CHAI HIV Diagnostics Market Forecasts - · PDF fileCHAI HIV Diagnostics Market Forecasts ......

CHAI HIV Diagnostics Market Forecasts Diagnostic Manufacturers and Stakeholders Meeting

April 2015

Agenda

• Viral Load

• Early Infant Diagnosis (EID)

• Introduction

• CD4

CHAI’s global diagnostics forecasts provide market intelligence to suppliers

- Source -

• Country and WHO-reported patient numbers

• Country testing guidelines and scale-up plans

• Assumptions regarding market dynamics (i.e., timing of introduction of POC, actual scale-up rates)

- Goal -

• Share with suppliers to inform them of existing demand and expected future market trends with the objective of lowering production risks and informing country support strategies

• Leverage projected volumes to promote volume-based discounts and commodity bundling where appropriate

Global diagnostics forecasts and other intelligence

21 high-burden

countries

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Demand-based Forecasts

Market Forecasts

CHAI collects data annually from country teams, which is used to inform forecasts and program planning

Annual Labs Data Request: Completed annually by country teams and incorporated within updated forecasts and market intelligence. Includes information related to guidelines, testing volumes, targets, installed equipment base, funding, and scale-up plans for CD4, EID, VL, and TB diagnostics.

Additional data collection: CHAI teams also collect data more frequently on specific topics, such as viral load scale-up (collected quarterly) and POC implementation (collected semi-annually)

CHAI uses linear extrapolations of historical data in its forecasts to project future demand

Collection of Patient and

Test Numbers

Calculation of Testing

Need Modeling

Testing Forecast Volume & Value

• ART and Pre-ART patients data (CD4 and VL)

• Number women living with HIV/AIDS

• Reported numbers of exposed and positive infants

• Historical test volumes (by test and sample type)

• Patient numbers

• Burden of disease

• Existing national guidelines for testing

• Global targets

Linear extrapolation of past demand or model of future scale-up influenced by:

• Current system capacity

• Introduction of new technology

• Funding

• Anticipated guidelines changes

• Forecast outputs by sample type (POC vs. conventional), country and test type

• Ex-works prices for POC and conventional reagents or test cartridges to demonstrate market value

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Creating demand-based forecasts requires robust historical records of testing volumes, as well as an in-depth understanding of country scale-up plans.

Agenda

• Viral Load


• Introduction

• CD4

The CD4 forecast can be modeled using high and low-growth scenarios driven by the pace of POC adoption and shift of ART monitoring to VL

Source: CHAI CD4 forecast, with laboratory-based testing volumes based on CD4 testing coverage data from 21 high HIV-burden countries Excludes money spent to expand install base of instruments

The largest increase in CD4 test volumes will be driven by the adoption of POC devices, including device-free technologies, in either scenario.

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CD4 Forecast Scenarios, 2013-2018

High Low Percent of Volumes for POC (High) Percent of Volumes for POC (Low)

The CD4 forecast relies on reported patient numbers, changes to the guidelines, and historical test volumes to project future demand


Test Numbers


Need Modeling


• Country and WHO-reported ART patient numbers

• Country-reported Pre-ART numbers where available

• Country-reported Pre-ART: ART patient ratios

• Test volumes

• Testing guidelines

• Coverage of viral load for ART monitoring by country

• Additional testing required for monitoring for opportunistic infections

• Historical volumes disaggregated by staging vs. monitoring

• Volumes also disaggregated by sample type (POC vs. conventional)

• Baseline coverage for conventional testing at 50% of need

• Different growth rates assumed for each sample type

• Forecast outputs by sample type (POC vs. conventional) and country


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Underlying assumptions for forecast (1 of 2)

Patient Numbers: The model uses patient numbers from the annual CHAI forecast for ART scale-up in 21 high-burden countries, which are generated using linear extrapolations from historical growth trends. It also uses approximate Pre-ART ratios shared by countries to estimate the total number of patients in care on a country by country basis.

Aggregated Pre-ART: ART Patient Ratios:

East Africa: 1.1 : 1 West Africa: 1.4 : 1

Southern Africa: 1.3 : 1 Rest of World: 1.2 : 1

Impact of viral load scale-up: ART patients are gradually transitioned from CD4 to VL in the model. The rates of transition differ by country and are based on scale-up plans.

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% of ART Patients Using CD4 2014 2015 2016 2017 2018

South Africa 0% 0% 0% 0% 0%

East Africa 82% 74% 57% 27% 10%

Other Southern Africa 64% 56% 32% 14% 0%

West Africa 91% 90% 50% 25% 0%

Rest of World 88% 85% 65% 29% 5%


Defining need:

• Need is defined as the total number of patients requiring CD4 testing annually multiplied by the national CD4 testing guidelines.

• An additional 5% of patients are assumed to require clinician-requested CD4 tests for opportunistic infections.

• Need also accounts for the gradual transition of ART patients from CD4 to viral load. For these patients, two tests annually are assumed.

Modeling forecasted tests:

• Baseline is 2013 testing volumes disaggregated by Point of Care (POC) and conventional tests.

• Where data unavailable for conventional testing, coverage of 49% of need assumed.

• For conventional testing, an annual growth rate of 5% is applied. Growth in POC is assumed to occur at a higher rate and is presented in two scenarios.

• In both scenarios, POC device-free instruments are expected to be introduced beginning in 2016.

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CHAI uses a variety of sources including country reports and publically available information to generate the forecasts

Data Points (by country) Data Sources Available Identifying Sources

ART population WHO TUAPR

Pre-ART population CHAI country teams

ART Guidelines Country guidelines WHO guidelines

POC volumes and forecasts Country purchases CHAI country teams

Conventional testing volumes and forecasts

CHAI country teams

Current CD4 Testing ART reports CHAI country teams

Testing volumes for staging vs. monitoring

CHAI country teams

Funding outside of UNITAID

Global Fund proposals, PEPFAR COPs, Govt. budgets

Country uptake of guidelines, funding, and the adoption of cost-effective POC devices may further influence growth in this segment

Potential Market Event Magnitude of Impact

Timing

Less gradual shift from CD4 ART Monitoring to viral load than anticipated

(-) Large 1-3 years

Introduction of device-free technology (+) Medium 1-3 years

Adoption of test and treat (-) Large 3-5 years

Agenda

• Viral Load


• Introduction

• CD4

Even with increased funding and national scale-up of viral load, there will still be a significant unmet need

The forecasted testing gap is a factor of funding, country support for widespread scale-up, challenges in extending access beyond existing sample transportation systems, and the

speed of clinical uptake.

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Note: Need is estimated using projected ART patient numbers and testing guidelines.

CHAI’s viral load forecast relies on country-reported patient numbers, scale-up plans, and historical test volumes to project future demand


Test Numbers


Need Modeling


• Country and WHO-reported ART patient numbers

• Testing volumes

• National testing guidelines

• Percent of patients requiring repeat tests

• Historical volumes disaggregated by sample type (DBS/POC vs. plasma)

• High, medium, and low-growth coverage rate scenarios based on EID scale-up rates in UNITAID countries

• Timeline for introduction of new technology

• Forecast outputs by sample type (POC vs. conventional) and country


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Patient Numbers: The model uses patient numbers from the annual CHAI forecast for ART scale-up in 21 high-burden countries, which are generated using linear extrapolations from historical growth trends.

Rate of transition from CD4 monitoring: ART patients are gradually transitioned from CD4 to VL in the model. The rates of transition differ by country and are based on (1) the existence of a national viral load program; (2) current scale-up plans; and (3) available funding.

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% of ART Patients Using VL 2014 2015 2016 2017 2018

South Africa 100% 100% 100% 100% 100%

East Africa 18% 26% 43% 73% 90%

Other Southern Africa 36% 44% 68% 86% 100%

West Africa 9% 10% 50% 75% 100%

Rest of World 12% 15% 45% 71% 95%


Defining need:

• Need is defined by the total number of patients expected to receive ART monitoring in a country and the country’s guidelines.

• Clinician-requested tests for patients suspected of treatment failure are also factored into the total need at an additional five percent.

• ART patients in most countries are assumed to require at least one viral load test annually.


• The forecasting model uses 2013 historical test numbers disaggregated by DBS and plasma tests sourced from CHAI country teams and publically-available sources.

• The model assumes that POC testing will begin to be available in 2015.

• Varying rates of scale-up based on country experiences with EID testing have been used to determine annual testing growth across viral load sample types, with plasma experiencing the slowest growth and POC the most rapid.

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In a changing landscape CHAI is continuing to invest in updated viral load scale-up information and supporting data


ART population WHO TUAPR

ART Guidelines Country guidelines WHO guidelines

Testing volumes and forecasts

Country purchases CHAI country teams

Country scale-up plans ART reports CHAI country teams Country implementation plans

Funding Global Fund proposals, PEPFAR COPs Government budgets

The pace of growth within the viral load market segment may be affected positively by various policy decisions

Note: PMTCT stands for the Prevention of Mother-to-Child Transmission of HIV


Timing

Increased funding to achieve 90-90-90 targets

(+) Large 1-2 years

Introduction of more stringent DBS standards for correlation with plasma by WHO

(+/-) Medium, supplier dependent

1-2 years

Lack of availability of cost-effective POC technologies for viral load

(-) Medium, POC only

1-3 years

Further increase in CD4 threshold for ART initiation

(+) Large 3 years

Adoption of test and treat (+) Large 5+ years

Agenda

• Viral Load


• Introduction

• CD4

EID coverage may fall short of the total need for testing based on current funding, country plans, and market conditions

Market Trends

• Coverage of EID remains low in most countries due to poor patient retention, weak sample transport systems, and a lack of training in recognizing exposed infants outside of PMTCT care

• Viral load uptake will continue to drive investment in strengthening sample transportation networks, which may also lead to more modest gains in EID volumes

Note: Need is estimated using national population figures, HIV prevalence rates, birth rates, and testing guidelines.

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CHAI’s EID forecast relies on historical test volumes to project future demand


Test Numbers


Need

Modeling Testing Forecast Volume & Value

• Number of women of reproductive age living with HIV

• Reported historical number of exposed and positive infants

• Testing volumes

• Testing guidelines

• Anticipated guidelines changes

• MTCT rates

• Split of current tests between 1st vs. 2nd or final DNA-PCR

• Projected number of positive infants

• Timeline for introduction of testing at birth

• Timeline for introduction of POC

• Forecast outputs by sample type (POC vs. conventional), test type, and country


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Underlying assumptions for forecast

Defining Need:

• Need is defined by the estimated number of exposed and positive infants born in a country each year multiplied by the number of DNA-PCR tests required per year for each infant.

• To estimate the total number of exposed infants, the historical change in the reported need for EID as well as the change in disease burden among women aged fifteen and older in each country is applied to 2013 reported need values to project linear growth through 2020.


• To forecast demand, historical EID test numbers, segmented by test type, are grown linearly using historical CAGRs.

• The model assumes that testing at birth will be introduced beginning in 2016 in addition to the 4-6 week DNA-PCR test.

• The model also assumes that countries will begin deploying POC EID in 2015.

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More robust data exists for EID than other HIV diagnostics, but there is opportunity for further data validation


Number of exposed and positive infants

WHO CHAI country teams Global Plan

Testing Guidelines Country guidelines WHO guidelines

Testing volumes Country purchases CHAI country teams UNICEF reports Global Plan reports

Funding Global Fund proposals, PEPFAR COPs Government budgets

The growth rate and size of the EID market may be influenced positively by several key factors

The largest constraint to improved EID coverage is the large loss-to-follow-up rates for infants whose mothers are in PMTCT programs, as well as a significant number of

exposed infants whose mothers are not in care.


Timing

Improved intervention models for mother-infant retention

(+) Large Varies by country

Increased funding (+) Large 1-5 years

Availability of cost-effective POC technologies

(+) Large 1-3 years

Adoption of testing at birth: (+) Large 2-3 years

Future forecasts would benefit from further data validation and comparisons with available funding

• CHAI’s forecasts should be validated by available country procurement plans and supplier sales information

• Moreover, further analysis could be conducted to verify the validity of country scale-up plans versus anticipated funding

• The regular exchange of procurement information among partners could significantly strengthen the quality of these forecasts

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