lives saved with vaccination for 10 pathogens across 112 countries in a pre covid 19 CORD-Papers-2022-06-02 (Version 1)

Title: Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world
Abstract: BACKGROUND: Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b hepatitis B human papillomavirus Japanese encephalitis measles Neisseria meningitidis serogroup A rotavirus rubella Streptococcus pneumoniae and yellow fever over the years 20002030 across 112 countries. METHODS: Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. RESULTS: We estimate 97 (95%CrI[80 120]) million deaths would be averted due to vaccination activities over 20002030 with 50 (95%CrI[41 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030 we estimate 52 (95%CrI[41 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. CONCLUSIONS: This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. FUNDING: VIMC is jointly funded by Gavi the Vaccine Alliance and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortiums modelling groups (VIMC-funded institutions represented in this paper: Imperial College London London School of Hygiene and Tropical Medicine Oxford University Clinical Research Unit Public Health England Johns Hopkins University The Pennsylvania State University Center for Disease Analysis Foundation Kaiser Permanente Washington University of Cambridge University of Notre Dame Harvard University Conservatoire National des Arts et Mtiers Emory University National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH MJ XL SE-L JT KW NMF KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development which supported aspects of VIMC's work (MRC grant number: MR/R015600/1). JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation. This paper was compiled by all coauthors including two coauthors from Gavi. Other funders had no role in study design data collection data analysis data interpretation or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Published: 2021-07-13
Journal: eLife
DOI: 10.7554/elife.67635
DOI_URL: http://doi.org/10.7554/elife.67635
Author Name: Toor Jaspreet
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Author Name: Echeverria Londono Susy
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Author Name: Li Xiang
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Author Name: Abbas Kaja
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Author Name: Carter Emily D
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Author Name: Clapham Hannah E
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Author Name: Clark Andrew
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Author Name: de Villiers Margaret J
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Author Name: Eilertson Kirsten
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Author Name: Ferrari Matthew
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Author Name: Hallett Timothy B
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Author Name: Hinsley Wes R
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Author Name: Hogan Daniel
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Author Name: Huber John H
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Author Name: Jackson Michael L
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Author Name: Jean Kevin
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Author Name: Jit Mark
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Author Name: Karachaliou Andromachi
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Author Name: Klepac Petra
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Author Name: Kraay Alicia
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Author Name: Lessler Justin
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Author Name: Li Xi
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Author Name: Lopman Benjamin A
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Author Name: Mengistu Tewodaj
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Author Name: Metcalf C Jessica E
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Author Name: Moore Sean M
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Author Name: Nayagam Shevanthi
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Author Name: Papadopoulos Timos
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Author Name: Perkins T Alex
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Author Name: Portnoy Allison
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Author Name: Razavi Homie
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Author Name: Razavi Shearer Devin
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Author Name: Resch Stephen
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Author Name: Sanderson Colin
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Author Name: Sweet Steven
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Author Name: Tam Yvonne
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Author Name: Tanvir Hira
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Author Name: Tran Minh Quan
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Author Name: Trotter Caroline L
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Author Name: Truelove Shaun A
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Author Name: Vynnycky Emilia
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Author Name: Walker Neff
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Author Name: Winter Amy
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Author Name: Woodruff Kim
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Author Name: Ferguson Neil M
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Author Name: Gaythorpe Katy AM
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sha: 0ff733e4e6d6d92e7f9ba2241e9e91d2552c95e5
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Medline; PMC; WHO
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/https://www.who.int/
pubmed_id: 34253291
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/34253291
pmcid: PMC8277373
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277373
url: https://doi.org/10.7554/elife.67635 https://www.ncbi.nlm.nih.gov/pubmed/34253291/
has_full_text: TRUE
Keywords Extracted from Text Content: Neisseria meningitidis serogroup A Haemophilus influenzae type b Echeverria-Londono rotavirus human papillomavirus Streptococcus pneumoniae rubella https://doi.org/10.7554/eLife.67635 1 measles children BD 2021a] MCV2 Sindh province EPI swh:1:rev:0da13630968de0863f38294a1c234c5947baf97e 2-3 Merlin Varaine Hib pneumonia NPNM hepatocellular carcinoma f R Vaccine children cervical line per-contact re-vaccinate Eye Hib Immune Reactive mother LMICs Echeverria-Londono cross-pathogen VIMC-wide GVAP hepatitis B chest x-ray Excelbased HPV vaccine Herd 83:1 b 1 DTP1 measles dynaMICE IHME GBD 2019 infants Hib meningitis survivors Fangjun JEV infections Rotavirus vaccines 201910gavi -version 5 people humans Velázquez 0Â Á33 Geneva, 2005 non-primary infections pre-vaccine Consortium ( encephalitis virus Vaccine-induced fowl CHB HBsAg+ HBeAg-at Clermont IgG DTP Hib [ tenofovir Susceptible-Infected-Recovered (SIR beta Georgakopoulou LP DAAC NASA Burkina Faso Rubella Nicoara Rota [ measles Rota, V gavi73 HepB3 PAHO Encephalitis b 1;i HBsAg+ HBeAg-mothers non-human primates HPV-16/18 JE Figure 2 PSA Hib, measles 0Á26 b-PERT VPDs Liver Cancer HBeAg-negative NRI VIMC rotavirus vaccines FVP Longbottom 2021a 95%CrI[6.1 SIR Appendix 5-figure 3 hepatitis B virus Hib non-pneumonia/non-meningitis non-vaccine HPV DynaMICE Culex tritaeniorhynchus BAL Hib vaccine b S CrIs CLT hepatitis B core antigen hepatitis B. country-bycountry under-5s HBsAg+ HBeAg- serum bactericidal antibody Gavi individuals encephalitis Bill measles Pennsylvania Fetal Immune liver cancer RCV SARS-COV-2 vaccines focal RI light-touch HPV 16/18 HPV vaccines mothers http://primetool.org/ GSK 4-11 post-2030 95%CrI[0.47 SARS-COV-2 vaccine FOIs immune 'M ð1 þ acosð2ptÞÞ HBV vaccine Nigeria (Appendix 5- figure 7 Rota age/year Zgó rniak-Nowosielska JEV HepB DCC D bSÀfS NRI for Jit hosts'status Jackson CrI hepatitis B e antigen rice colonization/disease Infants RI-only ( Health Survey b R FVPs land Hadler WHO-UNICEF Neisseria meningitidis GAMS birth-dose Hasso-Agopsowicz HCC hepatitis B surface antigen rubella immunoglobulin G Finkenstadt UNICEF HBeAg+/ HBsAg+ people's Pol3 95%CrI[120 HBsAg 95%CrI[2.9 Papillomavirus Rapid Interface lockdown Tristan de Espino perspectives-either HBsAg+ BD vaccine cervical cancer e t campaign-based vaccinations b 2 WorldPop hepatitis Tristan de Espino, 1989 Appendix 5-figure 2 YFV b 0;i rotavirus vaccine rotavirus infections RI coverage/FVPs TAP Quaglio HBsAg+ HBeAg+ f S cancer HBV NRI years Y v HPV rubella WHO/UNICEF herd RCV1 RStan b a;j;t 1⁄4 b Lingani Liver a=2 VPD anti-HBc matrix rotavirus liver Prem NPIs Zeshan Chad rotavirus gastroenteritis Beta zero-dose children WHO-AFRO Vaccines UNWPP EndHep2030 1-5, 6-11, 12-23 human https://dhsprogram.com FVP S Non-routine Rota, RI GLO-BOCAN 2020 b 1 0:7b 2 0:7b 2 b 2 HBIG WUENIC low-viral Campagne b a;j hepatitis B vaccine WUENIC DTP zone UPHIA Gambia DTP3 PCV13 serotypes pre-COVID-19 NRI, D S AOM HBeAg contact matrix HepB-attributable Measles LVL S. pneumoniae Tartof pre-infectious infection/disease 95%CrI[4100 MACs Eric Mast non-vaccine NRI denotes non-routine immunisations Vynnycky GDP FVP R 95%CrI[5.9 E1⁄2Á cervical cancers MenAfriVac 2019a Chandir persons vimc98 age-contact women Appendix 5-figure 1 COVID-19 GHDx, 2019 serotypes RCV2 UNIVAC GBD 2019 measles/measles-rubella Congo HPV vaccine VIMC-wide FitzJohn Appendix 5-figure 2 HPV 2021a HepB persons FVPs measles
Extracted Text Content in Record: First 5000 Characters:Background: Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, Toor, Echeverria-Londono, Li, et al. eLife 2021;10:e67635. DOI: https://doi.org/10.7554/eLife.67635 1 of 63 RESEARCH ARTICLE rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Methods: Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. Results: We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. Conclusions: This study represents the largest assessment of vaccine impact before COVID-19related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. Vaccines play a vital role in immunising populations worldwide to provide protection against a wide range of diseases. In 1974, the World Health Organisation (WHO) launched the Expanded Programme on Immunisation (EPI) with a goal of universal access to all relevant vaccines for all at risk (Keja et al., 1988) . To further increase momentum on vaccine coverage, Gavi, the Vaccine Alliance, was created in 2000 with a goal of providing vaccines to save lives and protect people's health (Bill & Melinda Gates Foundation, 2020; Zerhouni, 2019) . Over the past two decades, vaccination programmes have expanded across low-and middle-income countries (LMICs), significantly reducing morbidity and mortality related to vaccine preventable diseases (VPDs). As of 2019, Gavi has helped immunise over 822 million children through routine programmes and provided over 1.1 billion vaccinations through campaigns in supported countries (Gavi, the Vaccine Alliance, 2019) . Despite this immense progress, almost one in five (15.2 million) children in Gavi-supported countries remain under-immunised with the third dose of the essential childhood vaccination containing diphtheriatetanus-pertussis vaccine (DTP3), 10.6 million of these children are zero-dose children, that is, having not received their first dose of DTP (Zerhouni, 2019) . The beneficial effect of vaccination programmes cannot be assessed directly as the counterfactual, that is, the situation without vaccination, cannot be observed. Hence, models of disease risk and the impact of vaccination activities play a vital role in assessing the current burden, examining the effect of previous activities and projecting the future situation. The Vaccine Impact Modelling estimates. Twenty-one mathematical models were used to inform the estimates with two models per pathogen (except HepB which has three models) thereby increasing robustness and capturing structural uncertainty within the analyses. There is substantial variation in modelling approach due to both the differences in pathogen dynamics and inherent uncertainties in modelling disease risk. The model characteristics vary in their type, from static cohort to transmission-dynamic models; their complexity, for example in their representation of age effects; and their calibration and validation methods. A brief overview of pathogens is provided in Table 1 with detailed model descriptions provided in Appendix 2.2 (HepB [Nayagam et al., 2016] , HPV [Goldie et al., 2008; Abbas et al., 2020b] , Hib [Clark et al., 2019a; Walker et al., 2013a] , JE [Quan et al., 2020] , Measles [Chen et al., 2012] , MenA [Karachaliou et al., 2015; Tartof et al., 2013] , PCV [Walker et al., 2013a; Clark et al., 2019a] , Rota [Pitzer et al., 2012; Clark et al., 2019a] , Rubella [Boulianne et al., 1995; Vynnycky et al., 2019] , YF [Gaythorpe et al., 2021a] ). Each modelling group provided estimates of age-stratified disease burden at national level for three scenarios: no vaccination, only routine vaccination (routine immunisations; RI) and, where appropriate, both RI and non-routine vaccination (non-routine immunisations; NRI, such as multi-age cohort vaccinations for HPV, and catch-up campaigns for measles). Disease burden was quantified in terms of deaths and DALYs. DALYs measure the years of healthy life lost due to premature death and disability from the disease, and are the sum of years of life lost (YLLs) through premature mortality and years lived with disability (YLDs). No discounting or weighting was applied in the calculation of DALYs. For rubella, only disease burden from congenital rubella syndrome (CRS) was included and the models differed in the inc
Keywords Extracted from PMC Text: Rota, RI 95%CrI[6.1 WHO/UNICEF zero-dose children EPI HepB-attributable CrIs 95%CrI[0.47 2000–2019 RI-only ( HepB Gavi Rota [ VPDs Figure 2 COVID-19 measles Pennsylvania human Streptococcus pneumoniae pre-COVID-19 measles Hib DTP children Vynnycky Vaccine 's rubella Measles MCV2 Appendix 5—figure 4 95%CrI[4100 GBD 2019 WUENIC Neisseria meningitidis serogroup A re-vaccinate people's tetanus HPV FVP coronavirus 2019 rotavirus Deghmane GVAP human papillomavirus FVPs Tartof 95%CrI[120 LMICs 2019a 2021a] hepatitis B (HepB VIMC-wide Appendix 5—figure 2 Bill Haemophilus influenzae type b (Hib Nigeria (Appendix 5—figure 7 Appendix 5—figure 9 Rota, CrI Echeverria-Londono Hib, measles DTP3 RI Vaccines encephalitis Rota 5—figure Appendix 5—figure 3 measles dynaMICE NRI for NPIs Rubella line UNWPP JE NRI post-2030 95%CrI[2.9 Hib [ GHDx, 2019 VIMC 95%CrI[5.9
Extracted PMC Text Content in Record: First 5000 Characters:Vaccines play a vital role in immunising populations worldwide to provide protection against a wide range of diseases. In 1974, the World Health Organisation (WHO) launched the Expanded Programme on Immunisation (EPI) with a goal of universal access to all relevant vaccines for all at risk (Keja et al., 1988). To further increase momentum on vaccine coverage, Gavi, the Vaccine Alliance, was created in 2000 with a goal of providing vaccines to save lives and protect people's health (Bill & Melinda Gates Foundation, 2020; Zerhouni, 2019). Over the past two decades, vaccination programmes have expanded across low- and middle-income countries (LMICs), significantly reducing morbidity and mortality related to vaccine preventable diseases (VPDs). As of 2019, Gavi has helped immunise over 822 million children through routine programmes and provided over 1.1 billion vaccinations through campaigns in supported countries (Gavi, the Vaccine Alliance, 2019). Despite this immense progress, almost one in five (15.2 million) children in Gavi-supported countries remain under-immunised with the third dose of the essential childhood vaccination containing diphtheria-tetanus-pertussis vaccine (DTP3), 10.6 million of these children are zero-dose children, that is, having not received their first dose of DTP (Zerhouni, 2019). The beneficial effect of vaccination programmes cannot be assessed directly as the counterfactual, that is, the situation without vaccination, cannot be observed. Hence, models of disease risk and the impact of vaccination activities play a vital role in assessing the current burden, examining the effect of previous activities and projecting the future situation. The Vaccine Impact Modelling Consortium (VIMC), established in 2016, aims to deliver an effective, transparent and sustainable approach to generating disease burden and vaccine impact estimates (Imperial College London, 2021). The VIMC consists of twenty-one independent research groups which provide estimates of disease burden and vaccine impact across 112 LMICs for 10 pathogens, namely hepatitis B (HepB), Haemophilus influenzae type b (Hib), human papillomavirus (HPV), Japanese encephalitis (JE), measles, Neisseria meningitidis serogroup A (MenA), Streptococcus pneumoniae (PCV), rotavirus (Rota), rubella, and yellow fever (YF). There are various ways of calculating the impact of vaccination (Echeverria-Londono et al., 2021). The burden averted by vaccination can be estimated in terms of the number of cases, deaths and disability adjusted life years (DALYs) averted. Vaccine impact is commonly presented by calendar year, that is, the number of lives saved by vaccination in a particular year or by birth cohort, that is, the number of lives saved by vaccination over the lifetime of individuals born in a particular year. Previous work by the VIMC on these 10 pathogens estimated that 69 million deaths would be averted by vaccination over calendar years 2000–2030 across 98 LMICs, with 120 million deaths averted over the lifetime of birth cohorts born between 2000 and 2030 (Li et al., 2019). The WHO estimates that immunisation currently prevents 2–3 million deaths every year (World Health Organisation, 2021), similarly Ehreth, 2003 estimated 3 million deaths averted due to vaccination for pathogens such as measles, YF, HepB, diptheria, Hib, pertussis, neonatal tetanus and poliomyelitis. Although attributing vaccine impact to calendar year or birth cohort is intuitive and commonly used, these methods fail to capture the impact of a specific year's vaccination activities traced over the lifetime of those vaccinated. It is beneficial to examine the impact corresponding to a vaccination activity so that the cost and benefit of each intervention can be appropriately calculated. The impact by year of vaccination activity method, developed by the VIMC, estimates the number of individuals that will be saved due to a particular year's vaccination activities (Echeverria-Londono et al., 2021). This method addresses the issue of attributing impact to the vaccination activity that caused it without repeatedly rerunning modelling scenarios which, whilst the optimal approach, is extremely computationally intensive. As such, we can approximate the potential effect of one year's worth of activity. The first human case of coronavirus 2019 (COVID-19) was reported in December 2019 and has subsequently affected vaccination and healthcare worldwide. Whilst the effect of COVID-19 is not the focus of the current study, we acknowledge the huge influence the global pandemic has had and will have for years to come. Preliminary work has begun on quantifying the effect of disruption on vaccination activities and on assessing the benefit of continuing routine infant immunisation in times of COVID-19 (Abbas et al., 2020a; Gaythorpe et al., 2021b). There is also evidence that the rise in non-pharmaceutical interventions (NPIs, e.g. social distancing) associated with the pandemic may re
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