UNICEF VACCINES ZIKA Diagnostics Demand Forecast€¦ · Forecasting model: Overview Assesses various methodologies and targeting assumptions Applies 10-year time horizon incorporating

UNICEF VACCINESZIKA Diagnostics Demand Forecast

1Jorgen Kofoed – UNICEF SD

Forecasting model: Overview

Assesses various methodologies and targeting assumptions

Applies 10-year time horizon incorporating population growth effects but assuming constant rate of disease Illustrates ramp-up period and steady-state demand volumes

Uses scale-up matrix to determine incremental country introduction timinginformed by WHO’s country risk categorization

Includes demand for government programmes, and a stockpile

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Forecasting model: Technologies included/excluded

INCLUDES Rapid Diagnostic Tests (RDT)INCLUDES Point of Care (POC) tests

• Need for simple, specific IVD for detecting ZKV in acute different biological specimens thatcan be used in screening / diagnosis (particularly for prenatal and antenatal ZKVinfections) and that can generate results quickly and in close proximity to patients

EXCLUDES Surveillance testingEXCLUDES Blood screening

• While there is guidance on use of these technologies, these have not been included in theforecast as UNICEF is not currently planning to procure these tests

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Forecasting model: Country inclusion/exclusion

INCLUDES Countries at greatest risk of outbreak and where environment is most suitable for vector (See next slides)

INCLUDES Countries likely to channel procurement through UNICEF

o Of these, currently focuses on 20 countries with largest populations ( 80% of total forecasted demand)

EXCLUDES Countries in Latin America

EXLUDES China , India and Indonesia4

Forecasting model: Country selection and Riskcategorization (I)

Country-risk categorization:The country risk category was based on current WHO classification for Zikavirus transmission and environmental suitability (Messina et al., 2016, Oxford University)

Environmental suitability (Messina et. al)

Highly suitable Limited suitability Unsuitable

Classification of Zika virus

transmission (WHO)

Countries experiencing a first outbreak of Zika virus since 2015, with no previous

evidence of circulation, and with ongoing transmission by mosquitos

4 3 1

Countries where there is evidence of Zika virus transmission prior to 2015, with or

without ongoing transmission; or countries where an outbreak since 2015 is reported

to be over

4 3 1

Countries with evidence of person-to-person transmission of Zika virus, other than

mosquito-borne transmission3 2 1

Countries where there is no evidence of Zika virus transmission

3 2 0

Likelihood of demand: 4 – very high; 3 – high; 2 - moderate; 1 – low; 0 – none 5

Forecasting model: Country selection and risk categorization (II)

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Forecasting model: Base case targeting assumptions

Target Group 1

Test ALL symptomatic population

Symptomatic population = 1% of total population (based on Dengue outbreak)

80% coverage of target group Wastage : 5%

Target Group 2

Test ALL Pregnant Women both with or without symptoms

80% coverage of target group

Wastage : 5%

BASE CASE: Combination of Target Groups 1+2

Test ALL symptomatic population AND Pregnant Women

Symptomatic population = 1% of total population (based on Dengue outbreak)

80% coverage of target groups Wastage : 5% 7

Total forecasted demand – POC machines and tests

NB: Note difference scales on two charts

NB: Model assumes that 1 POC machine will perform 1300 tests/year, over 3-years life cycle 8

Total forecasted demand – RDTs

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Total forecasted demand – All tests (RDTs and POC tests)plus Stockpile quantities

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Next steps

• Running scenarios to test model sensitivities

• Conducting country consultation (currently ongoing) to inform model parameters

•Working with UNICEF Country Offices to validate assumptions

•Working with partners to refine model and possible extend scope; e.g. to incorporate dynamic effects of disease epidemiology

• Application to inform procurement and contracting modalities11

UNICEF VACCINESTHANK YOU!

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