Mathematical modelling of respiratory syncytial virus (RSV): vaccination strategies and budget applications

Modelling the epidemiological impact of maternal respiratory syncytial virus (RSV) vaccination in Australia

BACKGROUND

Respiratory syncytial virus (RSV) is a leading cause of respiratory illness among infants. A maternal RSV vaccine that protects young infants has recently been approved for registration in Australia. We estimated the population benefits of a future year-round maternal RSV vaccination program in terms of prevented RSV infections and hospitalisations in Australia.

METHODS

We described RSV transmission using an age-structured compartmental model calibrated to Australian aggregated monthly RSV-coded hospitalisations in children aged <5 years. We accounted for mother and infant interactions in the model to capture herd effects more realistically. Using the model, we estimated the annual age-specific RSV infections and hospitalisations prevented for a range of assumptions for vaccine efficacy, coverage, and durability to estimate the future impact of year-round maternal RSV vaccination on infants and the wider population.

RESULTS

Assuming base case vaccine efficacy, 6 months duration of protection and 70% coverage, RSV hospitalisations were predicted to fall by 60% (from 3.0 to 1.2 per 100 persons) in infants aged <3 months and 40% (from 1.9 to 1.1 per 100 persons) in 3-5-month-olds. These benefits were primarily due to direct protection to infants of vaccinated mothers. This vaccine program was predicted to reduce the population-level RSV infection by about 4%. Coverage and duration assumptions were influential, with higher coverage leading to larger declines in infants <6 months, and increased duration of protection leading to additional declines in infection and hospitalisation risk in older infants aged 6-8 months.

CONCLUSIONS

With vaccine uptake similar to that achieved for other maternal vaccines in Australia, a year-round RSV maternal vaccination program is predicted to approximately halve the number of RSV hospitalisations in infants younger than 6 months. There was a small herd effect predicted in the base case but potential for larger benefits if vaccine coverage or the duration of protection exceeds base case assumptions.

Long-term effects of non-pharmaceutical interventions on total disease burden in parsimonious epidemiological models

The recent global COVID-19 pandemic resulted in governments enacting non-pharmaceutical interventions (NPIs) targeted at reducing transmission of SARS-CoV-2. But the NPIs also affected the transmission of viruses causing non-target seasonal respiratory diseases, including influenza and respiratory syncytial virus (RSV). In many countries, the NPIs were found to reduce cases of such seasonal respiratory diseases, but there is also evidence that subsequent relaxation of NPIs led to outbreaks of these diseases that were larger than pre-pandemic ones, due to the accumulation of susceptible individuals prior to relaxation. Therefore, the net long-term effects of NPIs on the total disease burden of non-target diseases remain unclear. Knowledge of this is important for infectious disease management and maintenance of public health. In this study, we shed light on this issue for the simplified scenario of a set of NPIs that prevent or reduce transmission of a seasonal respiratory disease for about a year and are then removed, using mathematical analyses and numerical simulations of a suite of four epidemiological models with varying complexity and generality. The model parameters were estimated using empirical data pertaining to seasonal respiratory diseases and covered a wide range. Our results showed that NPIs reduced the total disease burden of a non-target seasonal respiratory disease in the long-term. Expressed as a percentage of population size, the reduction was greater for larger values of the basic reproduction number and the immunity loss rate, reflecting larger outbreaks and hence more infections averted by imposition of NPIs. Our study provides a foundation for exploring the effects of NPIs on total disease burden in more-complex scenarios.

Impact of including productivity costs in economic analyses of vaccines for C. difficile infections and infant respiratory syncytial virus, in a UK setting

OBJECTIVES

It has been estimated that vaccines can accrue a relatively large part of their value from patient and carer productivity. Yet, productivity value is not commonly or consistently considered in health economic evaluations of vaccines in several high-income countries. To contribute to a better understanding of the potential impact of including productivity value on the expected cost-effectiveness of vaccination, we illustrate the extent to which the incremental costs would change with and without productivity value incorporated.

METHODS

For two vaccines currently under development, one against Cloistridioides difficile (C. difficile) infection and one against respiratory syncytial disease (RSV), we estimated their incremental costs with and without productivity value included and compared the results.

RESULTS

In this analysis, reflecting a UK context, a C. difficile vaccination programme would prevent £12.3 in productivity costs for every person vaccinated. An RSV vaccination programme would prevent £49 in productivity costs for every vaccinated person.

CONCLUSIONS

Considering productivity costs in future cost-effectiveness analyses of vaccines for C. difficile and RSV will contribute to better-informed reimbursement decisions from a societal perspective.

In Silico Clinical Trials: Is It Possible?

Modeling and simulation (M&S), including in silico (clinical) trials, helps accelerate drug research and development and reduce costs and have coined the term "model-informed drug development (MIDD)." Data-driven, inferential approaches are now becoming increasingly complemented by emerging complex physiologically and knowledge-based disease (and drug) models, but differ in setup, bottlenecks, data requirements, and applications (also reminiscent of the different scientific communities they arose from). At the same time, and within the MIDD landscape, regulators and drug developers start to embrace in silico trials as a potential tool to refine, reduce, and ultimately replace clinical trials. Effectively, silos between the historically distinct modeling approaches start to break down. Widespread adoption of in silico trials still needs more collaboration between different stakeholders and established precedence use cases in key applications, which is currently impeded by a shattered collection of tools and practices. In order to address these key challenges, efforts to establish best practice workflows need to be undertaken and new collaborative M&S tools devised, and an attempt to provide a coherent set of solutions is provided in this chapter. First, a dedicated workflow for in silico clinical trial (development) life cycle is provided, which takes up general ideas from the systems biology and quantitative systems pharmacology space and which implements specific steps toward regulatory qualification. Then, key characteristics of an in silico trial software platform implementation are given on the example of jinkō.ai (nova's end-to-end in silico clinical trial platform). Considering these enabling scientific and technological advances, future applications of in silico trials to refine, reduce, and replace clinical research are indicated, ranging from synthetic control strategies and digital twins, which overall shows promise to begin a new era of more efficient drug development.

Mathematical Modeling: Global Stability Analysis of Super Spreading Transmission of Respiratory Syncytial Virus (RSV) Disease

In this paper, a model for the transmission of respiratory syncytial virus (RSV) in a constant human population in which there exist super spreading infected individuals (who infect many people during a single encounter) is considered. It has been observed in the epidemiological data for the diseases caused by this virus that there are cases where some individuals are super-spreaders of the virus. We formulate a simply SEIrIsR (susceptible–exposed–regular infected–super-spreading infected–recovered) mathematical model to describe the dynamics of the transmission of this disease. The proposed model is analyzed using the standard stability method by using Routh-Hurwitz criteria. We obtain the basic reproductive number (R0) using the next generation method. We establish that when R0<1, the disease-free state is locally asymptotically stable and the disease endemic state is unstable. The reverse is true when R0>1, the disease endemic state becomes the locally asymptotically stable state and the disease-free state becomes unstable. It is also established that the two equilibrium states are globally asymptotically stable. The numerical simulations show how the dynamics of the disease change as values of the parameters in the SEIrIsR are varied.

Use of mathematical modelling to assess respiratory syncytial virus epidemiology and interventions: a literature review

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection worldwide, resulting in approximately sixty thousand annual hospitalizations of< 5-year-olds in the United States alone and three million annual hospitalizations globally. The development of over 40 vaccines and immunoprophylactic interventions targeting RSV has the potential to significantly reduce the disease burden from RSV infection in the near future. In the context of RSV, a highly contagious pathogen, dynamic transmission models (DTMs) are valuable tools in the evaluation and comparison of the effectiveness of different interventions. This review, the first of its kind for RSV DTMs, provides a valuable foundation for future modelling efforts and highlights important gaps in our understanding of RSV epidemics. Specifically, we have searched the literature using Web of Science, Scopus, Embase, and PubMed to identify all published manuscripts reporting the development of DTMs focused on the population transmission of RSV. We reviewed the resulting studies and summarized the structure, parameterization, and results of the models developed therein. We anticipate that future RSV DTMs, combined with cost-effectiveness evaluations, will play a significant role in shaping decision making in the development and implementation of intervention programs.

Analysis of Delayed Vaccination Regimens: A Mathematical Modeling Approach

The first round of vaccination against coronavirus disease 2019 (COVID-19) began in early December of 2020 in a few countries. There are several vaccines, and each has a different efficacy and mechanism of action. Several countries, for example, the United Kingdom and the USA, have been able to develop consistent vaccination programs where a great percentage of the population has been vaccinated (May 2021). However, in other countries, a low percentage of the population has been vaccinated due to constraints related to vaccine supply and distribution capacity. Countries such as the USA and the UK have implemented different vaccination strategies, and some scholars have been debating the optimal strategy for vaccine campaigns. This problem is complex due to the great number of variables that affect the relevant outcomes. In this article, we study the impact of different vaccination regimens on main health outcomes such as deaths, hospitalizations, and the number of infected. We develop a mathematical model of COVID-19 transmission to focus on this important health policy issue. Thus, we are able to identify the optimal strategy regarding vaccination campaigns. We find that for vaccines with high efficacy (>70%) after the first dose, the optimal strategy is to delay inoculation with the second dose. On the other hand, for a low first dose vaccine efficacy, it is better to use the standard vaccination regimen of 4 weeks between doses. Thus, under the delayed second dose option, a campaign focus on generating a certain immunity in as great a number of people as fast as possible is preferable to having an almost perfect immunity in fewer people first. Therefore, based on these results, we suggest that the UK implemented a better vaccination campaign than that in the USA with regard to time between doses. The results presented here provide scientific guidelines for other countries where vaccination campaigns are just starting, or the percentage of vaccinated people is small.

A Multivariate Age-Structured Stochastic Model with Immunization Strategies to Describe Bronchiolitis Dynamics

Bronchiolitis has a high morbidity in children under 2 years old. Respiratory syncytial virus (RSV) is the most common pathogen causing the disease. At present, there is only a costly humanized monoclonal RSV-specific antibody to prevent RSV. However, different immunization strategies are being developed. Hence, evaluation and comparison of their impact is important for policymakers. The analysis of the disease with a Bayesian stochastic compartmental model provided an improved and more natural description of its dynamics. However, the consideration of different age groups is still needed, since disease transmission greatly varies with age. In this work, we propose a multivariate age-structured stochastic model to understand bronchiolitis dynamics in children younger than 2 years of age considering high-quality data from the Valencia health system integrated database. Our modeling approach combines ideas from compartmental models and Bayesian hierarchical Poisson models in a novel way. Finally, we develop an extension of the model that simulates the effect of potential newborn immunization scenarios on the burden of disease. We provide an app tool that estimates the expected reduction in bronchiolitis episodes for a range of different values of uptake and effectiveness.

Assessment of the Effects of Active Immunisation against Respiratory Syncytial Virus (RSV) using Decision-Analytic Models: A Systematic Review with a Focus on Vaccination Strategies, Modelling Methods and Input Data

BACKGROUND

Several vaccine and antibody candidates are currently in development for the prevention of lower respiratory tract infections caused by the respiratory syncytial virus (RSV).

METHODS

We searched MEDLINE, Embase, and SCOPUS and included model-based evaluations of RSV vaccinations. Two reviewers performed the selection, data extraction, and quality evaluation with EVIDEM. Cost-effectiveness (CE) estimates were converted to $US purchasing power parity (PPP), year 2018 values. Potential economic and epidemiological outcomes were summarised for maternal, infant, children, and elderly vaccinations. The PROSPERO identifier is CRD42019122570.

RESULTS

In total, 22 model-based studies were reviewed. On average, a potential 27% reduction in RSV hospitalisations in infants was projected for maternal vaccination and 50% for direct infant immunisation. The CE of maternal vaccination was $US1766-5857 PPP 2018/disability-adjusted life-years (DALYs) for Global Alliance for Vaccines and Immunisation (Gavi)-eligible countries. For England, the maximum cost-effective price of maternal vaccination was estimated at $US81.5 PPP 2018. Infant vaccination was associated with higher CE ratios in low- and high-income settings. Vaccination of neonates born before the RSV season was the most cost effective in high-income settings. Higher values for vaccine effectiveness, duration of protection, and vaccine uptake increased the benefits. Due to indirect effects, the vaccination of school-age children and a cocooning strategy were effective alternatives to protect infants, and the vaccination of children aged < 5 years had a beneficial impact on the elderly.

CONCLUSION

RSV vaccines with anticipated characteristics may reduce a sizeable proportion of the RSV burden. The results are subject to uncertainty because of the limited epidemiological and clinical data. Data on RSV incidence and hospitalisation risk for granular age strata should be prioritised to facilitate the evaluation of RSV interventions and decision making.

Optimization of the Controls against the Spread of Zika Virus in Populations

In this paper, we study and explore two control strategies to decrease the spread of Zika virus in the human and mosquito populations. The control strategies that we consider in this study are awareness and spraying campaigns. We solve several optimal control problems relying on a mathematical epidemic model of Zika that considers both human and mosquito populations. The first control strategy is broad and includes using information campaigns, encouraging people to use bednetting, wear long-sleeve shirts, or similar protection actions. The second control is more specific and relies on spraying insecticides. The control system relies on a Zika mathematical model with control functions. To develop the optimal control problem, we use Pontryagins’ maximum principle, which is numerically solved as a boundary value problem. For the mathematical model of the Zika epidemic, we use parameter values extracted from real data from an outbreak in Colombia. We study the effect of the costs related to the controls and infected populations. These costs are important in real life since they can change the outcomes and recommendations for health authorities dramatically. Finally, we explore different options regarding which control measures are more cost-efficient for society.

Number needed to immunize to prevent RSV with extended half-life monoclonal antibody

BACKGROUND

Respiratory syncytial virus (RSV) is one of the most important respiratory pathogens in young children. Infants <6 months of age and infants and young children with extreme pre-term birth, and cardiac and pulmonary co-morbidities experience the highest incidence of severe RSV disease. There are no licensed vaccines; immunoprophylaxis is recommended for the highest risk children. Extended half-life RSV monoclonal antibodies (EHL-mAbs) are under development intended for immunization of all infants and high-risk children <2 years of age. We modeled the anticipated public health benefits of RSV EHL-mAb immunization using the number needed to immunize (NNI).

METHODS

We combined RSV hospitalization, outpatient and outpatient lower respiratory tract infection (LRI) incidence estimates and a range of immunization efficacies to estimate the annual NNI. We calculated the absolute incidence rate reduction (ARR) by multiplying the incidence rates by immunization efficacy. NNI was calculated as the reciprocal of the ARR.

RESULTS

For an RSV EHL-mAb with 70% efficacy, 6-18 infants would need to be immunized to prevent one RSV-associated outpatient visit, and 13-33 infants would need to be immunized to prevent one RSV-associated LRI outpatient visit. To prevent one RSV-associated hospitalization, 37-85 infants 0-5 months of age, and 107-280 infants 6-11 months of age would need to be immunized.

CONCLUSIONS

Public health benefits, such as disease cases averted due to immunization, are essential elements in consideration of candidate vaccines for a national immunization program. An RSV EHL-mAb of moderate efficacy could have high impact. These data provide an additional perspective for public health decision making.

Estimating the impact of multiple immunization products on medically-attended respiratory syncytial virus (RSV) infections in infants

BACKGROUND

Palivizumab, a monoclonal antibody and the only licensed immunization product for preventing respiratory syncytial virus (RSV) infection, is recommended for children with certain high-risk conditions. Other antibody products and maternal vaccines targeting young infants are in clinical development. Few studies have compared products closest to potential licensure and have primarily focused on the effects on hospitalizations only. Estimates of the impact of these products on medically-attended (MA) infections in a variety of healthcare settings are needed to assist with developing RSV immunization recommendations.

METHODS

We developed a tool for practicing public health officials to estimate the impact of immunization strategies on RSV-associated MA lower respiratory tract infections (LRTIs) in various healthcare settings among infants <12 months. Users input RSV burden and seasonality and examine the influence of altering product efficacy and uptake assumptions. We used the tool to evaluate candidate products' impacts among a US birth cohort.

RESULTS

We estimated without immunization, 407,360 (range: 339,650-475,980) LRTIs are attended annually in outpatient clinics, 147,240 (126,070-168,510) in emergency departments (EDs), and 33,180 (24,760-42,900) in hospitals. A passive antibody candidate targeting all infants prevented the most LRTIs: 196,470 (48% of visits without immunization) outpatient clinic visits (range: 163,810-229,650), 75,250 (51%) EDs visits (64,430-86,090), and 18,140 (55%) hospitalizations (13,770-23,160). A strategy combining maternal vaccine candidate and palivizumab prevented 58,210 (14% of visits without immunization) LRTIs in outpatient clinics (range: 48,520-67,970), 19,580 (13%) in EDs (16,760-22,400), and 8,190 (25%) hospitalizations (6,390-10,150).

CONCLUSIONS

Results underscore the potential for anticipated products to reduce serious RSV illness. Our tool (provided to readers) can be used by different jurisdictions and accept updated data. Results can aid economic evaluations and public health decision-making regarding RSV immunization products.

Potential impact of a maternal vaccine for RSV: A mathematical modelling study

Respiratory syncytial virus (RSV) is a major cause of respiratory morbidity and one of the main causes of hospitalisation in young children. While there is currently no licensed vaccine for RSV, a vaccine candidate for pregnant women is undergoing phase 3 trials. We developed a compartmental age-structured model for RSV transmission, validated using linked laboratory-confirmed RSV hospitalisation records for metropolitan Western Australia. We adapted the model to incorporate a maternal RSV vaccine, and estimated the expected reduction in RSV hospitalisations arising from such a program. The introduction of a vaccine was estimated to reduce RSV hospitalisations in Western Australia by 6-37% for 0-2month old children, and 30-46% for 3-5month old children, for a range of vaccine effectiveness levels. Our model shows that, provided a vaccine is demonstrated to extend protection against RSV disease beyond the first three months of life, a policy using a maternal RSV vaccine could be effective in reducing RSV hospitalisations in children up to six months of age, meeting the objective of a maternal vaccine in delaying an infant's first RSV infection to an age at which severe disease is less likely.

Unexpected Infection Spikes in a Model of Respiratory Syncytial Virus Vaccination

Respiratory Syncytial Virus (RSV) is an acute respiratory infection that infects millions of children and infants worldwide. Recent research has shown promise for the development of a vaccine, with a range of vaccine types now in clinical trials or preclinical development. We extend an existing mathematical model with seasonal transmission to include vaccination. We model vaccination both as a continuous process, applying the vaccine during pregnancy, and as a discrete one, using impulsive differential equations, applying pulse vaccination. We develop conditions for the stability of the disease-free equilibrium and show that this equilibrium can be destabilised under certain extreme conditions, even with 100% coverage using an (unrealistic) vaccine. Using impulsive differential equations and introducing a new quantity, the impulsive reproduction number, we showed that eradication could be acheived with 75% coverage, while 50% coverage resulted in low-level oscillations. A vaccine that targets RSV infection has the potential to significantly reduce the overall prevalence of the disease, but appropriate coverage is critical.

Potential Cost-Effectiveness of RSV Vaccination of Infants and Pregnant Women in Turkey: An Illustration Based on Bursa Data

Background

Worldwide, respiratory syncytial virus (RSV) is considered to be the most important viral cause of respiratory morbidity and mortality among infants and young children. Although no active vaccine is available on the market yet, there are several active vaccine development programs in various stages. To assess whether one of these vaccines might be a future asset for national immunization programs, modeling the costs and benefits of various vaccination strategies is needed.

Objectives

To evaluate the potential cost-effectiveness of RSV vaccination of infants and/or pregnant women in Turkey.

Methods

A multi-cohort static Markov model with cycles of one month was used to compare the cost-effectiveness of vaccinated cohorts versus non-vaccinated cohorts. The 2014 Turkish birth cohort was divided by twelve to construct twelve monthly birth cohorts of equal size (111,459 new-borns). Model input was based on clinical data from a multicenter prospective study from Bursa, Turkey, combined with figures from the (inter)national literature and publicly available data from the Turkish Statistical Institute (TÜÏK). Incremental cost-effectiveness ratios (ICERs) were expressed in Turkish Lira (TL) per quality-adjusted life year (QALY) gained.

Results

Vaccinating infants at 2 and 4 months of age would prevent 145,802 GP visits, 8,201 hospitalizations and 48 deaths during the first year of life, corresponding to a total gain of 1650 QALYs. The discounted ICER was estimated at 51,969 TL (26,220 US $ in 2013) per QALY gained. Vaccinating both pregnant women and infants would prevent more cases, but was less attractive from a pure economic point of view with a discounted ICER of 61,653 TL (31,106 US $ in 2013) per QALY. Vaccinating only during pregnancy would result in fewer cases prevented than infant vaccination and a less favorable ICER.

Conclusion

RSV vaccination of infants and/or pregnant women has the potential to be cost-effective in Turkey. Although using relatively conservative assumptions, all evaluated strategies remained slightly below the threshold of 3 times the GDP per capita.

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.

Environmental drivers of the spatiotemporal dynamics of respiratory syncytial virus in the United States

Epidemics of respiratory syncytial virus (RSV) are known to occur in wintertime in temperate countries including the United States, but there is a limited understanding of the importance of climatic drivers in determining the seasonality of RSV. In the United States, RSV activity is highly spatially structured, with seasonal peaks beginning in Florida in November through December and ending in the upper Midwest in February-March, and prolonged disease activity in the southeastern US. Using data on both age-specific hospitalizations and laboratory reports of RSV in the US, and employing a combination of statistical and mechanistic epidemic modeling, we examined the association between environmental variables and state-specific measures of RSV seasonality. Temperature, vapor pressure, precipitation, and potential evapotranspiration (PET) were significantly associated with the timing of RSV activity across states in univariate exploratory analyses. The amplitude and timing of seasonality in the transmission rate was significantly correlated with seasonal fluctuations in PET, and negatively correlated with mean vapor pressure, minimum temperature, and precipitation. States with low mean vapor pressure and the largest seasonal variation in PET tended to experience biennial patterns of RSV activity, with alternating years of “early-big” and “late-small” epidemics. Our model for the transmission dynamics of RSV was able to replicate these biennial transitions at higher amplitudes of seasonality in the transmission rate. This successfully connects environmental drivers to the epidemic dynamics of RSV; however, it does not fully explain why RSV activity begins in Florida, one of the warmest states, when RSV is a winter-seasonal pathogen. Understanding and predicting the seasonality of RSV is essential in determining the optimal timing of immunoprophylaxis.

Respiratory syncytial virus (RSV) causes annual outbreaks of respiratory disease every winter in temperate climates, which can be severe particularly among infants. In the United States, RSV activity begins each autumn in Florida and appears to spread from the southeast to the northwest. Using data on hospitalizations and laboratory tests for RSV, we show that the timing of epidemics is associated with a variety of climatic factors, including temperature, vapor pressure, precipitation, and potential evapotranspiration (PET). Furthermore, using a dynamic model, we show that seasonal variation in the transmission rate of RSV can be correlated with the amplitude and timing of variation in PET, which is a measure of demand for water from the atmosphere. States with colder, drier weather and a large seasonal swing in PET tended to experience an alternating pattern of “early-big” RSV epidemics one year followed by a “late-small” epidemic the next year, which our model was able to reproduce based on the interaction between susceptible and infectious individuals. However, we cannot fully explain why epidemics begin in Florida. Being able to understand and predict the timing of RSV activity is important for optimizing the delivery of immunoprophylaxis to high-risk individuals.

A Bayesian SIRS model for the analysis of respiratory syncytial virus in the region of Valencia, Spain

We present a Bayesian stochastic susceptible-infected-recovered-susceptible (SIRS) model in discrete time to understand respiratory syncytial virus dynamics in the region of Valencia, Spain. A SIRS model based on ordinary differential equations has also been proposed to describe RSV dynamics in the region of Valencia. However, this continuous-time deterministic model is not suitable when the initial number of infected individuals is small. Stochastic epidemic models based on a probability of disease transmission provide a more natural description of the spread of infectious diseases. In addition, by allowing the transmission rate to vary stochastically over time, the proposed model provides an improved description of RSV dynamics. The Bayesian analysis of the model allows us to calculate both the posterior distribution of the model parameters and the posterior predictive distribution, which facilitates the computation of point forecasts and prediction intervals for future observations.

Modelling the seasonal epidemics of respiratory syncytial virus in young children

BACKGROUND

Respiratory syncytial virus (RSV) is a major cause of paediatric morbidity. Mathematical models can be used to characterise annual RSV seasonal epidemics and are a valuable tool to assess the impact of future vaccines.

OBJECTIVES

Construct a mathematical model of seasonal epidemics of RSV and by fitting to a population-level RSV dataset, obtain a better understanding of RSV transmission dynamics.

METHODS

We obtained an extensive dataset of weekly RSV testing data in children aged less than 2 years, 2000-2005, for a birth cohort of 245,249 children through linkage of laboratory and birth record datasets. We constructed a seasonally forced compartmental age-structured Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) mathematical model to fit to the seasonal curves of positive RSV detections using the Nelder-Mead method.

RESULTS

From 15,830 specimens, 3,394 were positive for RSV. RSV detections exhibited a distinct biennial seasonal pattern with alternating sized peaks in winter months. Our SEIRS model accurately mimicked the observed data with alternating sized peaks using disease parameter values that remained constant across the 6 years of data. Variations in the duration of immunity and recovery periods were explored. The best fit to the data minimising the residual sum of errors was a model using estimates based on previous models in the literature for the infectious period and a slightly lower estimate for the immunity period.

CONCLUSIONS

Our age-structured model based on routinely collected population laboratory data accurately captures the observed seasonal epidemic curves. The compartmental SEIRS model, based on several assumptions, now provides a validated base model. Ranges for the disease parameters in the model that could replicate the patterns in the data were identified. Areas for future model developments include fitting climatic variables to the seasonal parameter, allowing parameters to vary according to age and implementing a newborn vaccination program to predict the effect on RSV incidence.

Respiratory syncytial virus immunization program for the United States: impact of performance determinants of a theoretical vaccine

OBJECTIVES

To inform strategic decisions on respiratory syncytial virus (RSV) vaccine development and identify critical endpoints likely to drive the vaccine's medical and economic impact.

DESIGN

A decision-analysis model populated using healthcare utilization data and costs from the literature; vaccine efficacy and duration based on assumptions.

SETTING

Vaccination in the physician office setting in the USA.

PARTICIPANTS

A hypothetical cohort of newborn infants.

INTERVENTION

Vaccination of children at low and high risk of respiratory sequelae with a theoretical RSV vaccine vs palivizumab prophylaxis for children at high risk.

OUTCOME MEASURES

Medical and economic value of RSV vaccination, including cost per quality adjusted life-year (QALY) gained.

RESULTS

Using base-case assumptions (efficacy 50% at birth; half-life 12 months), RSV vaccination would prevent 23,069 hospitalizations and 66 deaths per vaccinated birth cohort in the USA. Excluding vaccination costs, direct medical costs for RSV would reduce by $236 million, and income and productivity losses by $134 million. Assuming a vaccine cost per course similar to Rotarix® in the USA ($232 including administration fees), the cost per QALY gained would be $93,401 (95% CI: $65,815-$126,060) from the healthcare system perspective and $65,115 (95% CI: $41,003-$93,679) from the societal perspective. The net cost (healthcare system perspective) per life-year saved would be $216,120 (95% CI: $161,184-$263,981); the cost per hospitalization averted would be $19,172 (95% CI: $14,679-$22,093). Aside from efficacy, the vaccine's impact is sensitive to the start of protective immunity and the duration of protection.

CONCLUSIONS

Development of an RSV vaccine would substantially reduce inpatient hospitalizations and outpatient visits. It would also have an impact on infant mortality. To demonstrate the full medical and economic value of the vaccine, appropriate endpoints or endpoint surrogates for hospitalization, mortality, and total case reductions should be collected during vaccine development.

Strategic priorities for respiratory syncytial virus (RSV) vaccine development

Although RSV has been a high priority for vaccine development, efforts to develop a safe and effective vaccine have yet to lead to a licensed product. Clinical and epidemiologic features of RSV disease suggest there are at least 4 distinct target populations for vaccines, the RSV naïve young infant, the RSV naïve child ≥ 6 months of age, pregnant women (to provide passive protection to newborns), and the elderly. These target populations raise different safety and efficacy concerns and may require different vaccination strategies. The highest priority target population is the RSV naïve child. The occurrence of serious adverse events associated with the first vaccine candidate for young children, formalin inactivated RSV (FI-RSV), has focused vaccine development for the young RSV naïve child on live virus vaccines. Enhanced disease is not a concern for persons previously primed by a live virus infection. A variety of live-attenuated viruses have been developed with none yet achieving licensure. New live-attenuated RSV vaccines are being developed and evaluated that maybe sufficiently safe and efficacious to move to licensure. A variety of subunit vaccines are being developed and evaluated primarily for adults in whom enhanced disease is not a concern. An attenuated parainfluenza virus 3 vector expressing the RSV F protein was evaluated in RSV naïve children. Most of these candidate vaccines have used the RSV F protein in various vaccine platforms including virus-like particles, nanoparticles, formulated with adjuvants, and expressed by DNA or virus vectors. The other surface glycoprotein, the G protein, has also been used in candidate vaccines. We now have tools to make and evaluate a wide range of promising vaccines. Costly clinical trials in the target population are needed to evaluate and select candidate vaccines for advancement to efficacy trials. Better data on RSV-associated mortality in developing countries, better estimates of the risk of long term sequelae such as wheezing after infection, better measures of protection in target populations, and data on the costs and benefits of vaccines for target populations are needed to support and justify funding this process. Addressing these challenges and needs should improve the efficiency and speed of achieving a safe and effective, licensed RSV vaccine.

Cost-effectiveness of potential infant vaccination against respiratory syncytial virus infection in The Netherlands

INTRODUCTION

Respiratory syncytial virus (RSV) infection is one of the major causes of respiratory illness in infants, infecting virtually every child before the age of 2 years. Currently, several Phase 1 trials with RSV vaccines in infants are ongoing or have been completed. As yet, no efficacy estimates are available for these vaccine candidates. Nevertheless, cost-effectiveness estimates might be informative to enable preliminary positioning of an RSV vaccine.

METHODS

A decision analysis model was developed in which a Dutch birth cohort was followed for 12 months. A number of potential vaccination strategies were reviewed such as vaccination at specific ages, a two- or three-dosing scheme and seasonal vaccination versus year-round vaccination. The impact of the assumptions made was explored in various sensitivity analyses, including probabilistic analysis. Outcome measures included the number of GP visits, hospitalizations and deaths, costs, quality-adjusted life years and incremental cost-effectiveness ratios (ICERs).

RESULTS

Currently, without vaccination, an annual number of 28,738 of RSV-related GP visits, 1623 hospitalizations, and 4.5 deaths are estimated in children in the age of 0-1 year. The total annual cost to society of RSV in the non-vaccination scenario is €7.7 million (95%CI: 1.7-16.7) and the annual disease burden is estimated at 597 QALYs (95%CI: 133-1319). In case all infants would be offered a potentially safe and effective 3-dose RSV vaccination scheme at the age of 0, 1 and 3 months, the total annual net costs were estimated to increase to €21.2 million, but 544 hospitalizations and 1.5 deaths would be averted. The ICER was estimated at €34,142 (95%CI: € 21,652-€ 87,766) per QALY gained. A reduced dose schedule, seasonal vaccination, and consideration of out-of-pocket expenses all resulted in more favorable ICER values, whereas a reduced vaccine efficacy or a delay in the timing of vaccination resulted in less favorable ICERs.

DISCUSSION

Our model used recently updated estimates on the burden of RSV disease in children and it included plausible utilities. However, due to the absence of clinical trial data, a number of crucial assumptions had to be made related to the characteristics of potential RSV vaccine. The outcomes of our modeling exercise show that vaccination of infants against RSV might be cost-effective. However, clinical trial data are warranted.

Modelling effectiveness of herd level vaccination against Q fever in dairy cattle

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. The control of this infection in cattle is crucial: infected ruminants can indeed encounter reproductive disorders and represent the most important source of human infection. In the field, vaccination is currently advised in infected herds but the comparative effectiveness of different vaccination protocols has never been explored: the duration of the vaccination programme and the category of animals to be vaccinated have to be determined. Our objective was to compare, by simulation, the effectiveness over 10 years of three different vaccination strategies in a recently infected dairy cattle herd.A stochastic individual-based epidemic model coupled with a model of herd demography was developed to simulate three temporal outputs (shedder prevalence, environmental bacterial load and number of abortions) and to calculate the extinction rate of the infection. For all strategies, the temporal outputs were predicted to strongly decrease with time at least in the first years of vaccination. However, vaccinating only three years was predicted inadequate to stabilize these dynamic outputs at a low level. Vaccination of both cows and heifers was predicted as being slightly more effective than vaccinating heifers only. Although the simulated extinction rate of the infection was high for both scenarios, the outputs decreased slower when only heifers were vaccinated.Our findings shed new light on vaccination effectiveness related to Q fever. Moreover, the model can be further modified for simulating and assessing various Q fever control strategies such as environmental and hygienic measures.