{"paper_id":"00c9226e-5066-4733-9df0-1d5130858428","body_text":"1\n1 Title: Maternal immunisation against Group B Streptococcus: a global analysis of health impact and \n2 cost-effectiveness\n3\n4 Authors\n5 Simon R. Procter1,2*, Bronner P. Gonçalves1,2, Proma Paul1,2, Jaya Chandna1,2, Farah Seedat1,2, Artemis \n6 Koukounari1,2, Raymond Hutubessy3, Caroline Trotter4, Joy E Lawn1,2, Mark Jit1,5*\n7\n8 *Corresponding authors: simon.procter@lshtm.ac.uk; mark.jit@lshtm.ac.uk\n9\n10 Affiliations\n11 1. Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United \n12 Kingdom\n13 2. Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, \n14 London, United Kingdom\n15 3. Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland \n16 4. Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom\n17 5. School of Public Health, University of Hong Kong, Hong Kong SAR, China\n18\n19\n20\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n2\n21 Abstract \n22 Background\n23 Group B Streptococcus (GBS) can cause invasive disease (iGBS) in young infants, typically presenting \n24 as sepsis or meningitis, and is also associated with stillbirth and preterm birth. GBS vaccines are \n25 under development, but their potential health impact and cost-effectiveness have not been assessed \n26 globally. \n27\n28 Methods\n29 We assessed the health impact and value (using net monetary benefit, NMB, which measures both \n30 health and economic effects of vaccination into monetary units), of GBS maternal vaccination across \n31 183 countries in 2020. Our analysis uses a decision-tree model, combining risks of GBS-related \n32 outcomes from a Bayesian disease burden model with estimates of GBS related costs and Quality-\n33 Adjusted Life Years (QALYs) lost. We assumed 80% vaccine efficacy against iGBS and stillbirth, \n34 following the WHO Preferred Product Characteristics, and coverage based on the proportion of \n35 pregnant women receiving at least four antenatal visits. One dose was assumed to cost $50 in high-\n36 income countries, $15 in upper-middle income countries, and $3.50 in low-/lower-middle income \n37 countries. We estimated NMB using alternative normative assumptions that may be adopted by \n38 policy makers.\n39\n40 Findings\n41 Vaccinating pregnant women could avert 214,000 (95% uncertainty range 151,000 – 457,000) infant \n42 iGBS cases, 31,000 deaths (14,000 – 67,000), 21,000 (9,000 – 52,000) cases of neurodevelopmental \n43 impairment, and 23,000 (10,000 – 58,000) stillbirths. A vaccine effective against GBS-associated \n44 prematurity might also avert 172,000 (13,000 – 378,000) preterm births. Globally, a 1-dose vaccine \n45 programme could cost $1.7 billion but save $385 million in healthcare costs. Estimated global NMB \n46 ranged from $1.1 billion ($-0.2 – 3.8 billion) to $17 billion ($9.1 – 31 billion).\n47\n48 Interpretation\n49 Maternal GBS vaccination could have a large impact on infant morbidity and mortality globally and \n50 at reasonable prices is likely to be cost-effective.\n51\n52\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n3\n53 INTRODUCTION\n54 Streptococcus agalactiae, commonly known as Group B Streptococcus (GBS), is an important \n55 bacterial pathogen causing morbidity and mortality in pregnant women and their babies and is also \n56 increasingly recognised as a cause of disease in non-pregnant adults.1–3 Invasive GBS (iGBS) disease \n57 in neonates and young infants can result from maternal colonisation and vertical transmission or \n58 environmental exposure after birth. It is classified by age at onset with early-onset GBS (EOGBS) \n59 occurring in the first 6 days of life, and late-onset disease (LOGBS) occurring between ages 7 and 89 \n60 days, and typically presents as sepsis, meningitis, or pneumonia. In 2020, an estimated 20 million \n61 pregnant women globally were colonised with GBS resulting in 231,000 (114,000 – 455,000) cases of \n62 EOGBS and a further 162,000 (70,000 – 394,000) LOGBS cases.1 Together these were estimated to \n63 have caused 58,000 to 91,000 infant deaths depending on the assumptions made about mortality in \n64 cases without access to healthcare. Furthermore, survivors of iGBS are at risk of long-term \n65 neurological sequelae with an estimated 37,100 (14,600 – 96,200) surviving infants developing \n66 moderate or severe neuro-developmental impairment (NDI).1,4 Maternal colonisation with GBS is \n67 also an important cause of adverse pregnancy outcomes with an estimated 46,000 (20,000 – \n68 111,000) GBS stillbirths and is potentially linked with 518,000 (36,000 – 1,142,000) excess preterm \n69 births.\n70\n71 Currently the main strategies for preventing iGBS are based on intrapartum antibiotic prophylaxis \n72 (IAP). Many higher-income countries have reduced EOGBS incidence through IAP with eligible \n73 pregnant women identified either through risk-factor based screening or routine testing based on \n74 microbiological culture.5 Despite this success IAP has several limitations, notably it is not effective \n75 against LOGBS or GBS-associated stillbirths. In addition, the need for access to laboratory testing for \n76 microbiological screening based strategies, and the requirement to deliver antibiotics intravenously \n77 substantially limits the prospect of attaining high IAP coverage in many low-resource settings where \n78 the burden of iGBS is highest.5 There are also concerns that routine administration of antibiotics \n79 could contribute to antimicrobial resistance and might also have unintended impacts on the gut \n80 microbiota of newborns.6 Hence, there is substantial interest in alternative approaches to \n81 prevention.\n82\n83 Maternal immunisation is a potential alternative strategy whereby vertical transfer of antibodies in \n84 utero from a woman vaccinated during pregnancy affords protection to the mother, unborn foetus \n85 and newborn infant.7 Maternal immunisation with Tetanus Toxoid has been successfully used to \n86 reduce the burden of neonatal tetanus since the 1970s and, in the last decade, countries have been \n87 increasingly recommending routine vaccination of pregnant women against influenza and pertussis.8 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n4\n88 In 2015 development of a maternal vaccine against GBS was identified as a priority by the WHO \n89 Product Development for Vaccines Advisory Committee (PDVAC),9 and three GBS maternal vaccine \n90 candidates have progressed to Phase-2 clinical trials.10 In 2021, the licensure of an affordable GBS \n91 vaccine by 2026 was identified as a key milestone in the WHO global roadmap for Defeating \n92 Meningitis by 2030.11\n93\n94 There have been previous economic evaluations of maternal GBS vaccination in the United States,12–\n95 14 Europe,15–17 and Sub-Saharan Africa.18–20 However, none of these studies have estimated the value \n96 of GBS vaccination in all world regions. A global economic evaluation of GBS vaccination is important \n97 to drive investment into vaccine development by indicating the vaccine’s potential value in different \n98 markets. It would also enable financing and pricing mechanisms to be put in place for equitable \n99 access to the vaccine once it is available. Such an evaluation is central to a Full Value of Vaccines \n100 Assessment (FVVA), which WHO has identified as key to catalysing vaccine development and \n101 subsequent equitable access.21,22 To inform the WHO GBS vaccine FVVA,23 we conducted the first \n102 global economic evaluation of maternal GBS vaccination in 183 countries, drawing on recently \n103 updated global disease burden estimates for GBS.1\n104\n105 METHODS\n106 Model overview\n107 We developed a decision-tree model (Fig. 1) to assess the health impact and cost-effectiveness of \n108 maternal vaccination against GBS in an annual cohort of pregnant women and their babies for the \n109 year 2020 compared with current practice of no vaccination. The size of the cohort of women in \n110 each country was calculated by combining country-specific estimates of the number of births from \n111 the United Nations World Populations Prospects (UNWPP)24 together with the stillbirth risk from the \n112 WHO Global Health Observatory.25 Our analysis included the 183 countries out of 195 UN member \n113 states for which UNWPP birth data was available, which excludes countries with estimated \n114 populations below 90,000.\n115\n116 The health impact model structure was designed to reflect the natural history of pregnancy related \n117 GBS infections and was aligned with the modelling framework used in recently reported global \n118 estimates of GBS burden.1,26 The model first stratifies pregnant women based on GBS colonisation \n119 status, and then by whether pregnancy results in a live birth or stillbirth. Live births are further sub-\n120 divided into preterm and term births, with infants then at risk of developing either EOGBS or LOGBS; \n121 the risk of EOGBS amongst babies born to non-colonised mothers was assumed zero. Invasive GBS \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n5\n122 disease (EOGBS or LOGBS) may then result in death or, amongst survivors of GBS sepsis or \n123 meningitis, either full recovery or long-term neurodevelopmental impairment.\n124\n125 The analysis used the lifetime of babies as the analytical time-horizon with health costs and Quality \n126 Adjusted Life Years (QALYs) calculated over the lifetime of infant iGBS survivors using country-\n127 specific life expectancy at birth.24 The model was used to compare scenarios with vaccination plus \n128 current practice against current practice without vaccination (i.e. assuming no change in each \n129 country’s IAP policy following vaccine introduction). All analyses were performed using R version \n130 4.0.2. A Consolidated Heath Economic Evaluation Reporting Standards (CHEERS) checklist is provided \n131 in supplementary appendix 1. \n132\n133 Figure 1: Decision tree for GBS-related outcomes in children for an annual birth cohort in 183 countries \n134 comparing maternal vaccination against no vaccination (current standard of care) Numbered boxes \n135 represent repeated model structure, however the risks for some outcomes vary across repeated branches.\n136\n137 Disease risk\n138 Model inputs are summarised in supplementary appendix A2. We parameterised the probability of \n139 different GBS-related outcomes in our model using posterior samples of key epidemiological \n140 parameters from the global burden estimates reported by Gonçalves et al.1 We used country-specific \n141 estimates of the prevalence of maternal GBS colonisation and of the risk of EOGBS in infants born to \n142 colonised mothers. The risks of LOGBS were then calculated using region-specific estimates of the \nMother\nnot\ncolonised\nEOGBS\nLOGBS\nStillbirth\nMother\ncolonised\niGBS death\niGBS survivor\nSepsis\nMeningitis\nLivebirth\nTerm\nPreterm\nPregnant\nwomen per\ncountry\nNo iGBS\nNo NDI\nMild NDI\nMod. NDI\nSevere NDI\nNo NDI\nMild NDI\nMod. NDI\nSevere NDI\nMaternal vaccination\nNo vaccination\n1\n21\n2 3\n3 4\n4\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n6\n143 fraction of iGBS cases that are EOGBS vs LOGBS. Regional classifications were based on the United \n144 Nations (UN) Sustainable Development Goal (SDG) region definitions.27 \n145\n146 Case fatality risks (CFR) for EOGBS and LOGBS were also based on regional level estimates from \n147 Gonçalves et al. There are no data on CFRs for infants with EOGBS without access to care, so the \n148 authors considered two scenarios where they had either 90% CFR (following the approach of Seale \n149 and co-workers3) or the same CFR as other infants with EOGBS. In our analysis, we assumed in the \n150 base case that these infants had the same CFR as other infants with EOGBS, to be conservative about \n151 this highly uncertain parameter and because mothers of these children might also be less likely to \n152 receive maternal vaccines. \n153\n154 Among iGBS survivors the proportion of sepsis and meningitis, and the excess risk of mild, moderate, \n155 and severe NDI outcomes after meningitis were based on pooled global estimates, while NDI risks \n156 after sepsis were based on separate estimates for high-income and for low- and middle-income \n157 countries. The excess risk attributable to iGBS exposure was calculated assuming a counterfactual \n158 risk of mild or moderate and severe NDI amongst unexposed children from a large Danish cohort \n159 study.28  We based the proportion of moderate and severe NDI that was severe on the same study. \n160 Following the approach used in the burden estimation, our base case analysis included only the \n161 excess risk of moderate or severe NDI, which is likely to be more consistent across settings, but \n162 include mild NDI as a sensitivity analysis.1,4\n163\n164 To estimate country-specific GBS-associated stillbirth risk, national stillbirth estimates from the WHO \n165 Global Health Observatory25 were combined with regional estimates of the proportion of stillbirths \n166 caused by GBS.1 For the risk of GBS-associated prematurity we used national data on the proportion \n167 of preterm births29 together with the global odds ratio for the association between GBS maternal \n168 colonisation and preterm births.1 Further details on these calculations are provided in \n169 supplementary appendix A2.3 and A2.4.\n170\n171 Health Outcomes\n172 To calculate QALYs we assumed country-specific life-expectancy at birth for both normal births and \n173 survivors of iGBS. For term births we assumed no reduction in Health-Related Quality-of-Life \n174 (HRQoL), but for preterm births we applied a utility decrement over the child’s lifetime based on a \n175 systematic review and meta-analysis by Petrou et al.30 For the acute iGBS episode we approximated \n176 QALY loss assuming 29 days duration based on the average length-of-stay among studies in a recent \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n7\n177 systematic review of the acute costs of infant sepsis and meningitis,31 and applied health state utility \n178 decrements for hospitalisation with acute sepsis or meningitis from a US study in young children.32 \n179 For survivors with long-term sequelae, we applied utility decrements for mild, moderate, and severe \n180 NDI to each year of life and conservatively, given previous studies provide evidence of post-acute \n181 mortality after bacterial meningitis,33,34 assumed no change in life-expectancy. These utility values \n182 were based on a UK study, which assessed HRQoL in a cohort of children with NDI followed up at age \n183 11.35 \n184  \n185 Vaccination \n186 Although clinical studies have demonstrated immunogenicity of candidate GBS vaccines, to date \n187 there have been no phase-3 efficacy trials.10  We therefore based our assumptions about vaccine \n188 efficacy (VE) and other characteristics of a GBS vaccine on the WHO preferred product \n189 characteristics (PPCs).36 In our base case we assumed a single-dose vaccine with 80% efficacy against \n190 both infant iGBS disease and GBS-stillbirth across all GBS serotypes. We also assumed no effect on \n191 GBS-associated prematurity because (i) the WHO PPC does not specify that GBS vaccines must \n192 reduce colonisation, which is most likely pathway for preventing GBS-associated prematurity, and (ii) \n193 the association between GBS maternal colonisation and higher risk of prematurity may be \n194 confounded.37 It is likely that delivery of GBS vaccines will need to be timed in either the late second \n195 trimester or third trimester and could be delivered through existing routine antenatal care (ANC) \n196 services. Hence, we assumed vaccine coverage based on the proportion of pregnant women in each \n197 country who attend at least four ANC visits (ANC4).25\n198\n199 We also considered a range of alternative scenarios (supplementary table 4): higher vaccine \n200 coverage based on the proportion of women attending at least one ANC visit (ANC1); a two-dose \n201 regimen; lower and higher VE (60% and 90%); and a vaccine that is also effective against GBS-\n202 associated prematurity. For the latter scenario we estimated the proportion of preterm births that \n203 are potentially protected through vaccination by combining the distribution of preterm births by \n204 gestational age38 with the timing of vaccine visits based on country-specific ANC data39 \n205 (supplementary appendix A2.5). \n206\n207 Costs\n208 Our analysis was undertaken from a healthcare payer economic perspective, and all costs are \n209 reported in 2020 United States Dollars (USD). Where cost inputs were for different years they were \n210 inflated using the World Bank Gross Domestic Product (GDP) deflator.40 Costs reported in different \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n8\n211 currencies were then converted to 2020 USD using historical foreign exchange rates.41 To estimate \n212 acute healthcare costs, we combined one GBS-specific cost estimate from a study in the United \n213 Kingdom,42 with the findings from a systematic review on the acute costs of infant sepsis and \n214 meningitis43, and result of a recent study reporting the acute costs of neonatal bacterial sepsis and \n215 meningitis in Mozambique and South Africa.44 We used linear regression to extrapolate country-\n216 specific cost estimates using total per capita healthcare expenditure as a predictor (supplementary \n217 appendix A2.6.)  For long-term costs, no direct GBS-specific estimates exist in the literature. nnual \n218 costs amongst survivors with moderate and severe NDI were parameterised as a fixed proportion of \n219 between 4% and 28% of the acute cost estimate in each country, based on the range between a UK \n220 study of costs in children with NDI35 and a US study of costs in adults with disabilities.45\n221\n222 For the vaccine programme costs we extrapolated results from a systematic review of maternal \n223 vaccination delivery costs using regression against GDP per capita (supplementary appendix A2.7).31 \n224 We used previously estimated vaccine prices by World Bank country income group, which were \n225 based on a combination of price benchmarking against other vaccines and cost of goods analysis: \n226 $50 for high-income countries; $15 for upper-middle-income countries; and $3.50 for lower-middle-\n227 income and low-income countries.46\n228\n229 Normative assumptions\n230 A health intervention may be considered cost-effective if the cost per QALY gained falls below that \n231 country’s cost-effectiveness threshold. Here we use two commonly cited thresholds: (i) country \n232 gross domestic product per capita,47 (ii) published thresholds based on empirical estimates of the \n233 health opportunity cost of health care spending (supplementary appendix A2.8).48,49\n234\n235 A second normative assumption is the QALY loss attributed to a stillbirth. In many settings these are \n236 not assigned any health or disability weight, but it has been argued that they should be assigned a \n237 QALY loss close or the same as that of the death of a newborn.50 Here we consider two scenarios, \n238 one in which stillbirths are not assigned any QALY loss, and a second in which they are assigned the \n239 same QALY loss as the death of a newborn.\n240\n241 Following WHO guidelines, we discount costs at 3% and health effects at both 0% and 3% in \n242 alternative scenarios.51 Table 1 summarises the normative scenarios used.\n243\n244\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n9\n245 Table 1: Parameter values used for least and most favourable normative assumptions\nParameter Least favourable \nAssumptions\nMost favourable \nassumptions\n \nDiscount rate 3% for costs and benefits 3% for costs; 0% for benefits\nInclusion of stillbirth quality-\nadjusted life-years\nNot included Included\nCost-effectiveness threshold Based on empirical estimates* 1 x GDP per capita\n246 *Cost-effectiveness thresholds were based either on estimates from Ochalek et al. and Woods et al. See \n247 supplementary appendix A2.8 for more detail.\n248\n249 Economic analysis\n250 To assess the cost-effectiveness of GBS maternal vaccination compared to current practice, we \n251 follow a Net Monetary Benefit (NMB) approach in which both the health and fiscal benefits of \n252 vaccination are expressed in monetary units.52 To calculate the NMB the incremental benefits in \n253 QALYs are multiplied by a country-specific cost-effectiveness threshold (CET; either empirical or 1 x \n254 GDP per capita) in USD and then the incremental costs are subtracted. An intervention may be \n255 considered cost-effective if the NMB is positive, since this is mathematically equivalent to the \n256 incremental cost-effectiveness ratio (ICER) being less than the CET. In addition to NMB, we also \n257 estimated the threshold price per dose at which a GBS vaccine would be cost-effective in each \n258 country. \n259\n260 An advantage of adopting an NMB framework is that our estimates for individual countries can be \n261 directly combined to estimate the aggregate value of vaccination both regionally and globally. To \n262 account for parameter uncertainty, for each scenario we ran 4000 simulations per country and \n263 calculated the median and the 95% uncertainty range (UR) based on 2.5 and 97.5 percentiles of the \n264 simulations. At the country level we also calculated the probability maternal GBS vaccination was \n265 cost-effective (i.e., the proportion of simulations with NMB > 0).\n266\n267 Role of the funding source\n268 The funder of the study had no role in study design, data collection, data analysis, data \n269 interpretation, or writing of the report. \n270\n271 RESULTS\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n10\n272 We estimate that vaccinating 99.8 million pregnant women across 183 countries could cost $1.7 \n273 billion but could save around $300 million in acute healthcare costs and $85 million in long-term \n274 healthcare costs, although these estimates have wide uncertainty. Overall, the incremental cost of \n275 GBS vaccination is about $1.3 billion, with the biggest cost increase in Europe and Northern America \n276 (Table 2).\n277\n278 Globally, the vaccine programme could avert an estimated 127,000 (UR: 63,300 – 248,000) EOGBS \n279 cases and 87,300 (UR: 38,100 – 209,000) LOGBS cases, thus avoiding 31,100 (UR: 14,400 – 66,400) \n280 infant deaths and 17,900 (UR: 6,380 – 49,900) cases of moderate and severe NDI. Additionally, \n281 23,000 (UR: 10,000 – 56,400) GBS stillbirths could be prevented and, if a vaccine also proves \n282 effective against GBS associated prematurity, 185,000 (UR: 13,500 – 407,000) preterm births might \n283 be avoided. The highest burden of iGBS cases and deaths, around two-fifths of the total, is averted in \n284 Sub-Saharan Africa which accounts for about one-fifth of the women vaccinated. In contrast, only \n285 about 1% of the deaths occur in Europe and Northern America despite a tenth of vaccinated women \n286 being in this region.\n287\n288 Overall, iGBS cases averted through vaccination resulted in a projected gain of 2.5 million (UR: 1.2 – \n289 5.4 million) undiscounted QALYs, and a further 1.5 million (UR: 0.6 – 3.6 million) QALYs when \n290 avoided stillbirths are included. A vaccine that prevents GBS-associated prematurity could add \n291 another 0.8 million (UR: 0.1 – 2.1 million) QALYs. The relative contribution of preventing iGBS, \n292 stillbirths and prematurity to the overall QALY gain varies by region. For example, in Sub-Saharan \n293 Africa, and Northern Africa and Western Asia preventing iGBS contributes the majority of the QALY \n294 gain, but in Europe and Northern America, and Central and Southern Asia avoided stillbirths make a \n295 larger contribution. In Europe and Northern America preventing preterm births might result in larger \n296 QALY gains than iGBS cases and stillbirths combined.\n297\nDescription Central & \nSouthern Asia\nEastern & \nSouth-Eastern \nAsia\nEurope & \nNorthern \nAmerica\nLatin America & \nCaribbean\nNorthern Africa \n& Western Asia Oceania Sub-Saharan \nAfrica Global^\n         \nNumber of women vaccinated \n(millions)\n22.8 25.5 11.7 9.51 7.8 0.546 21.9 99.8\nVaccine programme costs \n(discounted; $ millions)\n124 \n(117, 136)\n470 \n(452, 495)\n648 \n(621, 687)\n173 \n(169, 178)\n127 \n(124, 131)\n24.4 \n(22.9, 26.6)\n107 \n(104, 112)\n1,680 \n(1,640, 1,720)\nAcute healthcare costs \n(discounted; $ millions)\n-7.93 \n(-17.4, -3.74)\n-54.6 \n(-119, -24.9)\n-155 \n(-352, -60.9)\n-21.4 \n(-47.5, -10.7)\n-27.8 \n(-56.9, -13.5)\n-3.89 \n(-8.87, -1.57)\n-14.3 \n(-30.5, -6.67)\n-298 \n(-534, -155)\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n11\nLong-term healthcare costs \n(discounted; $ millions)\n-2.95 \n(-11.3, -0.581)\n-19.8 \n(-79.2, -3.78)\n-33.2 \n(-117, -7.02)\n-8.13 \n(-31.1, -1.63)\n-10 \n(-36.6, -2.08)\n-0.871 \n(-2.97, -0.185)\n-4.85 \n(-18.6, -1.01)\n-86.5 \n(-252, -20.6)\nTotal incremental costs \n(discounted; $ millions)\n113 \n(96.6, 127)\n394 \n(286, 446)\n456 \n(200, 581)\n143 \n(99.5, 160)\n88.9 \n(39.5, 110)\n19.6 \n(13, 23.2)\n87.9 \n(60.6, 99.7)\n1,290 \n(948, 1,490)\nEOGBS cases \n(thousands)\n-22.8 \n(-43.6, -11.6)\n-30.6 \n(-62.4, -14.5)\n-3.37 \n(-5.94, -1.57)\n-8.91 \n(-16.8, -4.72)\n-17.9 \n(-36, -8.6)\n-0.421 \n(-0.86, -0.207)\n-42.3 \n(-86.4, -20.1)\n-127 \n(-248, -63.3)\nLOGBS cases \n(thousands)\n-11.3 \n(-33.1, -2.94)\n-15.2 \n(-45.7, -3.86)\n-1.99 \n(-4.2, -0.84)\n-5.9 \n(-20.4, -1.94)\n-12.9 \n(-33, -5.24)\n-0.275 \n(-1.39, -0.0888)\n-36.4 \n(-101, -14)\n-87.3 \n(-209, -38.1)\nModerate & severe NDI cases \n(thousands)\n-2.91 \n(-8.52, -0.933)\n-3.86 \n(-11.8, -1.21)\n-0.257 \n(-0.572, -0.0975)\n-1.31 \n(-3.99, -0.42)\n-2.63 \n(-7.58, -0.9)\n-0.0541 \n(-0.223, -0.0182)\n-6.66 \n(-19.4, -2.2)\n-17.9 \n(-49.9, -6.38)\nGBS deaths \n(thousands)\n-4.22 \n(-9.6, -1.78)\n-5.58 \n(-13.4, -2.32)\n-0.335 \n(-0.668, -0.148)\n-1.95 \n(-4.7, -0.804)\n-4.76 \n(-10.8, -2.06)\n-0.0836 \n(-0.336, -0.0242)\n-13.6 \n(-32.2, -5.65)\n-31.1 \n(-66.4, -14.4)\nGBS stillbirths \n(thousands)\n-6.59 \n(-23, -1.63)\n-3.13 \n(-10.9, -0.794)\n-0.586 \n(-1.48, -0.206)\n-1.34 \n(-8.35, -0.222)\n-1.33 \n(-3.12, -0.591)\n-0.0646 \n(-0.336, -0.0174)\n-9.31 \n(-18.5, -4.12)\n-23 \n(-56.4, -10)\nGBS associated preterm births* \n(thousands)\n-34.7 \n(-78.5, -2.33)\n-28.7 \n(-66.1, -2.05)\n-33.2 \n(-72, -2.4)\n-18.5 \n(-40.9, -1.37)\n-23.8 \n(-52.4, -1.81)\n-1.45 \n(-3.27, -0.103)\n-44.4 \n(-97.4, -3.23)\n-185 \n(-407, -13.5)\nQALYs from averted GBS \ndisease \n(discounted; thousands)\n150 \n(66.3, 339)\n203 \n(86.9, 485)\n12.5 \n(5.64, 24.8)\n70.2 \n(30.7, 168)\n164 \n(73, 371)\n2.96 \n(1.01, 10.6)\n431 \n(186, 1,010)\n1,060 \n(486, 2,270)\nQALYs from averted stillbirths \n(discounted; thousands)\n180 \n(43.7, 627)\n87.2 \n(21.7, 301)\n16.5 \n(5.77, 41.3)\n37.3 \n(6.18, 233)\n36.9 \n(16.3, 85.9)\n1.75 \n(0.474, 9.06)\n243 \n(108, 486)\n622 \n(271, 1,550)\nQALYs from averted preterm \nbirths* \n(discounted; thousands)\n63.6 \n(5.01, 162)\n53.8 \n(4.24, 143)\n62.4 \n(4.99, 160)\n34.6 \n(2.77, 88.8)\n44.2 \n(3.58, 113)\n2.77 \n(0.213, 7.23)\n77.4 \n(6.26, 198)\n338 \n(27.6, 857)\nQALYs from averted GBS \ndisease \n(undiscounted; thousands)\n358 \n(158, 807)\n513 \n(220, 1,220)\n32.7 \n(14.6, 64.6)\n177 \n(77, 422)\n408 \n(181, 923)\n6.94 \n(2.46, 24.5)\n947 \n(407, 2,230)\n2,490 \n(1,160, 5,370)\nQALYs from averted stillbirths \n(undiscounted; thousands)\n429 \n(104, 1,490)\n218 \n(54.4, 752)\n42.7 \n(15, 107)\n94.1 \n(15.6, 586)\n91.4 \n(40.4, 213)\n4.19 \n(1.17, 20.9)\n532 \n(237, 1,060)\n1,460 \n(630, 3,670)\nQALYs from averted preterm \nbirths* \n(undiscounted; thousands)\n152 \n(12, 387)\n135 \n(10.7, 359)\n163 \n(13, 417)\n87.8 \n(7.03, 225)\n110 \n(8.91, 282)\n7.3 \n(0.56, 19)\n171 \n(13.8, 436)\n825 \n(67.4, 2,090)\nTable 2: Annual global and regional impact of GBS maternal vaccination compared with no vaccination for the year 2020\nAll values are reported to 3 significant figures. Values in brackets are 95% uncertainty ranges.\nGBS = Group B Streptococcus; EOGBS = Early-Onset GBS; LOGBS = Late-Onset GBS; NDI = Neurodevelopmental Impairment; QALY = Quality Adjust Life Year.\n*in scenario analysis where vaccine is assumed to have 80% VE against GBS associated prematurity\n^global median values do not exactly equal the sum of the regional median values\n298\n299 Using our base case assumptions about the vaccine characteristics the estimated global NMB of \n300 vaccination ranged from $1.1 billion (UR: $-0.2 – 3.9 billion) to $17 billion (UR: $9.1 – 31 billion) \n301 depending upon the normative assumptions (Fig. 2A). Including stillbirth QALYs increases the NMB \n302 by between $1.4 billion and $7.1 billion depending on the other normative assumptions made.\n303\n304 Under the most-favourable normative assumptions vaccination had a positive NMB in all regions \n305 (Fig. 2B). However, for least-favourable assumptions the NMB was negative for Central and Southern \n306 Asia, Europe and Northern America, and Oceania. Nevertheless, if stillbirth QALYs were included, the \n307 NMB for these regions was again positive (Supplementary Fig. 1).\n308\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n12\n309  \n310 Figure 2: Net Monetary Benefit of GBS maternal vaccination (A) globally under different normative \n311 assumptions (see Table 1); and (B) by region for the most and least favourable normative assumptions. \n312 Least-favourable normative assumptions were the use of an empirical CET, 3% discounting of QALYs, and \n313 exclusion of stillbirth QALYs. Most-favourable assumptions were the use of 1 x GDP per capita CETs, 0% \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n13\n314 discounting of QALYs, and inclusion of stillbirth QALYs. M = Millions; B = Billions; CET = Cost-Effectiveness \n315 Threshold; GDP = Gross Domestic Product; GDPPC = GDP per capita; QALY = Quality Adjusted Life Year; SB = \n316 Stillbirth; SDG = Sustainable Development Goal.\n317\n318 For the most-favourable normative assumptions vaccination is likely cost-effective in almost all \n319 countries (Fig 3.), but for least-favourable assumptions this was reduced to just over half (103/183) \n320 of countries. Notably, vaccination was less likely to be cost-effective amongst countries with lower \n321 GDP per capita within the Sub-Saharan Africa, Central & Southern Asia, and Europe & Northern \n322 America regions.\n323\n324325 Figure 3: Probability that GBS maternal vaccination is cost-effective in each country under most favourable \n326 and least favourable normative assumptions (see Table 1). Least-favourable normative assumptions were the \n327 use of an empirical CET, 3% discounting of QALYs, and exclusion of stillbirth QALYs. Most-favourable \n328 assumptions were the use of 1 x GDP per capita CETs, 0% discounting of QALYs, and inclusion of stillbirth \n329 QALYs. CET = Cost-Effectiveness Threshold; GDP = Gross Domestic Product; GDPPC = GDP per capita; QALY = \n330 Quality Adjusted Life Year; SB = Stillbirth; SDG = Sustainable Development Goal.\n331\n332 Figure 4 shows how the global NMB of vaccination varies under different scenarios. Inclusion of mild \n333 NDI, assuming GBS births without skilled birth attendants have 90% case-fatality or increasing \n334 vaccine efficacy from 80% to 90% slightly increase the global NMB of vaccination, while assuming \n335 zero long-term costs for NDI slightly decreases the NMB. However, none of these assumptions have \n336 a dramatic effect. If vaccine efficacy is decreased to 60%, global NMB remains positive under least-\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n14\n337 favourable assumptions, but the number of countries for which vaccination is no longer cost-\n338 effective increases to 96 (Supplementary Fig. 4). A vaccine that requires two doses to achieve 80% \n339 efficacy would have a negative global NMB, and vaccination would not be cost-effective in 111 \n340 countries. However, a vaccine with protection against preterm birth substantially increases the \n341 global NMB and is especially influential in the Europe & Northern America region (see \n342 Supplementary Fig. 2).\n343\n344345 Figure 4: Annual global Net Monetary Benefit of GBS maternal vaccination under most favourable and least \n346 favourable normative assumptions (see Table 1) for different vaccination scenarios. Points show median \n347 estimates and lines show 95% uncertainty ranges. Least-favourable normative assumptions were the use of an \n348 empirical CET, 3% discounting of QALYs, and exclusion of stillbirth QALYs. Most-favourable assumptions were \n349 the use of 1 x GDP per capita CETs, 0% discounting of QALYs, and inclusion of stillbirth QALYs. B = Billions; CET \n350 = Cost-Effectiveness Threshold; CFR = Case Fatality Risk; GDP = Gross Domestic Product; NDI = \n351 Neurodevelopmental Impairment; SBA = Skilled Birth Attendant; QALY = Quality Adjusted Life Year; VE = \n352 Vaccine Effectiveness.\n353\n354 The distribution of vaccine threshold prices amongst countries within each World Bank income \n355 group are shown in Figure 5 (results by SDG region are shown in Supplementary Fig. 5, and for other \n356 vaccine scenarios in Supplementary Fig. 6). The threshold price is usually positive (i.e., there is some \n357 price at which purchasing the vaccine would be cost-effective), and generally higher in high-income \n358 and upper-middle-income countries. However, under least-favourable normative assumptions \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n15\n359 threshold price is negative in eight countries, indicating that even with a free vaccine the delivery \n360 costs outweigh the health benefits in this analysis.\n361362 Figure 5: Distribution of GBS vaccine threshold prices amongst countries within each World Bank income \n363 group under most and least favourable normative assumptions (see Table 1). Threshold vaccine prices above \n364 $800 per dose are not shown. Least-favourable normative assumptions were the use of an empirical CET, 3% \n365 discounting of QALYs, and exclusion of stillbirth QALYs. Most-favourable assumptions were the use of 1 x GDP \n366 per capita CETs, 0% discounting of QALYs, and inclusion of stillbirth QALYs. CET = Cost-Effectiveness Threshold; \n367 GDP = Gross Domestic Product; QALY = Quality Adjusted Life Year.\n368\n369 DISCUSSION\n370 A high-coverage global maternal immunisation programme against GBS could avert hundreds of \n371 thousands of GBS cases, alongside tens of thousands of deaths, stillbirths, and cases of long-term \n372 disability. We estimate that such a programme may have a net cost of around $1.4 billion, with most \n373 costs occurring in Europe and Northern America. Nevertheless, it would be cost-effective in most \n374 countries under favourable assumptions, particularly if it can reduce preterm births. \n375\n376 Even under less favourable assumptions, a single-dose GBS vaccine could still be cost-effective due \n377 to additional factors we did not explore. In some high-income countries, GBS vaccination plus \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n16\n378 current practice may be less cost-effective compared to current practice alone because of lower GBS \n379 incidence in babies due to IAP. However, GBS vaccination might allow high-income countries to \n380 achieve additional cost savings by revising IAP algorithms for vaccinated mothers. In low- and lower-\n381 middle income countries, iGBS incidence may be higher, but so is the health opportunity cost of \n382 healthcare spending due to budget constraints leading to lower thresholds at which interventions \n383 may be considered cost-effective. \n384\n385 More competitive pricing may enable vaccination to be cost-effective, even under least favourable \n386 assumptions.  Competitive and finely tiered vaccine prices could also be beneficial for \n387 manufacturers, with financial analyses suggesting that high global demand is needed to ensure the \n388 development costs of a GBS vaccine to be recouped.46 Our economic evaluation can inform both \n389 manufacturers and donors investigating the financial viability of investing in GBS vaccine \n390 development, as well as countries identifying the price they should be willing to pay for such a \n391 vaccine.\n392\n393 Our study is the first to estimate the value of maternal GBS vaccination across all regions and \n394 country income groups. Previous analyses have estimated cost-effectiveness in the United States,12–\n395 14 the Netherlands,17 United Kingdom,15,16 South Africa,19 The Gambia,18  and 37 Gavi countries in \n396 Africa.20  These prior estimates suggested cost-effectiveness of vaccination ranged from $320-573 \n397 per DALY averted in Gavi-eligible countries,20 to $3550 per DALY averted in South Africa,19 to over \n398 $50,000 per QALY in the United States,12,13 which is broadly consistent with our results. Like our \n399 analysis, Kim et al. also found that the ability to avert GBS-associated prematurity greatly improved \n400 vaccine cost-effectiveness.19\n401\n402 This was the first cost-effectiveness study to use new global estimates of the health burden due to \n403 GBS including infant morbidity and mortality, long-term neurodevelopmental impairment, stillbirth, \n404 and GBS-associated prematurity. This burden study propagated parametric uncertainty \n405 comprehensively by using a Bayesian framework to synthesise existing data sources. Posterior \n406 distributions from the study then informed a probabilistic sensitivity analysis for our cost-\n407 effectiveness model. Similarly, for cost data, parameters with multiple sources of data from previous \n408 systematic reviews were synthesised using regression models. Conversely, the main limitations of \n409 our analysis reflected parameters with limited data such as those governing health-related quality of \n410 life and long-term costs from disability, where estimates were based on only 1-2 relevant studies. \n411 Our analysis also excluded the potential impact of vaccination on maternal morbidity and the costs \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n17\n412 of GBS-related disability beyond the health-sector. However, both these factors would likely \n413 reinforce our main findings on cost-effectiveness.\n414\n415 A further set of uncertainties govern GBS vaccine characteristics such as efficacy, number of doses \n416 needed and impact on GBS-associated prematurity. Since there is currently no licensed vaccine, \n417 these parameters were informed by the WHO PPC which is based on expert assumptions. We \n418 therefore used scenario sensitivity analyses to identify which of these characteristics are the most \n419 important drivers of vaccine value. Further data from carefully designed vaccine trials and other field \n420 studies are needed to inform these data gaps. Vaccine value is also driven by normative health \n421 economic assumptions around discounting, cost-effectiveness thresholds and the value of \n422 preventing stillbirths, which reflect uncertainty about the values of society rather than about \n423 empirical data.\n424\n425 Overall, our results suggest high coverage of a competitively priced maternal GBS vaccine has the \n426 potential to save tens of thousands of lives globally and is likely to be a cost-effective investment, \n427 particularly if the vaccine can reduce GBS-associated prematurity.\n428\n429 Contributors’ statement\n430 Conceptualisation – SRP, AK, JEL, and MJ; Methodology – SRP, BG, CT and MJ; Investigation – SRP; \n431 Formal Analysis – SRP; Software – SRP; Validation – SRP; Data Curation – SRP and BG; Writing – \n432 Original Draft – SRP and MJ; Writing – Review & Editing – SRP, BG, PP, JC, FS, AK, RH, CT, JEL and MJ; \n433 Visualisation – SRP; Supervision – MJ and JEL; Funding Acquisition – MJ and JEL.\n434\n435 Declaration of interests\n436 FS is employed by the UK NSC which developed the policy recommendation for maternal GBS \n437 screening.\n438\n439 Acknowledgements\n440 We would like to thank the authors of the GBS burden paper for sharing data on the posterior \n441 estimates of parameters in the burden model. We thank the GBS Full Value of Vaccine Assessment \n442 project Scientific Advisory Group for helpful discussion. We also thank Clint Pecenka and Ranju Baral \n443 for sharing estimates of antenatal care coverage by gestational age. This work was supported by a \n444 grant (INV-009018) to the London School of Hygiene & Tropical Medicine (PI Joy Lawn) from the Bill \n445 & Melinda Gates Foundation. RH is member of the WHO. The views expressed in this article are \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n18\n446 those of the authors and do not necessarily represent the decisions, official policy or opinions of the \n447 WHO. \n448\n449 Data sharing statement\n450 Code and data used in this analysis are available at https://github.com/mert0248/GBS-vax-econ-\n451 model\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted July 12, 2022. ; https://doi.org/10.1101/2022.07.11.22277482doi: medRxiv preprint \n\n19\n452 References\n453 1. Gonçalves BP, Procter SR, Paul P, Chandna J, Lewin A, Seedat F, et al. 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