Summary of two economic 

models for dengue vaccine 

TAK-003 use in Puerto Rico

Advisory Committee on Immunization Practices

June 22, 2023 

The models summarized are currently undergoing the CDC economic review following the ACIP 

Guidance for Health Economics Studies, so results should be considered as preliminary.

RajReni Kaul, PhD

CDC/NCIRD/ISD

The findings and conclusions in this presentation are those of the author(s) and do not 

necessarily represent the views of the Centers for Disease Control and Prevention.
Acknowledgements

• This presentation summarizes work conducted by two modeling 

teams

• Notre Dame team contracted by CDC (ND/CDC Model)

• Guido España, Manar Alkuzweny, Alex Perkins

• Takeda team (Takeda Model)

• J. Shen, R. Hanley, I. Zerda, et al. 

• CDC and ACIP contributors and reviewers

• Dengue ACIP workgroup

• Economists at CDC and colleagues (NCIRD/ISD)
Conflicts of Interest Statements

• RajReni Kaul: None.

• Notre Dame team:

• Dr. Guido España and Dr. Alex Perkins have previously received research 

funding from GlaxoSmithKline to support unrelated research on dengue 

vaccine development.

• Dr. Alex Perkins currently receives research funding and consulting fees

from Emergent Biosciences to support unrelated research on

chikungunya vaccine development.

• Takeda team:

• Takeda is the developer and manufacturer of the TAK-003 vaccine.

• Directly employed by Takeda or consultants employed by Putnam PHMR and 

contracted by Takeda
Terminology

Abbreviation Full term/Meaning

ND/CDC Notre Dame/CDC model

VE Vaccine efficacy

DENV (e.g., DENV-3) Dengue virus (e.g., serotype 3 dengue virus)

PICO Policy question articulated as Population, Intervention, Comparison, Outcomes

Case Medically-attended case

Hosp Hospitalization

Additional hospitalizations Hospitalization induced by vaccine-enhanced disease

NNV Number needed to vaccinate to avert an outcome (e.g., NNV hospitalization)

QALY Quality-adjusted life-years

All values rounded to 3 significant figures. 
Outline

• Recap of PICO questions

• Overview of models

• Comparison of results

• Exploring differences in assumptions

• QALY values used, vaccine efficacy

• Summary of Takeda model results 

• Base case

• Scenario analysis

• Model comparison summary and limitations

• Application to PICO questions
PICO Questions

• Should two doses of TAK-003 be administered routinely to seropositive

persons aged 4 – 16 years living in dengue-endemic areas?

• Should two doses of TAK-003 be administered routinely to seronegative

persons aged 4 – 16 years living in dengue-endemic areas?

• Should two doses of TAK-003 be administered routinely to seropositive

persons aged 17 – 60 years living in dengue-endemic areas?

• Should two doses of TAK-003 be administered routinely to seronegative

persons aged 17 – 60 years living in dengue-endemic areas?
General Model Design

Assumption/Model Characteristic Notre Dame/CDC Takeda

Model type Stochastic individual-based model Deterministic compartmental model

Prevaccination screening Included Not included

Vaccine implementation Age range, varying coverage rate over 

time

Single age, a catch-up routine in year 

1 possible, varying coverage rate over 

first four years then constant 

thereafter

Serotype specific VE point 

estimate

Point estimate estimated using multilevel Bayesian modelPoint estimate estimated using 

traditional methods from clinical trial*

Serotype specific VE ranges Each simulation used VE inputs 

sampled from the confidence interval 

around the point estimate

No range, only point estimate used

Geographic area San Juan municipality (N=280,000) Puerto Rico (N=3,256,028 )

DENV caused deaths Not included in QALYs Included in QALYs
Assumption/Model Characteristic Notre Dame/CDC Takeda

Model type Stochastic individual-based model Deterministic compartmental model

Prevaccination screening Included Not included

Vaccine implementation Age range, varying coverage rate over 

time

Single age, a catch-up routine in year 

1 possible, varying coverage rate over 

first four years then constant thereafter

Serotype specific VE point 

estimate

Point estimate estimated using multilevel Bayesian modelPoint estimate estimated using 

traditional methods from clinical trial*

Serotype specific VE ranges Each simulation used VE inputs 

sampled from the confidence interval 

around the point estimate

No range, only point estimate used

Geographic area San Juan municipality (N=280,000) Puerto Rico (N=3,256,028 )

DENV caused deaths Not included in QALYs Included in QALYs

General Model Design

* When the clinical trial estimate was negative or confidence interval included negative values, a VE model input of zero was assumed.
Assumption/Model Characteristic Notre Dame/CDC Takeda

Model type Stochastic individual-based model Deterministic compartmental model

Prevaccination screening Included Not included

Vaccine implementation Age range, varying coverage rate over 

time

Single age, a catch-up routine in year 

1 possible, varying coverage rate over 

first four years then constant thereafter

Serotype specific VE point 

estimate

Point estimate estimated using multilevel Bayesian modelPoint estimate estimated using 

traditional methods from clinical trial*

Serotype specific VE ranges Each simulation used VE inputs 

sampled from the confidence interval 

around the point estimate

No range, only point estimate used

Geographic area San Juan municipality (N=280,000) Puerto Rico (N=3,256,028 )

DENV caused deaths Not included in QALYs Included in QALYs

General Model Design

* When the clinical trial estimate was negative or confidence interval included negative values, a VE model input of zero was assumed.
General Model Design

Assumption/Model Characteristic Notre Dame/CDC Takeda

Model type Stochastic individual-based model Deterministic compartmental model

Prevaccination screening Included Not included

Vaccine implementation Age range, varying coverage rate over 

time

Single age, a catch-up routine in year 

1 possible, varying coverage rate over 

first four years then constant thereafter

Serotype specific VE point 

estimate

Point estimate estimated using multilevel Bayesian modelPoint estimate estimated using 

traditional methods from clinical trial*

Serotype specific VE ranges Each simulation used VE inputs 

sampled from the confidence interval 

around the point estimate

No range, only point estimate used

Geographic area San Juan municipality (N=280,000) Puerto Rico (N=3,256,028 )

DENV caused deaths Not included in QALYs Included in QALYs

* When the clinical trial estimate was negative or confidence interval included negative values, a VE model input of zero was assumed.
Economic Model Preliminary Results by PICO

Age 4-16 years

Model

Scenario conditions

Number 

vaccinated

Net number averted with vaccination §

$/QALY 

(ICER) Geographic §

Area† Age

Prevaccination 

screening Cases Hospitalizations Deaths

ND/CDC San Juan 

Municipality 4-16 Yes 11,700 485 (1.2%) 182 (2.6%) 1 (2.9%) 182,000*

ND/CDC San Juan 

Municipality 4-16 No 30,300 1,070 (2.5%) 192 (2.8%) 1 (2.9%) 255,000*

Takeda Puerto Rico

8, 

catchup 9-16 No 157,000 46,700 (12%) 9,150 (14 %) 5 (13%) Costsaving

†Modeled population size is 280,000 for the San Juan Municipality (ND/CDC model) and 3,256,028 for all of Puerto Rico (Takeda model).

§ When compared to no vaccination

*Death is not incorporated into QALYs gained in the ND/CDC model base case assumptions. If QALY gains from averted deaths were 

included, then the ICERs would change from $182,000 to $65,000 per QALY for the scenario with prevaccination screening and would 

change from $255,000 to $137,000 per QALY for the scenario without prevaccination screening.
Economic Model Preliminary Results by PICO

Age 4-16 years

Model

Scenario conditions

Number 

vaccinated

Net number averted with vaccination §

$/QALY 

(ICER) Geographic §

Area† Age

Prevaccination 

screening Cases Hospitalizations Deaths

ND/CDC San Juan 

Municipality 4-16 Yes 11,700 485 (1.2%) 182 (2.6%) 1 (2.9%) 182,000*

ND/CDC San Juan 

Municipality 4-16 No 30,300 1,070 (2.5%) 192 (2.8%) 1 (2.9%) 255,000*

Takeda Puerto Rico

8, 

catchup 9-16 No 157,000 46,700 (12%) 9,150 (14 %) 5 (13%) Costsaving

†Modeled population size is 280,000 for the San Juan Municipality (ND/CDC model) and 3,256,028 for all of Puerto Rico (Takeda model).

§ When compared to no vaccination

*Death is not incorporated into QALYs gained in the ND/CDC model base case assumptions. If QALY gains from averted deaths were 

included, then the ICERs would change from $182,000 to $65,000 per QALY for the scenario with prevaccination screening, and would 

change from $255,000 to $137,000 per QALY for the scenario without prevaccination screening.
Model

Scenario conditions

Number 

vaccinated

Net number averted with vaccination §

$/QALY 

(ICER) Geographic §

Area† Age

Prevaccination 

screening Cases Hospitalizations Deaths

ND/CDC San Juan 

Municipality 17-60 Yes 105,000 2,710 (6%) 724 (10%) 5 (11%) 397,000*

ND/CDC San Juan 

Municipality 17-60 No 121,000 3,360 (8%) 928 (13%) 4 (14%) 315,000*

Takeda Puerto Rico

17, 

catchup 18-

60

No 449,000 67,000 (17%) 13,100 (21%) 8 (21%) Costsaving

†Modeled population size is 280,000 for the San Juan Municipality (ND/CDC model) and 3,256,028 for all of Puerto Rico (Takeda model).

§ When compared to no vaccination

*Death is not incorporated into QALYs gained in the ND/CDC model base case assumptions. If QALY gains from averted deaths 

were included, then the ICERs would change from $397,000 to $188,000 per QALY for the scenario with prevaccination screening, 

and would change from $315,000 to $153,000 per QALY for the scenario without prevaccination screening.

Economic Model Preliminary Results by PICO

Age 17-60 years
Model

Scenario conditions

Number 

vaccinated

Net number averted with vaccination §

$/QALY 

(ICER) Geographic §

Area† Age

Prevaccination 

screening Cases Hospitalizations Deaths

ND/CDC San Juan 

Municipality 17-60 Yes 105,000 2,710 (6%) 724 (10%) 5 (11%) 397,000*

ND/CDC San Juan 

Municipality 17-60 No 121,000 3,360 (8%) 928 (13%) 4 (14%) 315,000*

Takeda Puerto Rico

17, 

catchup 18-

60

No 449,000 67,000 (17%) 13,100 (21%) 8 (21%) Costsaving

†Modeled population size is 280,000 for the San Juan Municipality (ND/CDC model) and 3,256,028 for all of Puerto Rico (Takeda model).

§ When compared to no vaccination

*Death is not incorporated into QALYs gained in the ND/CDC model base case assumptions. If QALY gains from averted deaths 

were included, then the ICERs would change from $397,000 to $188,000 per QALY for the scenario with prevaccination screening, 

and would change from $315,000 to $153,000 per QALY for the scenario without prevaccination screening.

Economic Model Preliminary Results by PICO

Age 17-60 years
Exploring Difference

Model Inputs : QALY loss from dengue episodes

Disease Outcome

Quality-adjusted 

days lost

ND/CDC Takeda

Non-hospitalized dengue 11.2§ 5.5

Hospitalized dengue 12.8§ 6.8

Persistent dengue after non-hospitalized or 

hospitalized case NA 4.9*

Dengue caused deaths NA

Agedependent

§QALY lost for dengue episodes includes persistent dengue in 34% of all cases.

* Model assumes 34% of dengue episodes aged 30 or older develop persistent symptoms.
Disease Outcome

Quality-adjusted 

days lost

ND/CDC Takeda

Non-hospitalized dengue 11.2§ 6.1†

Hospitalized dengue 12.8§ 7.2†

Persistent dengue after non-hospitalized or 

hospitalized case NA -

Dengue caused deaths NA

Agedependent

Exploring Difference

Model Inputs : QALY loss from dengue episodes

When persistent 

dengue QALY loss is 

combined with 

acute phase QALY 

loss

§QALY lost for dengue episodes includes persistent dengue in 34% of all cases.

† Calculated as if 34% of cases ages 30 or older develop persistent symptoms. 
Exploring Difference

Model Inputs : Vaccine Efficacy 

Disease 

Outcome Model

Vaccine efficacy inputs by serostatus and by dengue serotype

Seronegative at vaccination Seropositive at vaccination

DENV-1 DENV-2 DENV-3 DENV-4 DENV-1 DENV-2 DENV-3 DENV-4

Nonhospitalized 

Symptomatic 

case

ND/CDC* 29.7% 

(6.7, 48.5)

96.3% 

(87.1, 100)

30.0%

(7.8, 49.4)

-1.1%

(-73.5,64.4)

63.1% 

(52.7, 82.2)

85.2% 

(75.6, 94.4)

42.5% 

(26.4, 55.8)

60.2%

(19.8, 89.6)

Takeda† 30.8% 69.8% 0%# 0%# 46.7% 69.8% 42.6% 61.2%

Hospitalized 

case

ND/CDC* 84.6% 

(54.5, 98.7)

99.0% 

(95.6, 100)

-30.3% 

(-91.6, 25.6)

39.2% 

(-20.4, 81.0)

54.1% 

(13.3, 82.2)

99.5% 

(97.8, 100)

70.2% 

(45.6, 90.4)

68.1%

(27.2, 86.2)

Takeda 75.8% 98.5% 0%# 0%§ 75.8% 98.5% 71.4% 100%
Exploring Difference

Model Inputs : Vaccine Efficacy

* Point estimate with 95% confidence interval

† Non-hospitalized case

§Due to lack of data

* Point estimate with 95% confidence interval

† Average VE over 5 years post-vaccination. Includes vaccine waning.

§Due to lack of data

# Value used because pivotal clinical trial estimate or confidence interval included negative values

Disease 

Outcome Model

Vaccine efficacy inputs by serostatus and by dengue serotype

Seronegative at vaccination Seropositive at vaccination

DENV-1 DENV-2 DENV-3 DENV-4 DENV-1 DENV-2 DENV-3 DENV-4

Nonhospitalized 

Symptomatic 

case

ND/CDC* 29.7% 

(6.7, 48.5)

96.3% 

(87.1, 100)

30.0%

(7.8, 49.4)

-1.1%

(-73.5,64.4)

63.1% 

(52.7, 82.2)

85.2% 

(75.6, 94.4)

42.5% 

(26.4, 55.8)

60.2%

(19.8, 89.6)

Takeda† 30.8% 69.8% 0%# 0%# 46.7% 69.8% 42.6% 61.2%

Hospitalized 

case

ND/CDC* 84.6% 

(54.5, 98.7)

99.0% 

(95.6, 100)

-30.3% 

(-91.6, 25.6)

39.2% 

(-20.4, 81.0)

54.1% 

(13.3, 82.2)

99.5% 

(97.8, 100)

70.2% 

(45.6, 90.4)

68.1%

(27.2, 86.2)

Takeda 75.8% 98.5% 0%# 0%§ 75.8% 98.5% 71.4% 100%
Disease 

Outcome Model

Vaccine efficacy inputs by serostatus and by dengue serotype

Seronegative at vaccination Seropositive at vaccination

DENV-1 DENV-2 DENV-3 DENV-4 DENV-1 DENV-2 DENV-3 DENV-4

Nonhospitalized 

Symptomatic 

case

ND/CDC* 29.7% 

(6.7, 48.5)

96.3% 

(87.1, 100)

30.0%

(7.8, 49.4)

-1.1%

(-73.5,64.4)

63.1% 

(52.7, 82.2)

85.2% 

(75.6, 94.4)

42.5% 

(26.4, 55.8)

60.2%

(19.8, 89.6)

Takeda† 30.8% 69.8% 0%# 0%# 46.7% 69.8% 42.6% 61.2%

Hospitalized 

case

ND/CDC* 84.6% 

(54.5, 98.7)

99.0% 

(95.6, 100)

-30.3% 

(-91.6, 25.6)

39.2% 

(-20.4, 81.0)

54.1% 

(13.3, 82.2)

99.5% 

(97.8, 100)

70.2% 

(45.6, 90.4)

68.1%

(27.2, 86.2)

Takeda 75.8% 98.5% 0%# 0%§ 75.8% 98.5% 71.4% 100%

* Point estimate with 95% confidence interval

† Average VE over 5 years post-vaccination. Includes vaccine waning. 

§Due to lack of data

# Value used because pivotal clinical trial estimate or confidence interval included negative values

Exploring Difference

Model Inputs : Vaccine Efficacy
Disease 

Outcome Model

Vaccine efficacy inputs by serostatus and by dengue serotype

Seronegative at vaccination Seropositive at vaccination

DENV-1 DENV-2 DENV-3 DENV-4 DENV-1 DENV-2 DENV-3 DENV-4

Nonhospitalized 

symptomatic 

case

ND/CDC* 29.7% 

(6.7, 48.5)

96.3% 

(87.1, 100)

30.0%

(7.8, 49.4)

-1.1%

(-73.5,64.4)

63.1% 

(52.7, 82.2)

85.2% 

(75.6, 94.4)

42.5% 

(26.4, 55.8)

60.2%

(19.8, 89.6)

Takeda† 30.8% 69.8% 0%# 0%# 46.7% 69.8% 42.6% 61.2%

Hospitalized 

case

ND/CDC* 84.6% 

(54.5, 98.7)

99.0% 

(95.6, 100)

-30.3% 

(-91.6, 25.6)

39.2% 

(-20.4, 81.0)

54.1% 

(13.3, 82.2)

99.5% 

(97.8, 100)

70.2% 

(45.6, 90.4)

68.1%

(27.2, 86.2)

Takeda 75.8% 98.5% 0%# 0%§ 75.8% 98.5% 71.4% 100%

Exploring Difference

Model Inputs : Vaccine Efficacy 

* Point estimate with 95% confidence interval

† Average VE over 5 years post-vaccination. Includes vaccine waning. 

§Due to lack of data

# Value used because pivotal clinical trial estimate or confidence interval included negative values
Disease 

Outcome Model

Vaccine efficacy inputs by serostatus and by dengue serotype

Seronegative at vaccination Seropositive at vaccination

DENV-1 DENV-2 DENV-3 DENV-4 DENV-1 DENV-2 DENV-3 DENV-4

Nonhospitalized 

symptomatic 

case

ND/CDC* 29.7% 

(6.7, 48.5)

96.3% 

(87.1, 100)

30.0%

(7.8, 49.4)

-1.1%

(-73.5,64.4)

63.1% 

(52.7, 82.2)

85.2% 

(75.6, 94.4)

42.5% 

(26.4, 55.8)

60.2%

(19.8, 89.6)

Takeda† 30.8% 69.8% 0%# 0%# 46.7% 69.8% 42.6% 61.2%

Hospitalized 

case

ND/CDC* 84.6% 

(54.5, 98.7)

99.0% 

(95.6, 100)

-30.3% 

(-91.6, 25.6)

39.2% 

(-20.4, 81.0)

54.1% 

(13.3, 82.2)

99.5% 

(97.8, 100)

70.2% 

(45.6, 90.4)

68.1%

(27.2, 86.2)

Takeda 75.8% 98.5% 0%# 0%§ 75.8% 98.5% 71.4% 100%

Exploring Difference

Model Inputs : Vaccine Efficacy 

* Point estimate with 95% confidence interval

† Average VE over 5 years post-vaccination. Includes vaccine waning. 

§Due to lack of data

# Value used because pivotal clinical trial estimate or confidence interval included negative values
Exploring Difference

Impact of vaccine efficacy inputs on outcome

• What if the ND/CDC model uses the Takeda VE inputs in the scenario 

where 4–16-year-olds are vaccinated without screening?

• Takeda’s VE inputs did not substantially impact the results of the ND/CDC 

model. 

VE 

inputs

Number 

vaccinated

Net number averted with vaccination Vaccination enhanced 

disease NNV 

hosp.

QALYs 

gained*

$/QALY 

(ICER)*

Cases Hosp. Deaths Additional 

cases

Additional 

hosp.

ND/CDC† 30,300 1,070

(651-1,470) 

192 

(112-300)

1 

(0.5 -1.5)

45

(35-52)

32 

(29-37)

158 

(101-270) 35 255,000 

Takeda† 30,300 1,030 

(699-1,300) 

287 

(197-425)

1

(0.9 - 2.1) NA NA 105 (71-153) 34 262,000 

*QALY loss due to dengue caused death is not incorporated into ICER calculation.

†Range of model results due to stochasticity
Outline

• Recap of PICO questions

• Overview of models

• Comparison of results

• Exploring differences in assumptions

• QALY values used, vaccine efficacy

• Summary of Takeda model results 

• Base case

• Scenario analysis

• Model comparison summary and limitations

• Application to PICO questions
Takeda Base Case Preliminary Results

Routine vaccination at age 8

Base case conditions

• Entire population of Puerto Rico

• 20-year time horizon

• Routine vaccination at age 8

• Vaccination rate increases from 

0% at year 0 to 60% at year 4.

• Using slightly different QALY loss 

than previously presented*

Base Case

Number vaccinated 449,000

Averted cases 123,000 (15%)

Averted hospitalizations 25,000 (20%)

Averted deaths 15 (20%)

NNV hospitalization 17.6

QALYs gained 2,070

$/QALY Cost-saving

$/hospitalization Cost-saving

*Values reported in supplemental slides
Scenario Analysis

Takeda Model: Routine vaccination at age 8

*Used a fixed vaccine coverage parameter of 21.5% to approximate vaccination 

coverage that increases from 0% to 43% over 10 years.

Scenario

Number 

vaccinated

Number averted with vaccination

NNV 

hosp

QALYs 

gained

ICER 

($/QALY) Time 

(years)

TAK-003 

routine 

age

TAK-003 

catchup 

age

TAK-003 

coverage* Cases Hosp Deaths

10 8 None 22% 87,000 24,000 (6%) 4,510 (7%) 3 (8%) 19.3 402 Costsaving

10 8 9-16 22% 157,000 47,000 (12%) 9,150 (14%) 5 (13%) 17.1 838 Costsaving
Overall Cost-effectiveness

Preliminary results

 

 

 

 

 

 

 

 

 

 

Incremental Cost (in thousands)

QALYs gained
Overall Cost

-effectiveness

Preliminary results

 

 

 

 

 

 

 

 

  

 

Incremental Cost (in thousands)

QALYs gained

4-16 

w/prevaccination

screening

17-60 w/o 

prevaccination

screening

R8 

Catch-up 9-16

R17 

Catch-up 18-60
Limitations

• Parameter Uncertainty

• Large confidence interval (>100%) for DENV-3 and DENV-4 VE estimates for 

those seronegative at vaccination.

• Given vaccine’s range in serotype specific efficacy, actual outcome will 

be heavily influenced by the dominant circulating serotype.

• In the ND/CDC model, deaths were not part of the QALY calculation.

• Using Takeda’s model, we cannot assess benefits and risks of prevaccination screening strategies vs strategies without pre-vaccination 

screening.

The models summarized are currently undergoing the CDC economic review following the ACIP 

Guidance for Health Economics Studies, so results should be considered as preliminary.
Only seropositives 

(prescreening)

All individuals 

(no prescreening)

4–16 years

Children/Adolescents

Answered by ND/CDC Model Answered by ND/CDC Model

& Takeda Model

17–60 years

Adults

Answered by ND/CDC Model Answered by ND/CDC Model

& Takeda Model

Models answering the PICO Questions
Acknowledgements

• This presentation summarized work conducted by two modeling 

teams

• Notre Dame team contracted by CDC (ND/CDC Model)

• Guido España, Manar Alkuzweny, Alex Perkins

• Takeda team (Takeda Model)

• J. Shen, R. Hanley, I. Zerda*, Z. Janusz*, E. Kharitonova*, A. Rosas, A. Garcia, M. Curtis, 

M. Lu, C. Ruff, V. Tricou, M. Sharma, R. Kastner, E. Lloyd, G. Perez, S. Biswal, T. Tsai, I. 

Willits*

• Name with (*) are employed by Putnam PHMR and contracted by Takeda. All others are 

directly employed by Takeda. 

• CDC and ACIP contributors and reviewers

• Dengue ACIP workgroup

• Economists at CDC and colleagues (NCIRD/ISD)

The findings and conclusions in this presentation are those of the author(s) and do not 

necessarily represent the views of the Centers for Disease Control and Prevention.