Modelling the transmission dynamics of RSV and the impact of routine vaccination

Introduction: Respiratory Syncytial Virus is the major viral cause of lower respiratory tract disease in young children worldwide, with the greatest burden of disease in infants aged 1-3 months. Consequently, vaccine development has centered on a vaccine to directly protect the infants in this age group. The fundamental problem is that these young infants are poor responders to candidate RSV vaccines. This thesis focuses on the use of mathematical models to explore the merits of vaccination. Methods: Following development and analysis of a simple non-age-structured ODE model, we elaborate this to a Realistic Age Structured model (RAS) capturing the key epidemiological characteristics of RSV and incorporating age-specific vaccination options. The compartmental ODE model was calibrated using agespecific and time series hospitalization data from a rural coastal Kenyan population. The determination of Who Acquires Infection From Whom (WAIFW) matrix was done using social contact data from 1) a synthetic mixing matrix generated from primarily household occupancy data and 2) a diary study that we conducted in the Kilifi Health and Demographic Surveillance System (KHDSS). The vaccine was assumed to elicit partial immunity equivalent to wild type infection and its impact was measured by the ratio of hospitalized RSV cases after to before introduction. of vaccination. Uncertainty and sensitivity analysis were undertaken using Latin Hypercube Sampling (LHS) and partial rank correlation respectively. Given the importance of households in the transmission of respiratory infections, an exploratory household model was developed to capture the transmission dynamics of RSV A and B in a population of households. Results: From the analytical work of the simple ODE model, we have demonstrated that the model has the potential to exhibit a backward bifurcation curve within realistic parameter ranges. Both the diary and the synthetic mixing matrices had similar characteristics i.e. strong assortative mixing in individuals less than 30 years old and strong mixing between children less than 5 years and adults between 20 and 50 years old. When the two matrices were jointly linearly regressed, their elements were well correlated with an R2 ~ 0.6. The RAS model was capable of capturing the age-specific disease and the temporal epidemic nature of RSV in the specified location. Introduction of routine universal vaccination at ages varying from the first month of life to the 10th year of life resulted in optimal long-term benefit at 7 months (for the diary contact model) and 5 months (for the synthetic contact model). The greatest benefit arose under the assumption of age-related mixing with the contact diary data with no great deal of effectiveness lost when the vaccine is delayed between 5 and 12 months of age from birth. Vaccination was also shown to change the temporal dynamics of RSV hospitalizations and also to increase the average age at primary infection. From the sensitivity analysis, we identified the duration of RSV specific maternal antibodies, duration of primary and tertiary infections as the most important parameters in explaining the imprecision observed in predicting both the age specific hospitalizations and the optimal month at vaccination. Results from the household model have demonstrated that the household epidemic profile may be different from the general population with strong interaction of the viruses in the household that do not necessarily reflect at the population level. Conclusion: The synthetic matrix method would be a preferable alternative route in estimating mixing patterns in populations with the required socio-demographic data. Retrospectively, the synthetic mixing data can be used to reconstruct contact patterns in the past and therefore beneficial in assessing the effect of demographic transition in disease transmission. Universal infant vaccination has the potential to significantly reduce the burden of RSV associated disease, even with delayed vaccination between 5 and 12 months. This age class represents the group that is being targeted by vaccines that are currently under development. More accurate data measuring the duration of RSV specific maternal antibodies and the duration of infections are required to reduce the uncertainty in the model predictions

Information content of household-stratified epidemics

Household structure is a key driver of many infectious diseases, as well as a natural target for interventions such as vaccination programs. Many theoretical and conceptual advances on household-stratified epidemic models are relatively recent, but have successfully managed to increase the applicability of such models to practical problems. To be of maximum realism and hence benefit, they require parameterisation from epidemiological data, and while household-stratified final size data has been the traditional source, increasingly time-series infection data from households are becoming available. This paper is concerned with the design of studies aimed at collecting time-series epidemic data in order to maximize the amount of information available to calibrate household models. A design decision involves a trade-off between the number of households to enrol and the sampling frequency. Two commonly used epidemiological study designs are considered: cross-sectional, where different households are sampled at every time point, and cohort, where the same households are followed over the course of the study period. The search for an optimal design uses Bayesian computationally intensive methods to explore the joint parameter-design space combined with the Shannon entropy of the posteriors to estimate the amount of information in each design. For the cross-sectional design, the amount of information increases with the sampling intensity, i.e., the designs with the highest number of time points have the most information. On the other hand, the cohort design often exhibits a trade-off between the number of households sampled and the intensity of follow-up. Our results broadly support the choices made in existing epidemiological data collection studies. Prospective problem-specific use of our computational methods can bring significant benefits in guiding future study designs

Model evaluation of target product profiles of an infant vaccine against respiratory syncytial virus (RSV) in a developed country setting

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract disease in children worldwide and is a significant cause of hospital admissions in young children in England. No RSV vaccine has been licensed but a number are under development. In this work, we present two structurally distinct mathematical models, parameterized using RSV data from the UK, which have been used to explore the effect of introducing an RSV paediatric vaccine to the National programme. We have explored different vaccine properties, and dosing regimens combined with a range of implementation strategies for RSV control. The results suggest that vaccine properties that confer indirect protection have the greatest effect in reducing the burden of disease in children under 5 years. The findings are reinforced by the concurrence of predictions from the two models with very different epidemiological structure. The approach described has general application in evaluating vaccine target product profiles

Vaccine induced herd immunity for control of respiratory syncytial virus disease in a low-income country setting

Background: Respiratory syncytial virus (RSV) is globally ubiquitous, and infection during the first six months of life is a major risk for severe disease and hospital admission; consequently RSV is the most important viral cause of respiratory morbidity and mortality in young children. Development of vaccines for young infants is complicated by the presence of maternal antibodies and immunological immaturity, but vaccines targeted at older children avoid these problems. Vaccine development for young infants has been unsuccessful, but this is not the case for older children (> 6m). Would vaccinating older children have a significant public health impact? We developed a mathematical model to explore the benefits of a vaccine against RSV. Methods and Findings: We have used a deterministic age structured model capturing the key epidemiological characteristics of RSV and performed a statistical maximum-likelihood fit to age-specific hospitalization data from a developing country setting. To explore the effects of vaccination under different mixing assumptions, we included two versions of contact matrices: one from a social contact diary study, and the second a synthesised construction based on demographic data. Vaccination is assumed to elicit an immune response equivalent to primary infection. Our results show that immunisation of young children (5–10m) is likely to be a highly effective method of protection of infants (<6m) against hospitalisation. The majority benefit is derived from indirect protection (herd immunity). A full sensitivity and uncertainty analysis using Latin Hypercube Sampling of the parameter space shows that our results are robust to model structure and model parameters. Conclusions: This result suggests that vaccinating older infants and children against RSV can have a major public health benefit

Predicting the relative impacts of maternal and neonatal respiratory syncytial virus (RSV) vaccine target product profiles: A consensus modelling approach

AbstractBackgroundRespiratory syncytial virus (RSV) is the major viral cause of infant and childhood lower respiratory tract disease worldwide. Defining the optimal target product profile (TPP) is complicated due to a wide range of possible vaccine properties, modalities and an incomplete understanding of the mechanism of natural immunity. We report consensus population level impact projections based on two mathematical models applied to a low income setting.MethodTwo structurally distinct age-specific deterministic compartmental models reflecting uncertainty associated with the natural history of infection and the mechanism by which immunity is acquired and lost were constructed. A wide range of vaccine TPPs were explored including dosing regime and uptake, and effects in the vaccinated individual on infectiousness, susceptibility, duration of protection, disease severity and interaction with maternal antibodies and natural induced immunity. These were combined with a range of vaccine implementation strategies, targeting the highest priority age group and calibrated using hospitalization data from Kilifi County Hospital, Kenya.FindingsBoth models were able to reproduce the data. The impact predicted by the two models was qualitatively similar across the range of TPPs, although one model consistently predicted higher impact than the other. For a proposed realistic range of scenarios of TPP combinations, the models predicted up to 70% reduction in hospitalizations in children under five years old. Vaccine designs which reduced the duration and infectiousness of infection were predicted to have higher impacts. The models were sensitive to the coverage and rate of loss of vaccine protection but not to the interaction between vaccine and maternal/naturally acquired immunity.ConclusionThe results suggest that vaccine properties leading to reduced virus circulation by lessening the duration and infectiousness of infection upon challenge are of major importance in population RSV disease control. These features should be a focus for vaccine development

Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors

International audienc

RSV modelling meeting

A group of investigators gathered to review the landscape of predictive mathematical modelling of RSV intervention programmes, and to identify gaps in knowledge and strategy options being explored. The objective was to set an agenda for future modelling and related research, to explore possible areas for collaborations, and provide an informed status update for various stakeholders

Toward a Surrogate Marker of Malaria Exposure: Modeling Longitudinal Antibody Measurements under Outbreak Conditions

Background: Biomarkers of exposure to Plasmodium falciparum would be a useful tool for the assessment of malaria burden and analysis of intervention and epidemiological studies. Antibodies to pre-erythrocytic antigens represent potential surrogates of exposure. Methods and Findings: In an outbreak cohort of U.S. Marines deployed to Liberia, we modeled pre- and post-deployment IgG against P. falciparum sporozoites by immunofluorescence antibody test, and both IgG and IgM against the P. falciparum circumsporozoite protein by enzyme-linked immunosorbant assay. Modeling seroconversion thresholds by a fixed ratio, linear regression or nonlinear regression produced sensitivity for identification of exposed U.S. Marines between 58-70% and specificities between 87-97%, compared with malaria-naïve U.S. volunteers. Exposure was predicted in 30-45% of the cohort. Conclusion: Each of the three models tested has merits in different studies, but further development and validation in endemic populations is required. Overall, these models provide support for an antibody-based surrogate marker of exposure to malaria