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Confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against invasive meningococcal diseseases
 

Confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against invasive meningococcal diseseases

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Novartis satellite breakfast session at the Meningitis Research Foundation 2013 conference, Meningitis & Septicaemia in Children & Adults presented by Emeritus Professor Richard Moxon, Dr Jamie ...

Novartis satellite breakfast session at the Meningitis Research Foundation 2013 conference, Meningitis & Septicaemia in Children & Adults presented by Emeritus Professor Richard Moxon, Dr Jamie Findlow and Dr Simon Nadel

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  • investment Under Uncertainty (Princeton University Press, 1994),
  • I will add that although the speakers are important, time has been allocated for discussion and it is to be hoped that this will make an equally important contribution to the session.

Confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against invasive meningococcal diseseases Confidence in numbers; the evidence base for assessing thepublic health impact of vaccines against invasive meningococcal diseseases Presentation Transcript

  • THE EVIDENCE BASE FOR ASSESSING THE PUBLIC HEALTH IMPACT OF VACCINES AGAINST INVASIVE MENINGOCOCCAL DISEASES UK/BEX/13-0047f Date of prep: Oct 2013
  • Disclosure statement • Prof Richard Moxon is a member of the Scientific Advisory Boards of Novartis Vaccines and Diagnostics (NVD) and GlycoVaxyn from whom he receives financial compensation for his time; he holds no intellectual property and has no financial holdings or potential gains relating to 4CMenB.
  • Milestones in meningococcal vaccines • • • • • • • 1970s 1992 1999 2003 2010 2013 2013 Polysaccharide vaccines First conjugates for MenA and MenC MenC licensed in UK MenACYW licensed in USA (aged >11y) MenA licensed in Africa MenACYW licensed (aged >2 months) EMA licenses 4CMenB (Bexsero ® ) Bexsero prescribing information can be found on the last slide
  • July 2013: JCVI watershed recommendation* • «.......on the basis of the available evidence .... immunization using Bexsero is highly unlikely to be costeffective ...... • ...and could not be recommended» * JCVI interim position statement on use of Bexsero meningococcal B vaccine in the UK
  • Models of cost effectiveness • Models simplify: they are supposed to …. • Some factors are omitted • Can these omissions introduce bias? - familiar examples: climate change, markets
  • In defence of models: “Better to be roughly right than precisely wrong – or not to make any estimate at all ” John Maynard Keynes In opposition to models: “ Not appropriate tools for decision making as their use assumes a level of knowledge and precision that is illusory ” Robert Pindyck
  • Aims of breakfast session • To provide information and stimulate discussion on the evidence base used to inform decision making on the potential public health impact of 4CMenB (Bexsero) • Measuring disease burden and estimating vaccine impact Dr Jamie Findlow Deputy Head of Vaccine Evaluation Unit, Public Health England, Manchester • Challenges to quantifying the severity of meningococcal disease Dr Simon Nadel Consultant in Paediatric Intensive Care, St Mary’s Hospital, London • Panel discussion
  • Measuring disease burden and estimating vaccine impact Jamie Findlow jamie.findlow@phe.gov.uk Vaccine Evaluation Unit, Public Health England, Manchester, UK.
  • Disclosure statement  Jamie Findlow undertakes research, advisory and educational activities on behalf of Novartis as well as other vaccine manufacturers. All income and payments associated with these activities are made to his employers, Public Health England or independent charity. 10 Measuring disease burden and estimating vaccine impact
  • Presentation overview    11 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • Presentation overview    12 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • What are the input parameters into a model? Epidemiological parameters Vaccination parameters  Disease burden/incidence  Case fatality rate  Years of life lost  Vaccination coverage  Vaccine efficacy  Vaccine strain coverage  Impact (reduction) on carriage  Adverse reactions  Vaccine cost  Delivery costs Treatment costs  Ambulance & hospital costs  Specialist/intensive care costs  Follow up care costs Public Health response  Response to each case Long-term effects of disease  Sequelae  QALY 13 Aim: present the scientific data for deriving an input value for each of these parameters Measuring disease burden and estimating vaccine impact
  • Presentation overview    14 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • Changing epidemiology- Laboratory confirmed meningococcal disease cases in England & Wales1 MenW Number of cases 140 120 58 cases 100 80 60 2000/01 “Hajj” outbreak 21 cases Natural fluctuation 40 20 0 MenY Number of cases 100 87 cases 80 60 40 17 cases 20 0 15 Measuring disease burden and estimating vaccine impact 1 Public Health England Meningococcal Reference Unit, Unpublished data
  • Laboratory confirmed cases of meningococcal disease from England & Wales, 1984/85 to 2012/131 3000 2500 NG/ND Z/29E W Y X C B A „Latest‟ MenB burden 622 cases 2004/05 to 2005/06 Ave 1174 MenB cases per year Highestconfirmation PCR MenB burden 1624 MenB cases introduced in 1996 1997/98 to 2005/06 Ave 1305 MenB cases per year No. of cases 2000 Lowest MenB burden 344 cases 1984/85 to 2012/13 Ave 974 MenB cases per year Last two years (2011/12 to 2012/13) Ave 633 MenB cases per year 1500 1000 500 0 16 Measuring disease burden and estimating vaccine impact 1 Public Health England Meningococcal Reference Unit, Unpublished data
  • Other considerations when determining disease burden  Which data source should be used?  PHE Meningococcal Reference Unit (MRU).  PHE infectious disease surveillance reports (LabBase).  Hospital Episode Statistics (HES).  Office National Statistics (ONS) death registrations.  Disease burden varies across age groups (and varies by capsular group).  Meningococcal epidemiology is unpredictable Naturally fluctuates with peaks and troughs.  Outbreaks may occur. 17 Measuring disease burden and estimating vaccine impact
  • Presentation overview    18 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • Meningococcal Antigen Typing System (MATS) Are any of the Bexsero components in the test strain: (i) Expressed to a sufficient degree? and (ii) Similar enough to the antigens in the vaccine such that the antibodies generated by Bexsero will kill the bacteria? MATS ELISA determines the minimum amount of recognisable antigen needed to result in bacterial killing for each of fHbp, Nad A and NHBA (PorA characterised by sero/genotyping). For a strain to be „covered‟, at least one antigen must be greater than the positive bactericidal threshold (PBT) or possess homologous PorA. 19 Measuring disease burden and estimating vaccine impact
  • MATS predicted coverage of European MenB isolates from 2007/08 100% 73% (57-87) 85% (69-93) 82% (69-92) 87% (70-93) 85% (76-98) 78% Overall coverage (63-90) (95% CI) 90% 80% 70% 4Ag>PBT* 60% 3Ag>PBT* 2Ag>PBT* 50% 1Ag>PBT* 40% *> MATS PBT for fHBP, NadA and NHBA/homologous PorA. 30% 20% 10% 0% England and Wales 20 France Germany Italy Measuring disease burden and estimating vaccine impact Norway Combined Vogel U et al., Lancet Infect Dis 2013;13:416-25.
  • Considerations for interpreting MATS data  MATS PBT derived using pooled sera from 12-13 month toddlers post booster.1  Infants antibody responses are less cross-reactive.  Older children's and adolescents antibody responses may be more cross-reactive.  MATS may underestimate NadA expression due NadR repression during the in-vitro assay growth conditions.1,3  MATS concept is “conservative” and does not account for Any antibody synergy.1-3  Any responses against minor OMV components.1-3 1Donnelly 21 Measuring disease burden and estimating vaccine impact J et al., Proc Natl Acad Sci USA 2010;107:19490-5. G et al., Vaccine 2013: in press 3Vogel U et al., Lancet Infect Dis 2013;13:416-25. 2Frosi
  • MATS Prediction (535 MenB strains from 2007/07)1 MATS Prediction (40 MenB strains subset) 73% (95% CI 57-87) 70% (95% CI 55-85) Percentage of 40 strain subset killed in hSBA assay 100 Percentage coverage 80 60 40 88% (95% CI 72-95) 88% (95% CI 72-95) Toddler sera Adolescent sera 20 0 MATS prediction (full data set) 22 MATS prediction (40 sub set) Measuring disease burden and estimating vaccine impact 1Vogel U et al., Lancet Infect Dis 2013;13:416-25.
  • Capsular group distribution of laboratory confirmed meningococcal disease, England and Wales, 2012/131 Q1- Could protection be afforded against non-MenB strains? Age breakdown of MenW cases in England and Wales 2006/07 to Other C 2012/131 4% W 1% 200 7% Y 10% Q2- Should any „additional‟ protection be considered? Number of cases 150 31% of cases in <20 years of age B 78% 100 69% of cases in >20 years of age  One study suggested that 27/57 (48%) of MenC and 14/20 (70%) of MenW strains could be killed in the SBA assay by pooled postBexsero vaccination sera from toddlers.2 50 0 <1 1-4 5-9 10-14 15-19 20-24 Age group 25-44 45-64 >=65 1 23 Measuring disease burden and estimating vaccine impact Public Health England Meningococcal Reference Unit, Unpublished data et al., Poster 273, International Pathogenic Neisseria Conference 2012, Wurzburg, Germany, 9-14 September 2012. 2Claus
  • Presentation overview    24 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • Why is carriage and herd protection important?  Glycoconjugate vaccines reduce the acquisition of nasopharyngeal carriage of Haemophilus influenzae type b1, Streptococcus pneumoniae2, MenC3 and MenA4.  Imparts herd protection, and impacts on immunisation strategy. 2 71% reduction 81% reduction 1 8 6 67% reduction in rate in unvaccinated cohort 2001/02 4 2 0 0 1999 25 Direct and Herd protection5 Attack rate per 100,000 Percentage of MenC isolates 3 Reduction in MenC carriage3 (immunised 15-19 year olds) 2000 Unvaccinated 1998/99 2001 Measuring disease burden and estimating vaccine impact 1Takala Unvaccinated 2001/2002 Vaccinated 2001/2002 AK et al., J Infect Dis 1991;164:982-6. 2Dagan R et al., J Infect Dis. 1996;174:1271-8. 3Maiden MC et al., J Infect Dis. 2008;197:737-743. 4Kristiansen PA et al., Clin infect Dis 2013;56:354-63. 5Ramsay ME et al., BMJ; 326:365-6.
  • Impact of outer membrane vesicle vaccines on carriage Bjune G et al., 19921 Subject age range Number of subjects (vaccinated/contr ols) Vaccine Reduction of carriage Prevention of acquisition Holmes JD et al., 20083 Delbos V et al., 20134 Norway Country Rosenqvist E et al., 19942 Norway New Zealand France Do 13-21 vaccines have an impact on OMV 13-14 17-24 carriage? Observations from multiple phase II 529/265 57/152 Conflicting results/inconclusive. trials 3-7  321/761 MenBvac MenBvac MeNZB  Small numbers of subjects in each study. MenBvac  Low carriage ratesNo have No No Yes Yes (100% for hindered evaluations. (85% for all vaccine/outbreak meningococci) strain) Yes (59% for all meningococci) No ND ND: Not determined 1Bjune 26 Measuring disease burden and estimating vaccine impact G et al., Lancet 1992;340:315. 2Rosenqvist et al., In VIII International Pathogenic Neisseria conference, 1994, Cuernavaca, Mexico, 4-9 October 1992. 3Holmes JD et al., Epidemiol Infect 2008;136:790-9. 4Delbos V et al., Vaccine 2013;31:4416-20.
  • Bexsero carriage study1,2 Trial Design Group Visit 1 Day 1 Visit 2 Month 1 Visit 3 Month 2 Visit 4 Month 4 Visit 5 Month 6 Visit 6 Month 12 Enrolled Bexsero Swab Bexsero Swab Bexsero Swab Swab Swab Swab Menveo 974 Control Swab JE vaccine Swab JE vaccine Swab Swab Swab Swab Menveo 983 MenACWY Swab MenACWY Swab Placebo Swab Swab Swab Swab - 984 JE- Japanese Encephalitis vaccine Primary analysis- Carriage of disease associated sequence types (ST) of N. meningitidis capsular group B, 1 month post-2nd dose of Bexsero. 1Read 27 Measuring disease burden and estimating vaccine impact R et al., In The 31st meeting of the European Society for paediatric infectious diseases. 2013, Milan, Italy, 28th May-1st June 2013. 2Borrow et al., In The 13th European Meningococcal Disease Society, 2013, Bad Loipersdorf, Austria, 17-19th September 2013.
  • Bexsero carriage study- Primary analysis1,2 Primary analysis- Carriage of disease associated sequence types (ST) of N. meningitidis capsular group B, 1 month post-2nd dose of Bexsero.* Study limitations Bexsero Group Control Group  High baseline carriage rates (~33%). Efficacy % (95% CI) Number 87 75  Access to students prior to period of -18.2 (-73.7 to  Assessment of individual impact, not of 19.4) herd protection. 916 N 928 Visit 3 high transmission not possible. % 9.50 8.08 (Month 2) * Analyses adjusted for baseline carriage, treatment group, centre and significant risk factors as identified within the multivariate model. 1Read 28 Measuring disease burden and estimating vaccine impact R et al., In The 31st meeting of the European Society for paediatric infectious diseases. 2013, Milan, Italy, 28th May-1st June 2013. 2Borrow et al., In The 13th European Meningococcal Disease Society, 2013, Bad Loipersdorf, Austria, 17-19th September 2013.
  • Bexsero carriage study- Further analyses1,2 Further analysis- Efficacy % (95% CI) of Bexsero group compared to control group undertaken for visits 4 to 6 (months 4 to 12).* Group Capsular group B, C, W & Y Any N. meningitidis All Risk factor subgroups with high transmission /acquisition Capsular group B (all STs) 15.6 (-11.0 to 35.9) 26.6 (10.5 to 39.9) 18.2 (3.4 to 30.8) Early enrollers (<30 days after start of semester) 17.0 (-28.9 to 46.5) 32.0 (8.2 to 49.6) 33.7 (13.9 to 49.0) Smokers 38.1 (-9.1 to 64.9) 44.8 (14.0 to 64.5) 32.2 (2.5 to 52.9) <21 years of age at enrolment 23.9 (-4.0 to 44.4) 28.0 (9.9 to 42.4) 22.5 (6.3 to 35.9) * Analyses adjusted for baseline carriage, treatment group, centre and significant risk factors as identified within the multivariate model. 29 Measuring disease burden and estimating vaccine impact 1Read R et al., In The 31st meeting of the European Society for paediatric infectious diseases. 2013, Milan, Italy, 28th May-1st June 2013. 2Borrow et al., In The 13th European Meningococcal Disease Society, 2013, Bad Loipersdorf, Austria, 17-19th September 2013.
  • Presentation overview    30 Background information  Model input parameters Evidence base for determining Disease burden  Vaccine strain coverage  Vaccine impact on carriage (herd protection) Summary and conclusions Measuring disease burden and estimating vaccine impact
  • Summary and conclusions Disease burden  Meningococcal epidemiology is unpredictable and continually fluctuating. Strain coverage  MATS is “conservative” with recent data indicating higher coverage than that predicted by MATS.  Should protection against non-MenB strains be included in coverage? Carriage impact  Although the Bexsero carriage study failed to show any positive impact for the primary analysis, due to various limitations, further analyses demonstrated an impact. Other considerations  The scientific data behind each input parameter is variable and it is difficult to decide upon which is the appropriate or „correct‟ value.  Any value derived is a prediction of the future, which may or may not be accurate. 31 Measuring disease burden and estimating vaccine impact
  • Acknowledgements Vaccine Evaluation Unit, Public Health England, Manchester Ray Borrow. Meningococcal Reference Unit, Public Health England, Manchester Ed Kaczmarski, Steve Gray and Tony Carr. Immunisation, Hepatitis and Blood Safety Department, Public Health England, London Mary Ramsay, Shamez Ladhani and Helen Campbell. 32 Measuring disease burden and estimating vaccine impact
  • Challenges to quantifying the severity of meningococcal disease. Novartis Symposium 2013 Dr Simon Nadel
  • Disclosure statement Dr Simon Nadel undertakes research, advisory and educational activities on behalf of Novartis, Pfizer and the National Meningitis charities.
  • Challenges in quantifying disease • Can we accurately quantify mortality and morbidity? • Can wider impacts of meningococcal disease (social, economic and public health considerations ) be quantified?
  • Challenges in quantifying disease • Can we accurately quantify mortality and morbidity? • Can wider impacts of meningococcal disease (social, economic and public health considerations ) be quantified?
  • Variability in reported mortality & morbidity • Key differences in study inclusion criteria and definitions: – – – – – Disease focus (meningitis, septicaemia, IMD, acute life-threatening illness) Study populations (age, geography, hospitalisation/ ICU admission) Follow-up period (acute vs long-term) Categorisation, scoring and weighting of sequelae (impact on QoL) Physical +/- neuro-psychological impact on individuals • No consensus on how to weigh the impact of different sequelae – – – – Do “major” and “minor” sequelae have different impact on Quality of Life? Include immediate and long-term effects of sequelae? Can we effectively quantify Quality of Life loss in children? Impact on patients +/- carers +/- families +/- healthcare system +/- society?
  • Variability in reported mortality: CFR Agegroup (y) Causative organism(s) Data collection Data source Reference 23% - 2% 0-18 All capsular groups 1992-1997 St. Mary‟s Hospital PICU Booy, 2001 5.2% 0-19 Capsular group B 2006/72010/11 HPA enhanced surveill, England & Wales Ladhani, 2013 4% All ages Not specified 1997/82005/6 HES data, England Christensen, 2013 4.9% All ages All capsular groups 1999-2010 English national linked database Goldacre, 2013 12.4% - 10.6% 0-19 All capsular groups 1995, 2000, 2005 Severe mening sepsis data from 7 US states Hartmann, 2013 4.4% 0-1 All capsular groups 1985-7 England & Wales De Louvois, 1991
  • Variability in reported morbidity: Meningococcal disease and meningitis Invasive meningococcal serogroup B disease in children and adolescents (MOSAIC) Meningitis in infancy in England and Wales: follow up at age 5 years 244 survivors of group B meningococcal disease 402 survivors of meningococcal meningitis 1% disabling amputations 2.9% severe disability 9% major disabling deficits 6.5% moderate disability 36% at least one deficit 29.8% mild disorder 2% profound bilateral SNHL 60.7% no disability 5% moderate bilateral SNHL 6% any SNHL (control <1%) 4% speech/ communication difficulty IQ, memory and executive function significantly worse Significantly higher risk of mental health disorder (26% vs 10%) Viner, 2012 Bedford, 2001
  • Variability in reported morbidity: Survivors of meningococcal septic shock that required PICU treatment Long term skin-scarring & orthopaedic sequelae Long term overall outcome and health-related QoL Long term health status n=170, 4-16y after discharge n=120, 3-18y after discharge n=120, 10y after discharge 34% scarring 61% had 1 of 4 major adverse outcome variables 35% one or more neurological impairment 5.8% amputations 21.7% had >1 major adverse outcome 4% severe mental retardation 4.1% lower limb length discrepancy 39.2% had 1 major adverse outcome 3% epilepsy All had higher severity of illness scores 7.6% major physical adverse outcome 2% hearing loss 15.8% mild neurological outcome 6% focal neurology (i.e. paresis) 5.8% problem behaviour 6.7% had IQ<85 Longer LOS and higher severity score predicted worse outcome Buysse, 2009 Buysse, 2010 Buysse, 2008
  • Main determinants of outcome • Severity/pathophysiology • Management • Pre-morbid condition • Genetics • Family • Other factors
  • Challenges in quantifying disease • Can we accurately quantify mortality and morbidity? • Can wider impacts of meningococcal disease (social, economic and public health considerations ) be quantified?
  • Clinical evidence of longer-term effects • “Longer-term psychiatric adjustment of children and parents after meningococcal disease” Garralda ME, Gledhill J, Nadel S, Neasham D, O'Connor M, Shears D. Pediatr Crit Care Med. 2009 Nov;10(6):675-80. doi: 10.1097/PCC.0b013e3181ae785a. • Prospective cohort study of 70 children aged 3-16y with MD, admitted to 3 PICUs and 22 general paediatric wards in London –Parents and children seen 2-5d after hospital admission, and followed up following discharge at 3m (postal questionnaire) and 12m (interview) –Psychiatric risk assessed in children (SDQ), parents (GHQ) and both (IES)
  • Psychological after effects in parents & carers Outcomes in children and parents, 3 months and 12 months post discharge Children < 6y Children >6y 11% had PTSD 3 months post discharge Psychological symptoms linked to: PICU admission, illness severity, similar symptoms in parents and pre-morbid psychological symptoms Parents ~50% mothers and ~25% fathers had PTSD symptoms MD associated with emotional and hyperactivity symptoms 11% children at risk for PTSD Psychological symptoms linked to illness-related changes in parenting 12 months post discharge 1 child developed PTSD 22% scored above cut-off for psychiatric disorder Problems: tantrums, difficult to manage, sleep problems, fears and feeding problems • 50% at least one disorder 16% major depression 10% minor depression 8% adjustment disorder 8% oppositional defiant disorder 2% phobic disorder 2% panic disorder 2% organic psychotic disorder 24% mothers and 15% fathers at high risk for PTSD Maternal PTSD linked to paternal PTSD Summary: 50% of children develop mostly new psychopathology following MD (primarily depressive and anxiety-related disorders). In 25% this persisted at one year Garralda ME, et al. Pediatr Crit Care Med. 2009;10(6):675-80
  • Clinical evidence of neuropsychological effects • “Neuropsychologic function three to six months following admission to the PICU with meningoencephalitis, sepsis, and other disorders: a prospective study of school-aged children” Als LC, Nadel S, Cooper M, Pierce CM, Sahakian BJ, Garralda ME. Crit Care Med. 2013 Apr;41(4):1094-103. doi: 10.1097/CCM.0b013e318275d032. • Prospective observational case-control study of 88 children aged 5-16y admitted to ICUs between 2007-2010 c.f. 100 healthy controls –Follow-up 3-6 months after PICU admission –Data encompassing demographic and critical illness details were obtained, and children were assessed using tests of intellectual function, memory, and attention –Questionnaires addressing academic performance were returned by teachers. –Measurement tools: WASI, WRIT, CMS, Cambridge Neuropsychological Test Automated, Battery (CANTAB)
  • Neuropsychologic function after PICU admission Psychiatric risk PTSD risk Cognitive function • Summary: Meningoencephalitis and sepsis particularly associated with reduced neuropsychological function • Are these effects fully considered in evaluation of new vaccines? Adapted from Als LC, et al. Crit Care Med. 2013;41(4):1094-103
  • Can social, economic and public health considerations be quantified?
  • Counting the cost of Meningitis: Estimates for the management costs of a severe case of meningitis Discounted costs Undiscounted costs £600,000 to £1,000,000 £1,230,000 to £2,360,000 £1,300,000 to £1,700,000 £2,980,000 to £4,280,000 Costs to NHS Acute costs 26 days in PICU, 155 days on rehabilitation ward Outpatient appointments, including: -Physiotherapists -Speech and language therapists -Occupational therapists Other specialist treatments Costs to Personal Social Services Social care assessment, direct pay payments, short break provision, residential Costs to government Education, disabled facilities grant, specialised vehicle fund, lost income tax revenue, transfer payments Wright C, Wordsworth R, Glennie L. Meningitis Research Foundation: Counting the costs of meningitis. 2011.
  • Costs to society Siblings of disabled children are more likely to experience Families are four times more likely behavioural and emotional problems1 to be living in poverty (84% of mothers of disabled children do not work compared to 39% of mothers of nondisabled children1) Day to day costs to the family with a disabled child are three times more than with a non-disabled child (Minimum budget to bring up a disabled child £7,355 per year compared to £2,100 for a nondisabled child2 ) 1. New Philanthropy Capital, 2007 2. Joseph Rowntree Foundation, 1998 Depression and anxiety are more common among family members1
  • Summary • Estimates of mortality and morbidity (frequency and impact) vary considerably • The values selected for inclusion directly affect cost-effectiveness calculations • HE models currently include values to represent: – – – – – Case fatality rate Proportion of survivors with „minor‟ sequalae Proportion of survivors with „major‟ sequalae QALY for survivors without sequalae QALY loss for survivors with sequalae • Can we be confident that the selected data adequately capture the clinical burden of meningococcal disease?
  • PANEL DISCUSSION UK/BEX/13-0047f Date of prep: Oct 2013
  • Strengths of models • Validated method for assessing complex outcomes: multiple components and non-linearity result in counterintuitive results • Provides systematic benchmarking of economic gains or losses to facilitate policy decisions • Rigorous exploration (e.g. through sensitivity analyses) of worst case and best case scenarios – parameter space
  • Weaknesses of models • Results depend crucially on the confidence -- or lack of it -- in the data used to construct the models • Biases are introduced because some essential factors are not easily quantified • It is only one of many methodologies used to assemble an evidence base. • A blunt tool for assessing public health impact as compared to economic gains
  • THE EVIDENCE BASE FOR ASSESSING THE PUBLIC HEALTH IMPACT OF VACCINES AGAINST INVASIVE MENINGOCOCCAL DISEASES UK/BEX/13-0047f Date of prep: Oct 2013