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. 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. Infectious disease modelling
at 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. Criteria for the introduction of a new vaccine
to 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. 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. 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. 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. Incidence of varicella
Proportion with varicella virus
At what age do
individuals first
encounter the virus?
Age (years) Davidkin et al.

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. Incidence of zoster
At what age
do individuals
get zoster?
Karhunen et al., 2009

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. 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. 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. 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. 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. 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. 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. Elements of modelling HPV
TREATMENT AND MANAGEMENT
CIN0
Outcome CIN1 CIN2 CIN3 Ca
Screening testing testing testing testing testing/
sypmtoms
Rate of CIN0 CIN1 CIN2 CIN3 Cancer
infection
Clear Clear Clear Clear
Vänskä, Salo et al. 2012

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. 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. 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. 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. Predicting replacement disease
14
PCV13*:
No vaccination
0.0004
19A
4e-04
Case 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. Differences in disease incidence
Salo et al., 2012

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. 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. 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. Acknowledgements
 Heini Salo
 Simopekka Vänskä
 Markku Nurhonen
 Markku Karhunen