent tension on the complex leading to a decreased two-dimensional lifetime. Interestingly, the model predicts a nonlinear relationship between the three- and two-dimensional lifetimes, which can enhance the ability of receptors to discriminate between similar ligands.

A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients.

Motivated by viral persistence in HIV+ patients on long-term anti-retroviral treatment (ART), we present a stochastic model of HIV viral dynamics in the blood stream. We consider the hypothesis that the residual viremia in patients on ART can be explained principally by the activation of cells latently infected by HIV before the initiation of ART and that viral blips (clinically-observed short periods of detectable viral load) represent large deviations from the mean. We model the system as a continuous-time, multi-type branching process. Deriving equations for the probability generating function we use a novel numerical approach to extract the probability distributions for latent reservoir sizes and viral loads. We find that latent reservoir extinction-time distributions underscore the importance of considering reservoir dynamics beyond simply the half-life. We calculate blip amplitudes and frequencies by computing complete viral load probability distributions, and study the duration of viral blips via direct numerical simulation. We find that our model qualitatively reproduces short small-amplitude blips detected in clinical studies of treated HIV infection. Stochastic models of this type provide insight into treatment-outcome variability that cannot be found from deterministic models.

Modestly protective cytomegalovirus vaccination of young children effectively prevents congenital infection at the population level.

A vaccine to prevent congenital cytomegalovirus infection (cCMV) is a public health priority. cCMV results from maternal primary or non-primary CMV infection (reinfection, or reactivation of chronic infection) during pregnancy. Young children are a major source of transmission to pregnant women because they shed CMV at high viral loads for prolonged periods. CMV vaccines evaluated in clinical trials so far have demonstrated only approximately 50% efficacy against maternal primary infection. None of these have been approved, as higher levels of vaccine efficacy are assumed to be required to substantially reduce cCMV prevalence. Here, we designed a mathematical model to capture the relationship between viral shedding by young children and maternal CMV infections during pregnancy. Using this model, we were able to quantify the impact of CMV post-infection immunity on protecting against reinfection and viral shedding. There was a 36% reduction in the risk of infection to a seropositive person with post-infection immunity (reinfection) versus a seronegative person without this immunity (primary infection), given the same exposure. Viral shedding following reinfection was only 34% the quantity of that following primary infection. Our model also predicted that a vaccine that confers the equivalent of post-infection immunity, when given to young children, would markedly reduce both CMV transmission to pregnant women and the prevalence of cCMV. Thus, we predict that existing vaccine candidates that have been shown to be only modestly protective may in fact be highly effective at preventing cCMV by interrupting child-to-mother transmission.