Maternal immunisation against Group B Streptococcus: A global analysis of health impact and cost-effectiveness.

BACKGROUND: Group B Streptococcus (GBS) can cause invasive disease (iGBS) in young infants, typically presenting as sepsis or meningitis, and is also associated with stillbirth and preterm birth. GBS vaccines are under development, but their potential health impact and cost-effectiveness have not been assessed globally. METHODS AND FINDINGS: We assessed the health impact and value (using net monetary benefit (NMB), which measures both health and economic effects of vaccination into monetary units) of GBS maternal vaccination in an annual cohort of 140 million pregnant women across 183 countries in 2020. Our analysis uses a decision tree model, incorporating risks of GBS-related health outcomes from an existing Bayesian disease burden model. We extrapolated country-specific GBS-related healthcare costs using data from a previous systematic review and calculated quality-adjusted life years (QALYs) lost due to infant mortality and long-term disability. We assumed 80% vaccine efficacy against iGBS and stillbirth, following the WHO Preferred Product Characteristics, and coverage based on the proportion of pregnant women receiving at least 4 antenatal visits. One dose was assumed to cost $50 in high-income countries, $15 in upper-middle income countries, and $3.50 in low-/lower-middle-income countries. We estimated NMB using alternative normative assumptions that may be adopted by policymakers. Vaccinating pregnant women could avert 127,000 (95% uncertainty range 63,300 to 248,000) early-onset and 87,300 (38,100 to 209,000) late-onset infant iGBS cases, 31,100 deaths (14,400 to 66,400), 17,900 (6,380 to 49,900) cases of moderate and severe neurodevelopmental impairment, and 23,000 (10,000 to 56,400) stillbirths. A vaccine effective against GBS-associated prematurity might also avert 185,000 (13,500 to 407,000) preterm births. Globally, a 1-dose vaccine programme could cost $1.7 billion but save $385 million in healthcare costs. Estimated global NMB ranged from $1.1 billion ($-0.2 to 3.8 billion) under the least favourable normative assumptions to $17 billion ($9.1 to 31 billion) under the most favourable normative assumptions. The main limitation of our analysis was the scarcity of data to inform some of the model parameters such as those governing health-related quality of life and long-term costs from disability, and how these parameters may vary across country contexts. CONCLUSIONS: In this study, we found that maternal GBS vaccination could have a large impact on infant morbidity and mortality. Globally, a GBS maternal vaccine at reasonable prices is likely to be a cost-effective intervention.

Correspondence to: Estimating the full health and economic benefits of current and future influenza vaccines.

We recently published an article in BMC Medicine looking at the potential health and economic impact of paediatric vaccination using next-generation influenza vaccines in Kenya: a modelling study. In their commentary on our article, Lafond et al. highlight the potential importance of the wider benefits of vaccination on cost-effectiveness. Whilst we agree with many points raised in the commentary, we think it raises further interesting discussion points, specifically around model complexity, model assumptions and data availability. These points are both relevant to this manuscript but have wider implications for vaccine cost-effectiveness studies.

Potential health and economic impact of paediatric vaccination using next-generation influenza vaccines in Kenya: a modelling study.

BACKGROUND: Influenza is a major year-round cause of respiratory illness in Kenya, particularly in children under 5. Current influenza vaccines result in short-term, strain-specific immunity and were found in a previous study not to be cost-effective in Kenya. However, next-generation vaccines are in development that may have a greater impact and cost-effectiveness profile. METHODS: We expanded a model previously used to evaluate the cost-effectiveness of seasonal influenza vaccines in Kenya to include next-generation vaccines by allowing for enhanced vaccine characteristics and multi-annual immunity. We specifically examined vaccinating children under 5 years of age with improved vaccines, evaluating vaccines with combinations of increased vaccine effectiveness, cross-protection between strains (breadth) and duration of immunity. We evaluated cost-effectiveness using incremental cost-effectiveness ratios (ICERs) and incremental net monetary benefits (INMBs) for a range of values for the willingness-to-pay (WTP) per DALY averted. Finally, we estimated threshold per-dose vaccine prices at which vaccination becomes cost-effective. RESULTS: Next-generation vaccines can be cost-effective, dependent on the vaccine characteristics and assumed WTP thresholds. Universal vaccines (assumed to provide long-term and broad immunity) are most cost-effective in Kenya across three of four WTP thresholds evaluated, with the lowest median value of ICER per DALY averted ($263, 95% Credible Interval (CrI): $ - 1698, $1061) and the highest median INMBs. At a WTP of $623, universal vaccines are cost-effective at or below a median price of $5.16 per dose (95% CrI: $0.94, $18.57). We also show that the assumed mechanism underlying infection-derived immunity strongly impacts vaccine outcomes. CONCLUSIONS: This evaluation provides evidence for country-level decision makers about future next-generation vaccine introduction, as well as global research funders about the potential market for these vaccines. Next-generation vaccines may offer a cost-effective intervention to reduce influenza burden in low-income countries with year-round seasonality like Kenya.

Assessing the impacts of COVID-19 vaccination programme's timing and speed on health benefits, cost-effectiveness, and relative affordability in 27 African countries.

BACKGROUND: The COVID-19 vaccine supply shortage in 2021 constrained roll-out efforts in Africa while populations experienced waves of epidemics. As supply improves, a key question is whether vaccination remains an impactful and cost-effective strategy given changes in the timing of implementation. METHODS: We assessed the impact of vaccination programme timing using an epidemiological and economic model. We fitted an age-specific dynamic transmission model to reported COVID-19 deaths in 27 African countries to approximate existing immunity resulting from infection before substantial vaccine roll-out. We then projected health outcomes (from symptomatic cases to overall disability-adjusted life years (DALYs) averted) for different programme start dates (01 January to 01 December 2021, n = 12) and roll-out rates (slow, medium, fast; 275, 826, and 2066 doses/million population-day, respectively) for viral vector and mRNA vaccines by the end of 2022. Roll-out rates used were derived from observed uptake trajectories in this region. Vaccination programmes were assumed to prioritise those above 60 years before other adults. We collected data on vaccine delivery costs, calculated incremental cost-effectiveness ratios (ICERs) compared to no vaccine use, and compared these ICERs to GDP per capita. We additionally calculated a relative affordability measure of vaccination programmes to assess potential nonmarginal budget impacts. RESULTS: Vaccination programmes with early start dates yielded the most health benefits and lowest ICERs compared to those with late starts. While producing the most health benefits, fast vaccine roll-out did not always result in the lowest ICERs. The highest marginal effectiveness within vaccination programmes was found among older adults. High country income groups, high proportions of populations over 60 years or non-susceptible at the start of vaccination programmes are associated with low ICERs relative to GDP per capita. Most vaccination programmes with small ICERs relative to GDP per capita were also relatively affordable. CONCLUSION: Although ICERs increased significantly as vaccination programmes were delayed, programmes starting late in 2021 may still generate low ICERs and manageable affordability measures. Looking forward, lower vaccine purchasing costs and vaccines with improved efficacies can help increase the economic value of COVID-19 vaccination programmes.

Quantifying the Acute Care Costs of Neonatal Bacterial Sepsis and Meningitis in Mozambique and South Africa.

BACKGROUND: Sepsis and meningitis are among the leading causes of neonatal deaths in sub-Saharan Africa (SSA). Neonatal sepsis caused ~400 000 deaths globally in 2015, half occurring in Africa. Despite this, there are few published data on the acute costs of neonatal sepsis or meningitis, with none in SSA. METHODS: We enrolled neonates admitted to 2 hospitals in South Africa and Mozambique between 16 April 2020 and 1 April 2021. In South Africa all cases were microbiologically confirmed, but in Mozambique both clinically suspected and microbiologically confirmed cases were included. Data were collected on healthcare resource use and length of stay, along with information on household expenditure and caregiving. We used unit costs of healthcare resources in local currencies to estimate healthcare provider costs per patient and costs per household. Results were converted to 2019 international dollars (I$). RESULTS: We enrolled 11 neonates in Mozambique and 18 neonates in South Africa. Mean length of stay was 10 days (median, 9 [interquartile range {IQR}, 4-14) and 16 days (median, 15 [IQR, 13-18]), respectively. In Mozambique we estimated mean household costs of I$49.62 (median, 10.19 [IQR, 5.10-95.12]) and hospitalization costs of I$307.58 (median, 275.12 [IQR, 149.43-386.12]). In South Africa these costs were I$52.31 (median, 30.82 [IQR, 19.25-73.08]) and I$684.06 (median, 653.62 [IQR, 543.33-827.53]), respectively. CONCLUSIONS: We found substantial costs associated with acute neonatal bacterial (all-cause) sepsis and meningitis in SSA. Our estimates will inform economic evaluations of interventions to prevent neonatal invasive bacterial infections.

Prematurity Modifies the Risk of Long-term Neurodevelopmental Impairments After Invasive Group B Streptococcus Infections During Infancy in Denmark and the Netherlands.

BACKGROUND: Preterm birth and neonatal infections are both associated with mortality and long-term neurodevelopmental impairments (NDIs). We examined whether the effect of invasive group B Streptococcus disease (iGBS) on mortality and long-term NDI differs for preterm and term infants, and whether co-occurrence of iGBS and prematurity leads to worse outcome. METHODS: Nationwide cohort studies of children with a history of iGBS were conducted using Danish and Dutch medical databases. Comparison cohorts of children without iGBS were matched on birth year/month, sex, and gestational age. Effects of iGBS on all-cause mortality and NDI were analyzed using Cox proportional hazards and logistic regression. Effect modification by prematurity was evaluated on additive and multiplicative scales. RESULTS: We identified 487 preterm and 1642 term children with a history of iGBS and 21 172 matched comparators. Dutch preterm children exposed to iGBS had the highest mortality rate by 3 months of age (671/1000 [95% CI, 412-929/1000] person-years). Approximately 30% of this mortality rate could be due to the common effect of iGBS and prematurity. Preterm children with iGBS had the highest NDI risk (8.8% in Denmark, 9.0% in the Netherlands). Of this NDI risk 36% (Denmark) and 60% (the Netherlands) might be due to the combined effect of iGBS and prematurity. CONCLUSIONS: Prematurity is associated with iGBS development. Our study shows that it also negatively impacts outcomes of children who survive iGBS. Preterm infants would benefit from additional approaches to prevent maternal GBS colonization, as this decreases risk of both preterm birth and iGBS.

Correction: COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness.

[This corrects the article DOI: 10.1371/journal.pmed.1003815.].

Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods.

Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary.

COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness.

BACKGROUND: Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). METHODS AND FINDINGS: We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. CONCLUSIONS: COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries.

SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study.

BACKGROUND: The COVID-19 pandemic has disrupted the delivery of immunisation services globally. Many countries have postponed vaccination campaigns out of concern about infection risks to the staff delivering vaccination, the children being vaccinated, and their families. The World Health Organization recommends considering both the benefit of preventive campaigns and the risk of SARS-CoV-2 transmission when making decisions about campaigns during COVID-19 outbreaks, but there has been little quantification of the risks. METHODS: We modelled excess SARS-CoV-2 infection risk to vaccinators, vaccinees, and their caregivers resulting from vaccination campaigns delivered during a COVID-19 epidemic. Our model used population age structure and contact patterns from three exemplar countries (Burkina Faso, Ethiopia, and Brazil). It combined an existing compartmental transmission model of an underlying COVID-19 epidemic with a Reed-Frost model of SARS-CoV-2 infection risk to vaccinators and vaccinees. We explored how excess risk depends on key parameters governing SARS-CoV-2 transmissibility, and aspects of campaign delivery such as campaign duration, number of vaccinations, and effectiveness of personal protective equipment (PPE) and symptomatic screening. RESULTS: Infection risks differ considerably depending on the circumstances in which vaccination campaigns are conducted. A campaign conducted at the peak of a SARS-CoV-2 epidemic with high prevalence and without special infection mitigation measures could increase absolute infection risk by 32 to 45% for vaccinators and 0.3 to 0.5% for vaccinees and caregivers. However, these risks could be reduced to 3.6 to 5.3% and 0.1 to 0.2% respectively by use of PPE that reduces transmission by 90% (as might be achieved with N95 respirators or high-quality surgical masks) and symptomatic screening. CONCLUSIONS: SARS-CoV-2 infection risks to vaccinators, vaccinees, and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate risk mitigation measures for vaccination campaigns held during SARS-CoV-2 epidemics, rather than cancelling them entirely.

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

BACKGROUND: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient's "bed pathway" - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. METHODS: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. RESULTS: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: "Ward, CC, Ward", "Ward, CC", "CC" and "CC, Ward". Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. CONCLUSIONS: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. TRIAL REGISTRATION: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.

COVID-19 length of hospital stay: a systematic review and data synthesis.

BACKGROUND: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care. METHODS: We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community. RESULTS: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date. CONCLUSION: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.

Timing of exposure assessment in studies on Group B streptococcus colonization and preterm birth.

BACKGROUND: Maternal colonization by the bacterium Group B streptococcus (GBS) increases risk of preterm birth, a condition that has an important impact on the health of children. However, research studies that quantify the effect of GBS colonization on preterm birth have reported variable estimates of the effect measure. METHODS: We performed a simulated cohort study of pregnant women to assess how timing of exposure (GBS colonization) assessment might influence results of studies that address this question. We used published data on longitudinal maternal GBS colonization and on the distribution of preterm births by gestational age to inform parameters used in the simulations. RESULTS: Assuming that the probability of preterm birth is higher during weeks when pregnant women are colonized by GBS, our results suggest that studies that assess exposure status early during pregnancy are more likely to estimate an association between GBS colonization and preterm birth that is closer to the null, compared with studies that assess exposure either at birth or during gestational weeks matched to preterm births. In sensitivity analyses assuming different colonization acquisition rates and diagnostic sensitivities, we observed similar results. CONCLUSIONS: Accurate quantification of the effect of maternal GBS colonization on the risk of preterm birth is necessary to understand the full health burden linked to this bacterium. In this study, we investigated one possible explanation, related to the timing of exposure assessment, for the variable findings of previous observational studies. Our findings will inform future research on this question.

Cost-effectiveness analysis of maternal vaccination against Group B streptococcus in Japan.

Background: Group B Streptococcus (GBS) is a leading pathogen causing life-threatening bacterial infections in neonates (early- or late-onset) and infants, and is associated with preterm and stillbirth. Japan introduced national guidelines to reduce early-onset neonatal GBS disease, with universal prenatal screening and intrapartum antimicrobial prophylaxis (IAP). However, screening/IAP does not prevent GBS associated late-onset disease, preterm or stillbirth. Maternal GBS vaccines in development are targeted at infant GBS disease but may provide benefit across perinatal outcomes. We aimed to assess cost-effectiveness of a future maternal GBS vaccine, for a base case prevention of infant GBS disease in combination with screening/IAP compared to screening/IAP alone. Methods: We used a decision tree model to estimate cases of infant GBS disease, deaths, and neuro-developmental impairment (NDI), GBS-related stillbirths, and the associated costs and loss in Quality-Adjusted Life Years (QALYs). We calculate the threshold price at which a vaccine would be cost-effective assuming a cost-effectiveness threshold of ¥5 million/QALY. We explored the potential benefit of a maternal GBS vaccine that also prevents preterm birth in a scenario analysis. Results: Maternal GBS vaccination in Japan could prevent an additional 142 infant GBS cases annually, including 5 deaths and 21 cases of NDI, and 13 stillbirths compared to screening/IAP alone. The incremental cost-effectiveness ratio (ICER) was ¥3.78 million/QALY with a vaccine cost of ¥5,000/dose. If the QALY lost for stillbirth is included, the ICER is reduced to ¥1.78 million/QALY. Median threshold vaccine price was ¥6,900 per dose (95 % uncertainty interval ¥5,100 to ¥9,200 per dose). If maternal GBS vaccination also prevented half of GBS-associated preterm, the ICER would be reduced to ¥1.88 million/QALY. Conclusions: An effective maternal GBS vaccine is likely to be considered cost-effective in Japan at a price of ¥5,000/dose. Effectiveness against other adverse perinatal outcomes would increase health benefits and cost-effectiveness.

The potential cost-effectiveness of next generation influenza vaccines in England and Wales: A modelling analysis.

Next generation influenza vaccines are in development and have the potential for widespread health and economic benefits. Determining the potential health and economic impact for these vaccines is needed to drive investment in bringing these vaccines to the market, and to inform which groups public health policies on influenza vaccination should target. We used a mathematical modelling approach to estimate the epidemiological impact and cost-effectiveness of next generation influenza vaccines in England and Wales. We used data from an existing fitted model, and evaluated new vaccines with different characteristics ranging from improved vaccines with increased efficacy duration and breadth of protection, to universal vaccines, defined in line with the World Health Organisation (WHO) Preferred Product Characteristics (PPC). We calculated the cost effectiveness of new vaccines in comparison to the current seasonal vaccination programme. We calculated and compared the Incremental Cost-Effectiveness Ratio and Incremental Net Monetary Benefit for each new vaccine type. All analysis was conducted in R. We show that next generation influenza vaccines may result in a 21% to 77% reduction in influenza infections, dependent on vaccine characteristics. Our economic modelling shows that using any of these next generation vaccines at 2019 coverage levels would be highly cost-effective at a willingness to pay threshold of £20,000 for a range of vaccine prices. The vaccine threshold price for the best next generation vaccines in £-2019 is £230 (95%CrI £192 - £269) per dose, but even minimally-improved influenza vaccines could be priced at £18 (95%CrI £16 - £21) per dose and still remain cost-effective. This evaluation demonstrates the promise of next generation influenza vaccines for impact on influenza epidemics, and likely cost-effectiveness profiles. We have provided evidence towards a full value of vaccines assessment which bolsters the investment case for development and roll-out of next-generation influenza vaccines.

Health effects of routine measles vaccination and supplementary immunisation activities in 14 high-burden countries: a Dynamic Measles Immunization Calculation Engine (DynaMICE) modelling study.

BACKGROUND: WHO recommends at least 95% population coverage with two doses of measles-containing vaccine (MCV). Most countries worldwide use routine services to offer a first dose of measles-containing vaccine (MCV1) and later, a second dose of measles-containing vaccine (MCV2). Many countries worldwide conduct supplementary immunisation activities (SIAs), offering vaccination to all people in a specific age range irrespective of previous vaccination history. We aimed to estimate the relative effects of each dose and delivery route in 14 countries with high measles burden. METHODS: We used an age-structured compartmental dynamic model, the Dynamic Measles Immunization Calculation Engine (DynaMICE), to assess the effects of different vaccination strategies on measles susceptibility and burden during 2000-20 in 14 countries with high measles incidence (containing 53% of the global birth cohort and 78% of the global measles burden). Country-specific routine MCV1 and MCV2 coverage data during 1980-2020 were obtained from the WHO and UNICEF Estimates of National Immunization Coverage database for all modelled countries and SIA data were obtained from the WHO summary of measles and rubella SIAs. We estimated the incremental health effects of different vaccination strategies using prevented cases of measles and deaths from measles and their efficiency using the incremental number needed to vaccinate (NNV) to prevent an additional measles case. FINDINGS: Compared with no vaccination, MCV1 implementation was estimated to have prevented 824 million cases of measles and 9·6 million deaths from measles, with a median NNV of 1·41 (IQR 1·35-1·44). Adding routine MCV2 to MCV1 was estimated to have prevented 108 million cases and 404 270 deaths, whereas adding SIAs to MCV1 was estimated to have prevented 256 million cases and 4·4 million deaths. Despite larger incremental effects, adding SIAs to MCV1 (median incremental NNV 6·02, 5·30-7·68) showed reduced efficiency compared with adding routine MCV2 (5·41, 4·76-6·11). INTERPRETATION: Vaccination strategies, including non-selective SIAs, reach a greater proportion of children who are unvaccinated and reduce measles burden more than MCV2 alone, but efficiency is lower because of the wide age range targeted by SIAs. This analysis provides information to help improve the health effects and efficiency of measles vaccination strategies. The interplay between MCV1, MCV2, and SIAs should be considered when planning future measles vaccination strategies. FUNDING: Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

Vaccine value profile for Group B streptococcus.

Group B streptococcus (GBS) is a major global cause of neonatal meningitis, sepsis and pneumonia, with an estimated 91,000 infant deaths per year and an additional 46,000 stillbirths. GBS infection in pregnancy is also associated with adverse maternal outcomes and preterm births. As such, the World Health Organization (WHO) prioritised the development of a GBS vaccine suitable for use in pregnant women and use in LMICs, where the burden of disease is highest. Several GBS vaccines are in clinical development. The WHO Defeating Meningitis by 2030 has set a target of 2026 for vaccine licensure. This 'Vaccine Value Profile' (VVP) for GBS is intended to provide a high-level, holistic assessment of the information and data that are currently available to inform the potential public health, economic and societal value of pipeline vaccines and vaccine-like products. This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public private partnerships and multi-lateral organizations, and in collaboration with stakeholders from the WHO regions of AFR, AMR, EUR, WPR. All contributors have extensive expertise on various elements of the GBS VVP and collectively aimed to identify current research and knowledge gaps. The VVP was developed using only existing and publicly available information.

What, how and who: Cost-effectiveness analyses of COVID-19 vaccination to inform key policies in Nigeria.

While safe and efficacious COVID-19 vaccines have achieved high coverage in high-income settings, roll-out remains slow in sub-Saharan Africa. By April 2022, Nigeria, a country of over 200 million people, had only distributed 34 million doses. To ensure the optimal use of health resources, cost-effectiveness analyses can inform key policy questions in the health technology assessment process. We carried out several cost-effectiveness analyses exploring different COVID-19 vaccination scenarios in Nigeria. In consultation with Nigerian stakeholders, we addressed three key questions: what vaccines to buy, how to deliver them and what age groups to target. We combined an epidemiological model of virus transmission parameterised with Nigeria specific data with a costing model that incorporated local resource use assumptions and prices, both for vaccine delivery as well as costs associated with care and treatment of COVID-19. Scenarios of vaccination were compared with no vaccination. Incremental cost-effectiveness ratios were estimated in terms of costs per disability-adjusted life years averted and compared to commonly used cost-effectiveness ratios. Viral vector vaccines are cost-effective (or cost saving), particularly when targeting older adults. Despite higher efficacy, vaccines employing mRNA technologies are less cost-effective due to high current dose prices. The method of delivery of vaccines makes little difference to the cost-effectiveness of the vaccine. COVID-19 vaccines can be highly effective and cost-effective (as well as cost-saving), although an important determinant of the latter is the price per dose and the age groups prioritised for vaccination. From a health system perspective, viral vector vaccines may represent most cost-effective choices for Nigeria, although this may change with price negotiation.

Short-term and long-term risk of mortality and neurodevelopmental impairments after bacterial meningitis during infancy in children in Denmark and the Netherlands: a nationwide matched cohort study.

BACKGROUND: Few studies have reported the long-term consequences of bacterial meningitis during infancy, and studies that have been done usually do not include a comparison cohort. We aimed to assess short-term and long-term risk of mortality, neurodevelopmental impairment (NDI), and health-care use and household income in cohorts of children with and without a history of bacterial meningitis during infancy in Denmark and the Netherlands. METHODS: In this nationwide cohort study, infants with a history of bacterial meningitis before age 1 year were identified through the Danish Medical Birth Registry and Danish National Patient Registry using International Classification of Diseases (ICD)-10 codes and through the Netherlands Reference Laboratory for Bacterial Meningitis. Infants were matched (1:10) by sex and birth month and year to a comparison cohort of the general population without a history of bacterial meningitis. We analysed mortality using Cox proportional hazards regression. In Denmark, diagnoses of NDIs were based on ICD-10 codes; in the Netherlands, special educational needs were used as a functional NDI outcome. Risk ratios (RRs) of NDIs were estimated using modified Poisson regression. We also analysed long-term health-care use in Denmark and household income in both countries. All regression analyses were adjusted for sex and year of birth, and stratified by pathogen whenever sample size allowed. FINDINGS: We included 2216 children with a history of bacterial meningitis (570 [25·7%] in Denmark between Jan 1, 1997, and Dec 31, 2018, and 1646 [74·3%] in the Netherlands between Jan 1, 1995, and Dec 31, 2018), matched to 22 127 comparison cohort members. Median age at diagnosis was 2·8 months (IQR 0·4-7·1) in Denmark and 4·3 months (0·7-7·4) in the Netherlands. Mortality risks within 3 months after disease onset were 3·9% (95% CI 2·6-5·8%) in Denmark and 5·9% (4·7-7·0) in the Netherlands, compared with 0·0% (p<0·0001) and 0·1% (p<0·0001) in the comparison cohorts. Survivors had an increased risk of moderate or severe NDIs at age 10 years (RR 5·0 [95% CI 3·5-7·1] in Denmark and 4·9 [4·0-6·2] in the Netherlands) compared to children in the comparison cohort, particularly after pneumococcal and group B streptococcal meningitis. In Denmark, a history of bacterial meningitis was associated with increased health-care use in the 10 years following diagnosis (rate ratio 4·5 [95% CI 3·9-5·2] for outpatient visits and 4·1 [3·6-4·7] for hospital admissions). INTERPRETATION: Our study shows increased risk of mortality in the short and long term, a five times increase in risk of NDIs, and increased health-care use after bacterial meningitis during infancy. Together with context-specific incidence data, our results can advance pathogen-specific estimation of the meningitis burden and inform service provision at the individual and population level. FUNDING: Bill & Melinda Gates Foundation, the Stichting Remmert Adriaan Laan Fonds, and the Netherlands Organisation for Health Research and Development.