Global Issues in Comparing Vaccination Strategies

Dr Lara Wolfson

Vaccine Assessment & Monitoring

Department of Immunization, Vaccines & Biologicals

Vaccination Strategies: WHO• Overview of work at WHO

• Examples of current work

• Unmet needs

Measuring Mortality and Morbidity1. Estimates of current disease

burden for vaccine-preventable diseases

2. Forecasts of future disease burden & cost-effectiveness under different vaccination scenarios

3. Methods and Materials to assist RO’s and countries in estimation and forecasting of disease burden, introduction of new vaccines, cost-effectiveness assessments

4. Support to users of burden of disease data, technical assistance for cost-effectiveness

Innovation

Accelerated Disease Control

Immunization Systems

Age-specific

mortality rates

5q045q15

Life tables

Complete vital

registration

Sample registration

system

Incomplete vital registration

DHS and other surveys

Censuses

No recent data

UN estimatesCause-specific

mortality patterns

Independent studies / reports /

models

Country level age, sex and cause

specific mortality estimates

UN population

estimates

Epidemiological data from studies, verbal autopsies,

WHO programme estimates (child, maternal,

injuries, non-communicable, TB,

HIV/AIDS)

All-cause mortalityenvelope by age and sex

Estimating (Total) Mortality at WHO

Vaccine-Preventable Diseases: 24%

Other76.77%

Polio0.00%

JE0.02%YF

0.05%Hib

0.68%Tetanus0.37%

Pertussis0.52%

Rotavirus0.79% Hepatitis B

1.05%Measles1.07%

Diphtheria0.01%

Malaria2.23%

TB2.75%

Diarrhoea (other)2.37%

Mening A/C0.05%

Pneumococcal2.83%

ALRI (Other)3.56%

HIV4.87%

Causes of 4.1 M Child Deaths, 2002

Measles13%

Hib9%

Rotavirus10%

Pneumococcal17%

Malaria29%

HIV9%

TB1%

Meningococcal A/C, JE

<1%

Pertussis7%

Tetanus5%

YF, Diphtheria, Polio, Hepatitis B

0%

Proportional Mortality Approaches

N oninfe c tiou s

D ia rrhoe a

C roup A c ute b ronc hitis

R S V Influe nz a

V ira l

S . p ne um onia e H ib

B a c te r ia l

P ne um onia

A R I

Infe c tiou s

O ve ra ll m orta lity

Natural History Approaches

H ib S . p ne um onia e

B a c te r ia l V ira l

U ntre a te d p ne um onia

N o a c c e ss to he a lth c a r e

T re a te d p ne um onia

A c c e ss to he a lth c a r e

Infe c te d N on infe c te d

E xp ose d U ne xp ose d

S usc e p tib le N on s usc e p tib le

P op ula tio n

Looking at all the sources of data

Method 1

Method 3Method 2

Best estimate

Prim

ary

data V

alidatio

n

Sensitivity analysis

General Approach• Get best data/information (literature/grey literature review)

• Primary data

• Secondary data

• Seek expert advise/opinion• natural history of the disease

• methods/models

• context

• Develop consultative process with ROs/countries

• Develop best methods/models

• Use best assumptions/probabilities

• Conduct sensitivity analysis

• Validate/check consistency & coherence

• Document (explicit & transparent)

• Subject to in-house review, then expert review

Expected Outputs• Burden of Disease Estimates

– By country, age group, sex, year– With estimates of uncertainty, document methods– Country consultation, continuous update of inputs

(?!?)

• "Scenarios" (aka Comparing Strategies)– Recommendations for best practice– Tools for use at country level– Provide support to advocacy efforts

• Cost-Effectiveness– Tools and guidelines, training, support

HQ produces burdenof disease estimates

Develop scenario modelsAnd database of inputs

Develop costing tools and guidelines

CountryRequests

CEA assistance

Targeted Country forField-testing

orEvaluation

Collaborate with countryOn CEA

Publish methods, databaseOf results, inputsCountry clearance

Simultaneous

IF!

Publish tools

Publish tools

Update annually

GAVI and the Vaccine Fund• 75 out of 192 member states with GNI

<$1000 eligible for support

• Immunization Systems Strengthening (ISS) support –performance/reward based system

• New Vaccine Support (NVS) – vaccine provided for 1st five years

• "Next Window" – 2005-2009

• ICF (Investment Case Framework)

The ADIP Paradigm

The Example: Measles• Need to develop a method for estimating

measles mortality and morbidity• Measure progress towards Measles Mortality

Reduction Goal (50% reduction in measles deaths from 1999-2005)

• Evaluate the impact of supplemental immunization activities (SIA’s) and routine coverage

• Develop a tool for countries to use to estimate their own disease burden and monitor progress

"Current" Burden of Measles1 1 1 2

Year i 1 1 1

1 2

All Ages Year iYear i

Age Group jYear i

1 (1 ) (1 )

Protected = (1 100% ) (1 90% )

(1 80% )

(1 Protected )

Protected <80% Protected >80

=

i i

i

VE MCV VE MCV

VE SIA VE SIA

VE SIA

Cases Births

Cases

All AgesYear i

Age Group j Age j Age Group jYear i Year i

% Age Group

12% 12% <1

65% 47% 1 to 4

18% 25% 5 to 9

4% 11% 10 to 14

1% 5% 15 to 19

Cases

Deaths Cases CFR

CFR Literature Review

CFR

0 10 20 30 40 50

New Zealand N=1Sri Lanka N=2

Marshall Islands N=1Zambia N=1Somalia N=1

Bangladesh N=6Pakistan N=1

India N=33Peru N=2

Nigeria N=1Myanmar N=3

DR Congo N=1Phillipines N=1

Burundi N=1Chad N=1

Malawi N=2Gambia N=6Senegal N=7

Zimbabwe N=1Niger N=2

Guinea-Bissau N=6Ghana N=1

Ethiopia N=1Thailand N=1

Kenya N=2

Country (N)

Summary Data (with confidence intervals): 12 to 23 Age Group

869,000 in 1999 to 610,000 in 2002

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Mill

ion

s o

f D

eath

s

Deaths Averted

Measles: Comparing Vaccination Strategies in 35 African Countries, 2005-2015

0

100

200

300

400

500

600

700

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

An

nu

al D

eath

s (

tho

usa

nd

s)

(Th

ou

san

ds)

Constant Routine Constant Routine + 2nd Opportunity Best Estimates Routine Best Estimates Routine + 2nd Opportunity (Project) Reaching 90% Routine Reaching 90% Routine + 2nd Oppportunity

SIR Model for 192 Member States ( , ) 1 ( , ) ( , ) ( , ) ( , ) ( , ) (1 ( , )) ( , )

( , ) ( , ) ( , ) ( , ) ( , ) ( , )

( , ) ( , ) ( , ) ( , ) (1 ( , )) ( , )

where

( , ) The "birth rate" (in

dS dSa t p a t a t S a t a t S a t p a t S a t

da dtdI dI

a t S a t a t I a t a t I a tda dtdR dR

a t I a t a t R a t p a t S a tda dt

a t

crease in population) of age at time

( , ) The force of infection for age group at time

( , ) The immunization rate of age group at time

( , ) The "death rate" (decrease in population) of

a t

a t a t

p a t a t

a t

age at time

( , ) The death rate (due to all causes) among those infected with

measles of age at time

( , ) The recovery rate for age group at time

a t

a t

a t

a t a t

How to calculate R0?

t

t-1

Immigrant Infections

0,

.3Density0, 0, 1 Density

1tCases

t

t

t t

Rt

Pop

where

R R

Looking at Scenarios

Disease/syndrome Lit review

Data extracte

d

Model develop

ed

Current Estimat

es

Estimates

Deaths/Cases

Averted

WHO Clearan

ce

Expert review

Methods written

Country review

process complet

ed

Manuscript submitted

Published

Measles - static modelpartial partial

completed

completed

completed

completed

completed completed    

completed

Measles - SIR model

               

Measles - prop model

         

Pertussis completed

completed

completed

completed

completed yes          

PolioNA NA    

completed

completed NA completed    

Neonatal tetanus completed                 Q1 2004

Maternal tetanus

      Q2 2004 Q2 2004         Q4 2004

Total tetanus

      Q2 2004 Q2 2004         Q4 2004

Hepatitis B

Q1 2004 Q1 2004   Q2 2004 Q2 2004         Q2 2004

Hib meningitis

            Q3 2004      

Hib pneumonia

      Q1 2004 Q1 2004 Q1 2004 Q3 2004 Q1 2004 Q3 2004

Work that is needed (urgently!!)High Priority/Some Work

Started

• Pneumococcal Disease (Meningitis, Pneumonia)

• Rotavirus• Yellow Fever• Rubella/CRS• Diphtheria

Lower Priority/Not Started

• Meningoccocus A/C• Japanese Encephalitis• Mumps• Dengue• Typhoid • Cholera • ETEC• Papillomavirus• RSV• Shigella• Streptococcus group A• Infant TB

CEADisease Costing

Tools

Costing studies completed

Costing studies in progress

Measles Yes Burkina Faso, Kenya, Tanzania, Laos, Zambia, Rwanda

Sudan, Nepal, Philippines, Afghanistan, Kazakhstan, Turkey, Kosovo

Neonatal Tetanus

Pakistan Indonesia

Hepatitis B Yes Mozambique, Mongolia

Hib Yes Moscow, Albania, Thailand

Rubella In progress Oman, Fiji, Tonga

Pneumococcal Yes South Africa, Kenya

Polio South Africa

Rotavirus In progress Ghana

Data Collected by the Global Monitoring System (VAM)

Incidence and Coverage 1980-2001 (5 yr MA)Complete Incidence Reporting Only

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Coverage

Incidence per 100,000 Population Aged 0-19 Coverage

Mixed Bag of Needs• Simple tools for use in country to make

policy decisions – but validated compared to complex methods.

• Valid assessments of current burden of disease (MDG!!)

• Guidance on plugging "data holes"

• Introduction of new vaccines