Public Health Impact of the Adjuvanted RSVPreF3 Vaccine for Respiratory Syncytial Virus Prevention Among Older Adults in the United States

INTRODUCTION

Respiratory syncytial virus (RSV) is an important cause of lower respiratory tract disease in older adults, resulting in substantial morbidity and mortality.

METHODS

This study estimates the public health impact of vaccination with the adjuvanted RSVPreF3 vaccine among adults aged ≥ 60 years in the United States (US). A static, multi-cohort Markov model was used to estimate RSV-related outcomes over a 3-year time horizon for scenarios with and without one-time RSV vaccination. The base-case analysis assumed the same vaccination coverage as for influenza vaccines, with key epidemiology and vaccine inputs obtained from the published literature and phase 3 clinical trial results for the adjuvanted RSVPreF3 vaccine. Model outcomes included the clinical burden of RSV (symptomatic RSV acute respiratory illness [RSV-ARI] cases [classified as upper or lower respiratory tract disease], pneumonia complications, and mortality) and RSV-related healthcare resource use (hospitalizations, emergency department visits, outpatient visits, and antibiotic prescriptions).

RESULTS

In the base-case analysis, approximately 56.7 million adults aged ≥ 60 years received the vaccine, resulting in 2,954,465 fewer symptomatic RSV-ARI cases over 3 years compared with no vaccination, including 321,019 fewer X-ray confirmed pneumonia cases and 16,660 fewer RSV-related deaths. Vaccination also prevented a substantial number of RSV-related hospitalizations (203,891), emergency department visits (164,060), outpatient visits (1,577,586), and antibiotic prescriptions (1,343,915) over the 3-year period. A considerable public health impact was observed across a range of sensitivity analyses.

CONCLUSIONS

These findings highlight the potential of the adjuvanted RSVPreF3 vaccine to substantially reduce RSV disease burden among US older adults aged ≥ 60 years.

The potential public health impact of the respiratory syncytial virus prefusion F protein vaccine in people aged ≥60 years in Japan: results of a Markov model analysis

BACKGROUND

Respiratory syncytial virus (RSV), a common respiratory pathogen, can lead to severe symptoms, especially in older adults (OA). A recently developed RSV prefusion F protein (RSVPreF3 OA) vaccine confers high protection against RSV lower respiratory tract disease (LRTD) over two full RSV seasons. The aim of this study was to assess the potential public health impact of RSVPreF3 OA vaccination in the Japanese OA population.

RESEARCH DESIGN AND METHODS

A static Markov model was used to estimate the number of symptomatic RSV cases, hospitalizations and deaths in the Japanese population aged ≥ 60 years over a 3-year time horizon. Japan-specific RSV epidemiology and healthcare resource use parameters were used; vaccine efficacy was derived from a phase 3 randomized study (AReSVi-006, NCT04886596). Vaccination coverage was set to 50%.

RESULTS

Without vaccination, >5 million RSV acute respiratory illness (ARI) would occur (2.5 million LRTD and 2.8 million upper respiratory tract infections) leading to ~ 3.5 million outpatient visits, >534,000 hospitalizations and ~ 25,500 RSV-related deaths over 3 years. Vaccination could prevent > 1 million RSV-ARI cases, 728,000 outpatient visits, 143,000 hospitalizations and 6,840 RSV-related deaths.

CONCLUSIONS

RSVPreF3 OA vaccination is projected to have a substantial public health impact by reducing RSV-related morbidity and mortality in the OA population.

Determinants of basic childhood vaccination coverage in European and OECD countries

Vaccination coverage varies between countries and over time. Using official databases, we extracted data on 50 national-level immunization, socio-economic, demographic, healthcare, and cultural factors, and the uptake of the third dose of diphtheria toxoid, tetanus toxoid, and pertussis vaccines (DTP3) and the first dose of measles-containing vaccines (MCV1) for 61 countries between 1990 and 2019. The main branch of the analysis included all covariates, while a secondary branch excluded life-expectancy and child mortality. The statistical analysis was completed in three stages: a variable-selection stage via random forests; multilevel multiple imputation for missing data in the reduced dataset; and generalized estimating equations (GEE) over all imputed datasets with pooled results. Less than 20 covariates were retained after variable-selection. Among a relatively small number of statistically significant (p-value <.05) effects in the pooled GEE results of our main branch, under-5 mortality and long-term orientation culture showed negative associations with both uptake outcomes and GDP per capita a positive association. For MCV1, whether a second dose was integrated into routine immunization appeared as the overall strongest negative correlate. In the secondary analytical branch, results were largely consistent, with a few additional statistically significant effects emerging, mainly related to immunization and healthcare system characteristics. These insights improve our understanding of the main factors influencing vaccine uptake, some of which are broadly contextual (e.g., GDP, socio-cultural factors), requiring bespoke vaccine program approaches, in order to maximize childhood vaccine uptake over time.

Different forms of superspreading lead to different outcomes: Heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2

Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity.

To investigate the effect of different sources of superspreading on disease dynamics, we implemented superspreading driven by heterogeneity in infectiousness and heterogeneity in contact behavior into an individual-based model for the transmission of SARS-CoV-2 in the Belgian population. We compared the impact of both forms of superspreading in a scenario without interventions as well as in a scenario in which a period of strict social distancing (i.e. a lockdown) is followed by a period of partial release. We found that both forms of superspreading have very different effects. On the one hand, increasing the level of infectiousness-related heterogeneity led to less outbreaks being observed following the introduction of one infected individual in the population. Furthermore, final outbreak sizes decreased, and outbreaks became slower, with lower and later peaks, and a lower herd immunity threshold. Finally, the risk for resurgence of an outbreak following a period of lockdown also decreased. On the other hand, when contact-related heterogeneity was high, this also led to smaller final sizes, but caused outbreaks to be more explosive regarding other aspects (such as higher peaks that occurred earlier). The herd immunity threshold also increased, as did the risk of resurgence of outbreaks.

Individual factors influencing COVID-19 vaccine acceptance in between and during pandemic waves (July-December 2020)

Background

A year after the start of the COVID-19 outbreak, the global rollout of vaccines gives us hope of ending the pandemic. Lack of vaccine confidence, however, poses a threat to vaccination campaigns. This study aims at identifying individuals’ characteristics that explain vaccine willingness in Flanders (Belgium), while also describing trends over time (July–December 2020).

Methods

The analysis included data of 10 survey waves of the Great Corona Survey, a large-scale online survey that was open to the general public and had 17,722–32,219 respondents per wave. Uni- and multivariable general additive models were fitted to associate vaccine willingness with socio-demographic and behavioral variables, while correcting for temporal and geographical variability.

Results

We found 84.2% of the respondents willing to be vaccinated, i.e., respondents answering that they were definitely (61.2%) or probably (23.0%) willing to get a COVID-19 vaccine, while 9.8% indicated maybe, 3.9% probably not and 2.2% definitely not. In Flanders, vaccine willingness was highest in July 2020 (90.0%), decreased over the summer period to 80.2% and started to increase again from late September, reaching 85.9% at the end of December 2020. Vaccine willingness was significantly associated with respondents’ characteristics: previous survey participation, age, gender, province, educational attainment, household size, financial situation, employment sector, underlying medical conditions, mental well-being, government trust, knowing someone with severe COVID-19 symptoms and compliance with restrictive measures. These variables could explain much, but not all, variation in vaccine willingness.

Conclusions

Both the timing and location of data collection influence vaccine willingness results, emphasizing that comparing data from different regions, countries and/or timepoints should be done with caution. To maximize COVID-19 vaccination coverage, vaccination campaigns should focus on (a combination of) subpopulations: aged 31–50, females, low educational attainment, large households, difficult financial situation, low mental well-being and labourers, unemployed and self-employed citizens.

SOCRATES-CoMix: a platform for timely and open-source contact mixing data during and in between COVID-19 surges and interventions in over 20 European countries

BACKGROUND

SARS-CoV-2 dynamics are driven by human behaviour. Social contact data are of utmost importance in the context of transmission models of close-contact infections.

METHODS

Using online representative panels of adults reporting on their own behaviour as well as parents reporting on the behaviour of one of their children, we collect contact mixing (CoMix) behaviour in various phases of the COVID-19 pandemic in over 20 European countries. We provide these timely, repeated observations using an online platform: SOCRATES-CoMix. In addition to providing cleaned datasets to researchers, the platform allows users to extract contact matrices that can be stratified by age, type of day, intensity of the contact and gender. These observations provide insights on the relative impact of recommended or imposed social distance measures on contacts and can inform mathematical models on epidemic spread.

CONCLUSION

These data provide essential information for policymakers to balance non-pharmaceutical interventions, economic activity, mental health and wellbeing, during vaccine rollout.

No Such Thing as a Free-Rider? Understanding Drivers of Childhood and Adult Vaccination through a Multicountry Discrete Choice Experiment

Increased vaccine hesitancy and refusal negatively affects vaccine uptake, leading to the reemergence of vaccine preventable diseases. We aim to quantify the relative importance of factors people consider when making vaccine decisions for themselves, or for their child, with specific attention for underlying motives arising from context, such as required effort (accessibility) and opportunism (free riding on herd immunity). We documented attitudes towards vaccination and performed a discrete choice experiment in 4802 respondents in The United Kingdom, France and Belgium, eliciting preferences for six attributes: (1) vaccine effectiveness, (2) vaccine preventable disease burden, (3) vaccine accessibility in terms of copayment, vaccinator and administrative requirements, (4) frequency of mild vaccine-related side-effects, (5) vaccination coverage in the country’s population and (6) local vaccination coverage in personal networks. We distinguished adults deciding on vaccination for themselves from parents deciding for their youngest child. While all attributes were found to be significant, vaccine effectiveness and accessibility stood out in all (sub)samples, followed by vaccine preventable disease burden. We confirmed that people attach more value to severity of disease compared to its frequency, and discovered that peer influence dominates free-rider motives, especially for the vaccination of children. These behavioral data are insightful for policy and are essential to parameterize dynamic vaccination behavior in simulation models. In contrast to what most game theoretical models assume, social norms dominate free-rider incentives. Policy-makers and healthcare workers should actively communicate on high vaccination coverage, and draw attention to the effectiveness of vaccines while optimizing their practical accessibility.

Preferential differences in vaccination decision-making for oneself or one's child in The Netherlands: a discrete choice experiment

BACKGROUND

To optimize the focus of future public information campaigns in The Netherlands promoting the uptake of vaccines among adults and children, we quantified the contribution of several attributes to the vaccination decision.

METHOD

We performed a discrete choice experiment (DCE) among Dutch adults including six attributes, i.e. vaccine effectiveness, vaccine-preventable burden of disease (specified in severity and frequency), accessibility of vaccination in terms of co-payment and prescription requirements, frequency of mild side-effects, population-level vaccination coverage and local vaccination coverage among family and friends. Participants answered the DCE from their own perspective ('oneself' group) or with regard to a vaccine decision for their youngest child ('child' group). The data was analysed by means of panel mixed logit models.

RESULTS

We included 1547 adult participants (825 'oneself' and 722 'child'). Vaccine effectiveness was the most important attribute in the 'oneself' group, followed by burden of disease (relative importance (RI) 78%) and accessibility (RI 76%). In the 'child' group, burden of disease was most important, but tied closely with vaccine effectiveness (RI 97%). Of less importance was the risk of mild vaccine-related side-effects and both population and local vaccination coverage. Interestingly, participants were more willing to vaccinate when uptake among the population or family and friends was high, indicating that social influence and social norms plays a role.

CONCLUSIONS

Vaccine effectiveness and disease severity are key attributes in vaccination decision-making for adults making a decision for themselves and for parents who decide for their children. Hence, public information campaigns for both adult and child vaccination should primarily focus on these two attributes. In addition, reinforcing social norms may be considered.

Indications for healthcare surge capacity in European countries facing an exponential increase in coronavirus disease (COVID-19) cases, March 2020

European healthcare systems face extreme pressure from coronavirus disease (COVID-19). We relate country-specific accumulated COVID-19 deaths (intensity approach) and active COVID-19 cases (magnitude approach) to measures of healthcare system capacity: hospital beds, healthcare workers and healthcare expenditure. Modelled by the intensity approach with a composite measure for healthcare capacity, the countries experiencing the highest pressure on 25 March 2020 - relative to Italy on 11 March - were Italy, Spain, the Netherlands and France (www.covid-hcpressure.org).

Drivers of vaccine decision-making in South Africa: A discrete choice experiment

To increase vaccination coverage, it is essential to understand the vaccine decision-making process. High population coverage is required to obtain herd immunity and to protect vulnerable groups in terms of age (e.g. the very young) or health (e.g. immunodeficiency). Vaccine confidence and coverage in South Africa are relatively low, opening the window for sustained outbreaks of vaccine-preventable diseases in a country facing one of the most severe HIV epidemics in the world. To capture the vaccine-related decision-making process in South Africa, we performed a discrete choice experiment with 1200 participants in December 2017. We asked for their preferences with respect to (1) vaccine effectiveness, (2) vaccine-preventable burden of disease, (3) accessibility of the vaccine in terms of co-payment and prescription requirements, (4) frequency of mild vaccine-related side-effects, (5) population vaccination coverage and (6) local vaccination coverage. We distinguished between decision-making for vaccines administered to the participant, and for vaccines administered to their youngest child. We analyzed the data for each of these groups using a panel mixed logit model and found similar results for decisions to vaccinate oneself or one's child. Vaccine effectiveness was the most important attribute followed by population coverage and burden of disease. Local coverage and accessibility were also important determinants of vaccination behavior, but to a lesser extent. Regarding population and local coverage, we observed a positive effect on vaccine utility indicating the potential of peer influence. As such, social normative influence could be exploited to increase vaccination confidence and coverage. With respect to vaccine-preventable burden of the disease, the marginal utilities showed disease severity to be more important than frequency of disease. Policymakers and health care workers should stress the effectiveness of vaccines together with the severity of vaccine-preventable diseases.

Economic Burden of Epilepsy in Rural Ituri, Democratic Republic of Congo

BACKGROUND

Epilepsy is still very prevalent in Sub-Saharan Africa, particularly in remote, poverty-confronted onchocerciasis-endemic villages. It constitutes a significant burden for the families and communities. However, the financial costs of managing persons with epilepsy (PWE) have not been assessed in these settings. Proper cost analyses will facilitate future health interventions.

METHODS

In November 2017, persons with epilepsy (PWE) and their caretakers were recruited at health centres of the Logo health zone in the Democratic Republic of Congo. A pre-tested questionnaire was administered to collect information on both direct and indirect costs of epilepsy, as well as household income of participants.

FINDINGS

The weighted mean cost of epilepsy was 241.2 USD per PWE per year (50.2% direct cost, 49.8% indirect cost). Epilepsy-related expenses represented 46.5% of the mean household income. Traditional medicine accounted for 68.2% of the direct cost. An estimated cumulative cost of 1929.6 USD attributable to epilepsy had been incurred by the populations of the Logo health zone for each PWE in the community.

INTERPRETATION

Almost half of the household revenue was spent on epilepsy care. Expenses on traditional medicine must be discouraged via education and regular provision of affordable anti-epileptic drugs. Prevention of onchocerciasis-associated epilepsy using optimal control measures will avert additional epilepsy-related costs on the community. Early diagnosis and proper management of epilepsy would be economically beneficial in the study villages.

Sponsorship Bias in Base-Case Values and Uncertainty Bounds of Health Economic Evaluations? A Systematic Review of Herpes Zoster Vaccination

BACKGROUND

New health technologies are more likely adopted when they have lower incremental cost-effectiveness ratios (ICERs) and/or when their ICER is presented with more certainty. Industry-funded (IF) health economic evaluations use often more favorable base-case values, leading to more favorable conclusions.

PURPOSE

To study whether IF health economic evaluations of varicella-zoster virus vaccination in the elderly use more favorable base-case values and account for less uncertainty than non-industry-funded (NIF) evaluations.

METHODS

DATA SOURCE

PubMed. Data extracted: funding source; incremental cost per quality-adjusted life year (QALY) gained; vaccine price; study quality score; base-case values, uncertainty ranges, and data sources for influential parameters: duration of vaccine protection, utility loss due to herpes zoster (HZ) disease, percentage of HZ patients developing postherpetic neuralgia (PHN), and duration of PHN.

DATA SYNTHESIS

qualitative comparisons; Fisher exact test for differences in study quality score and 1-sided Mann-Whitney U tests for differences in base-case values and uncertainty ranges.

RESULTS

Despite using the same data sources, IF studies ( n = 10) assume a longer duration of vaccine protection ( U = 56, P = 0.03), have a higher percentage of HZ patients developing PHN ( U = 22/33, P = 0.02/0.03 for ages 60-64/65-69), and tend to use higher HZ utility loss than NIF studies ( n = 11) for their baseline. IF studies show lower ICERs given similar or even higher vaccine prices than NIF studies, consider less uncertainty around the duration of vaccine protection ( U = 8, P < 0.001), and tend to use less uncertainty around the duration of PHN. Yet their quality has been rated equally well, using current standard quality rating tools.

CONCLUSION

Researchers and decision makers should be aware of potential sponsorship bias in health economic evaluations, especially in the way source data are used to specify base-case values and uncertainty ranges.

Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015)

Background

Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.

Methods

We systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening.

Results

We identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but combined applications are still sparse. The amount of missing information on model characteristics and study design is remarkable.

Conclusions

IBMs are suited to combine heterogeneous within- and between-host interactions, which offers many opportunities, especially to analyze targeted interventions for endemic infections. We advocate the exchange of (open-source) platforms and stress the need for consistent “branding”. Using (existing) conventions and reporting protocols would stimulate cross-fertilization between research groups and fields, and ultimately policy making in decades to come.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2699-8) contains supplementary material, which is available to authorized users.

Behavioural change models for infectious disease transmission: a systematic review (2010-2015)

We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010-2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process.