From  the  modellers’  point  of  view  - How to communicate with the policy community? - Kari Auranen and Tuija Leino

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From  the  modellers’  point  of  view  - How to communicate with the policy community? - Kari Auranen and Tuija Leino

  1. 1. From  the  modellers’  point  of  view  -How to communicate with the policy community? Kari Auranen and Tuija Leino Department of Vaccination and Immune Protection National Institute for Health and Welfare, Finland
  2. 2. Outline Infectious disease modelling at NPHI/Finland Three recent examples  Varicella vaccination  HPV vaccination  Pneumococcal conjugate vaccination Communicating modelling results to decision makers  Main question(s) for modelling  Some results and how they were addressed in decision making  Lessons learned
  3. 3. Infectious disease modellingat NIPH/Finland Haemophilus influenzae type b (Hib) Streptococcus pneumoniae Cost-effectiveness  analysis:  rota,  flu,  pnc,… Transmission  models:  varicella,  HPV,  …1994 1997 2000 2003 2006 2009 2012 2 3 4 8 7 6
  4. 4. Criteria for the introduction of a new vaccineto the national programme in Finland [1] There is a considerable disease burden which can be prevented by vaccination [2] The vaccine is safe on the individual level [3] Vaccination is safe on the population level [4] Vaccination is cost-effective NACV
  5. 5. Varicella zoster virus Chickenpox  Childhood disease (90% cases in children < 10y)  Virus remains latent, can activate as herpes zoster Herpes zoster  Disease of the elderly  Encounters with varicella virus may sustain immunity against herpes zoster Vaccination protects from chickenpox and (subsequent) herpes zoster  Under high coverage of vaccination, circulation of the virus ceases  The adult population may become susceptible to herpes zoster because lack of boosting
  6. 6. Introducing varicella vaccination? Vaccination against varicella zoster virus has not been part of the national program in Finland Vaccine-specific expert group (2006-2008) The main question for dynamic modelling  What would be the effect of varicella vaccination on zoster incidence?
  7. 7. Three types of data Age-specific incidence of varicella infection  At what age do individuals first encounter the virus? A contact survey on the social mixing pattern: ”who  meets  with  whom”  From whom do they acquire the virus? Age-specific incidence of herpes zoster  At what age do individuals get the disease?
  8. 8. Incidence of varicellaProportion with varicella virus At what age do individuals first encounter the virus? Age (years) Davidkin et al.
  9. 9. Pattern of transmission Finland 70+ 65-69 60-64 Age of the contact 55-59 50-54 From whom 45-49 Age of contact 40-44 35-39 30-34 do individuals 25-29 acquire 20-24 15-19 the virus? 10-14 05-09 00-04 70+ 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 Age of participant Age of participant 0.00-0.31 0.31-0.63 0.63-0.94 0.94-1.25 1.25-1.56 Mossong et al, 2008 1.56-1.88 1.88-2.19 2.19-2.50
  10. 10. Incidence of zoster At what age do individuals get zoster? Karhunen et al., 2009
  11. 11. A transmission model + zoster Susceptible, (a,t) Infected, latent  Infectious,  VZV positive S(a,t) phase L(a,t) I(a,t) with one previous exposure (1-)v1(a,t) (a,t) Herpes zoster, h(a,d) H(a,t) VZV positive with two Vaccinated v2(a,t) previous  exposures protected, R(v)(a,t) Removed, (a,t) R(a,t) VZV positive with three v1(a,t)  previous v2(a,t) exposures  etc. Vaccinated Vaccinated Vaccinated susceptible, latent, L(v)(a,t) infectious, S(v)(a,t) (a,t) I(v)(a,t)
  12. 12. Effects of vaccination  Varicella transmission stops in few years  Incidence of zoster increases, in excess to that due to aging population  The extent of the excess increase depends on the model assumptions  30-85% excess cases in the next 50 years
  13. 13. Excess cases under 2 scenarios Zoster immunity depends solely on exposure to the virus Zoster immunity depends on exposure and aging Karhunen et al., 2009
  14. 14. What  happened  next… Cost-effective analysis  Varicella vaccination was deemed cost effective, even under the worst case scenario for zoster Vaccine-specific Expert Group (2008)  Recommendation,  with  ”consideration  of  potential   increase  in  zoster  incidence”  and  a  reference  to  potential   use of HZ vaccine  not necessarily safe for the (elderly) population National Advisory Committee (2009)  No agreement: the decision was put on hold
  15. 15. Lessons learned Worst-case scenarios should perhaps not present the absolutely worst outcomes  The modelling group intended to maximise certainty  However, the worst-case may have been taken as a likely outcome  There was actually a wish to remove any reference into zoster risk Efficient  communication  of  one’s  own  results   possible as long as one can participate in boards  Commitment  to  the  implications  of  one’s  own  modelling   results is inevitable (and appropriate)
  16. 16. Human papillomavirus (HPV) Common asymptomatic and usually transient infection  Up to 30% of young adults are infected at any time  Infection may become persistent and progress to cancer Cervical cancer (5.7/100,000 in Finland)  The incidence of disease is greatly modulated by the very effective screening program in Finland Vaccination protects against primary HPV infection and (subsequent) disease  The impact of screening is intertwined with that of vaccination
  17. 17. Introducing HPV vaccination? The aims for dynamic modelling  To disentangle the underlying disease process from that affected by the current screening program  To optimise the screening program  To consider the optimal introduction policy for HPV vaccination The model was constructed in two parts (1) Transmission of the virus (2) Progression of infection to disease
  18. 18. Elements of modelling HPV TREATMENT AND MANAGEMENT CIN0Outcome CIN1 CIN2 CIN3 CaScreening testing testing testing testing testing/ sypmtomsRate of CIN0 CIN1 CIN2 CIN3 Cancerinfection Clear Clear Clear Clear Vänskä, Salo et al. 2012
  19. 19. The fate of HPV vaccination(and screening)? Vaccine-specific Expert Group and the National Advisory Committee recommended introducing the vaccine The screening experts presented strong criticism against the underlying analysis  Strong reliance on the current screening policy  The perception of the burden of disease was based on the apparent incidence of disease  Opportunistic screening falls out of the sight of the systematic screening program The final decision was put on hold, primarily for financial reasons
  20. 20. Lessons learned Communicating modelling results to a group of outside stakeholders in their own substance matter area is extremely difficult  Without success in engaging the group from the first beginning  Without the incentive originating from that group  Without expertise and tradition in the methods of modelling in that group If the model-based analysis is not totally transparent, including its relation to epidemiological data  Criticism is considered more acceptable  Criticism more likely misses the point  The justification of criticism is impossible to assess by the third parties
  21. 21. Pneumococcus (Streptococcus pneumoniae) Causes different forms of disease  Mild infections of the respiratory tract  Pneumonia  Meningitis Is usually carried asymptomatically New vaccines protect against disease due 10 or 13 types out of the >90 types Vaccination affects asymptomatic carriage as well  This may lead to increase in carriage and disease caused by the non-vaccine types
  22. 22. Setting the tender criteria Currently, the 10-valent vaccine is in the national immunisation program A new tender process was to be prepared to choose between the 10- and 13-valent vaccines  Price and quality (i.e. number of types) Questions for modelling:  Considering the expected greater health benefits from the 13-valent vaccine, how much more are we prepared to pay for that?  What is the expected difference in the health outcomes (incidence of disease)?
  23. 23. Predicting replacement disease 14 PCV13*: No vaccination 0.0004 19A 4e-04Case to carrier ratio (CCR) PCV10: IPD: 4 6B 7F 9V 18C PCV10 types 78 2e-04 1 PCV13*types 15 22 9N 12 11 15 8 rst 35 0.0002 3 10 33 16 23A 20 35F other 7 23F 19F 6A ------------ 100 0e+00 0 * PCV13 0e+00 0 2e+05 200 000 4e+05 400 000 6e+05 600 000 8e+05 800 000 additional types 0.0004 19A Incidence of carriage per year (absolute value) 4e-04 PCV10 2e-04 IPD: 0.0002 3 6A PCV10 types 37 PCV13*types 17 0e+00 ------------ 4e-040 other 54 0e+00 0 2e+05 200 000 4e+05 400 000 6e+05 600 000 8e+05 800 000 PCV13 2e-04 22 9N 12 11 15 8 rst 0.0002 35 10 33 16 IPD: 23A 20 35F other 24 0e+00 0 0e+00 0 2e+05 200 000 4e+05 400 000 6e+05 600 000 8e+05 800 000 Nurhonen et al., 2012
  24. 24. Differences in disease incidence Salo et al., 2012
  25. 25. What happened next? The Ministry accepted the tender criteria, based on the modelling results  This was based on a simplified model of vaccine efficacy against individual types  This fact was overlooked by the board, probably due to too much preoccupance to other assumptions The tender criteria have already been criticised by the other vaccine provider  Criticism of the models not being truthful enough!
  26. 26. Lessons learned Although the models incorporate a large number of assumptions, only some of them usually catch attention in expert panels  The communication needs to be based on few key assumptions  It is not worthwhile to present solutions to problems, which the expert panel does not know to appreciate in the first hand Implications of the decisions need to be made explicit
  27. 27. Concluding remarks Communication for public health decision makers and science audiences differ  More  emphasis  on  ”certainty”  in  public  health Peer-reviewed publications from the group give more support and credibility The  modeller’s  view  may  sometimes  be   (appropriately) naive  We live in the world of models and methods!
  28. 28. Acknowledgements Heini Salo Simopekka Vänskä Markku Nurhonen Markku Karhunen

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