Estimating the Global Health Impact of Improved Diagnostic Tools

1. Estimating the Global Health Impact of Improved Diagnostic Tools Jeffrey Wasserman Federico Girosi Emmett Keeler November 2006, April 2007

2. Outline • Introduction to Diagnostic Tools Project for BMGF • Better diagnosis might reduce the burden of disease • Modeling the Benefits of New Diagnostics • Basic approach • Key issues and decisions • Findings • Benefits of New Diagnostics for Tuberculosis • Selected Findings from Other Diseases

3. The Burden of Disease Remains Large in the Developing World Annual Deaths Worldwide* HIV/AIDS Tuberculosis Child respiratory Child diarrhea Malaria 0 1,000,000 2,000,000 3,000,000 * World Health Organization, 2003 (HIV) and 2002 (all others)

4. Diseases Are Concentrated in Some Regions Asia Africa LatinAmerica

5. Diagnosis Many Factors Might Contribute to Improved Health Outcomes in the Developing World Nutrition Lifestyle GoodHealth Clinical Care Public HealthPrograms Treatment

6. How Better Diagnostics Could Help • More accurate tests could help target therapy to those who need it and eliminate wasteful treatments • Earlier diagnosis could allow therapy to start sooner, reducing impact on the individual and reducing spread of the disease • Simpler, easy-to-use tests could help increase access to diagnostics to those who currently have no care

7. Tests often require advanced infrastructure High-performing tests are expensive Some existing tests are inadequate and slow Cultural and political considerations may impede acceptance Needs may vary across countries But Barriers Exist to Using Many Current Diagnostic Tools in Resource-Poor Countries

8. We were asked two Key Questions What are the global health benefits of better clinical diagnostic tools? What performance specifications and infrastructure requirements does a test need to achieve the estimated benefits?

9. Outline • Introduction • Better diagnosis might reduce the burden of disease • Modeling the Benefits of New Diagnostics • Basic approach • Key issues and decisions • Findings • Benefits of New Diagnostics for Tuberculosis • Selected Findings from Other Diseases

10. The Forum’s Role Provide expertise on relevant diseases, diagnostic needs, emerging technologies Identify key intervention points for each disease Refine the approach for assessment Serve as conduits to the broader scientific community We Worked with the Gates Foundation to Create a Global Health Diagnostics Forum Forum Working Groups Tuberculosis Malaria HIV and Sexually-TransmittedDiseases Acute Lower Respiratory Infections Diarrheal Diseases

11. Difference in outcomes = Gains from improved diagnostic tests Healthoutcomes With new diagnostic test Model for calculating benefits of new Test Healthoutcomes Status quo • Population characteristics • Health status • Access to diagnostics and treatment

12. Access to a New Diagnostic Depends on the Level of Infrastructure Available Advanced/Moderate Minimal None • Hospitals and urban clinics • Electricity, clean water, well-equipped laboratories, trained clinicians • Health clinics (Africa), rural clinics (Asia, Latin America) • No reliable electricity or clean water, no laboratory, minimal expertise • Village or community • No electricity, clean water, physical infrastructure, or trained staff

13. Characteristics of potential new tests • Accuracy = sensitivity, specificity • Access • Time to diagnosis ( related to loss to follow-up) • Cost of equipment and operation • Other (specimen type, multiplex diseases….)

14. Outline • Introduction to Diagnostic Tools Project for BMGF • Better diagnosis might reduce the burden of disease • Global Health Diagnostics Forum • Modeling the Benefits of New Diagnostics • Basic approach • Key issues and decisions • Findings • Benefits of New Diagnostics for Tuberculosis • Selected Findings from Other Diseases

15. Key modeling issues and decisions • Get intervention points from experts or models? • Decision trees are good for studying diagnostic tests • Static vs. Epidemic Models, future trends • What about costs, especially of over-treatment? • Potential vs probable access, diffusion • Where can we get data to populate the models?

16. Static or dynamic models • For TB and HIV, state of the art is dynamic models: people flow between states according to diff. equations, researchers calculate long-run policy impacts. • states: no disease, treated early dis., untreat dis.,… • decision trees give some parameters for models • An alternative is static decision trees: calculate costs and effects in one year, with incidence assumed unaffected by new DX tool. • long run effects ~ proportional to one year effects • our main interest is comparative performance • transmission handled by multipliers • Static model can be used for all five diseases • Simpler method allows us to do project with limited time and money.

17. 2 If k = 2 1 0 Each case infects kn-1 others Susceptible people Sn-1 Sn Epidemics Let Sn be the number of cases in generation n The difference equations Sn = Function(Sn-1, other “n-1” conditions) show how the system evolves over the generations.

18. A dynamic model:Diseases in Equilibrium (TB) cures Healthy TB Death Active TB 20 Latent TB p? Each active case “infects” about 20 people on average. - they then have latent TB, but a few progress Some active cases are cured, some die A generation is ~ 4 years from activation to resolution If Disease is in equilibrium, what % p of latent cases progress to be active each generation? What happens if a higher % progresses? New diagnostic tool affects the transitions from active TB.

19. What are the costs of over-treatment? • BMGF said not to consider costs, but… • If no cost of treatment, no need for Dx, just treat all equivocal patients. • What are the costs? • Side-effects of treatment • Possible super-germs? • Opportunity costs

20. Methods to calculate C = cost*of over-treatment • Ask panel of experts: identifying one more person with TB justifies the costs of tagging N more people who don’t have TB as having it? • Use opportunity costs of wasted money, assuming we can save a life by spending $x on another program. • Girosi: Use treatment guidelines to bound C • If we don’t treat when p(dis) < Pmin • then C > lower bound L • If we treat whenever p(dis)>Pmax • then C < upper bound U * This cost is called the Harm in Hunink.

21. Girosi’s Method to calculate C = cost of over-treatment (2) • Girosi: Often, recommended treatment involves a test and then only the positives get treated. for ARI it’s a clinical judgment with TPR = .9, TNR =.7, the benefit of treatment = .2 -.1 = .1 death averted, and prior p =.015. • costs of treating everyone = H(1-p)~H • costs of treating no one = Bp • costs of following clin judgment: (1-.9)pB + (1-.7) (1-p)H • If the last is best .1pB +.3H <H and also <pB. • So .7 H> .1pB and .3H<.9pBm so pB/7<H <3pB. So H=pB is a reasonable guess. H = .015x.1 = .0015

22. Potential vs Actual access • Actual: people currently being tested for disease X in Level L facilities • Potential: people who could get to a facility of level L with a certain amount of time and effort • We used potential: • with better tests and treatment, demand would rise • thinking about the post diffusion future • Fit potential access using geographic data from a few countries, and data on actual access to TB clinics in a regression and estimate for all countries of interest.

23. Data Problems • Models need incidence of disease of interest, incidence of seeking treatment for symptoms, outcomes of treated and untreated cases, accuracy of status quo tests • Future test characteristics can be whatever we choose.

24. Outline • Introduction • Better diagnosis might reduce the burden of disease • Modeling the Benefits of New Diagnostics • Basic approach • Key issues and decisions • Findings • Benefits of New Diagnostics for Bacterial Lower RI • Selected Findings from Other Diseases

25. Respiratory Infections Are the Leading Cause of Childhood Mortality • Respiratory infections contribute to the deaths of more than 2 million children each year, mostly in Africa and Southeast Asia • Most of these 2 million children die of bacterial pneumonia, which is treatable with antiobiotics • In developing countries, the main form of diagnosis is clinical assessment • A large number of children are not being diagnosed, while others are being treated unnecessarily, leading to wasted treatments and antibiotic resistance

26. Disease Yes SurvivesDies Test + Treat Disease No SurvivesDies Disease Yes Test – No Treat SurvivesDies Disease No SurvivesDies We Modeled the Status Quo and Access to a New Test for Bacterial Pneumonia in Children Under 5 Access toclinical diagnosis StatusQuo Self-treat No care Child withsymptoms Access to new test New Test No accessto new test

27. We Traded Off Test Performance and Infrastructure Requirements Good Performance PerfectPerformance Advancedinfrastructure Minimalinfrastructure *Results assumeaccess totreatment Lives saved by new test forbacterial pneumonia*

28. Significantgains,potentiallyachievable 405,000 Easier Tests Produce Large Health Benefits, Even with Less Than Perfect Performance Good Performance PerfectPerformance Advancedinfrastructure 142,000 261,000 596,000 Minimalinfrastructure *Results assumeaccess totreatment Lives saved by new test for bacterial pneumonia*

29. Our Recommendations for a New Diagnosticfor Bacterial Lower Respiratory Infections • Requires minimal infrastructure • Preferred samples types include saliva, urine, or dried blood spot • Results should be available within 2 hours or less

30. Much of the Benefit of the New Diagnostic Would Be Due to Reductions in Overtreatment Benefits of New Test forBacterial Pneumonia With C = .001 ! Reductionin overtreatment Reductionin diseaseburden LivesSaved(1000s) Developing World

31. Most Lives Saved from Reducing Disease Burden Accrue to Africa, While Other Regions Benefit from Reducing Overtreatment Benefits of New Test forBacterial Pneumonia Benefits of New Test by Region Reductionin overtreatment Reductionin overtreatment Reductionin diseaseburden Reductionin diseaseburden LivesSaved(1000s) Africa Asia Latin America Developing World

32. All Disease Models Show a Significant Benefit from New Diagnostics Lives Saved Annually from New Forum-Recommended Tests Bacterialpneumonia Children under age 5 Children under age 5 (Africa) Malaria Pregnant women (Africa) Syphilis Adults with persistent cough TB 0 500,000 1,000,000 1,500,000 2,000,000 Additional benefits were found for other diseases studied

33. Study Findings Highlight Other Themes • Tests that are more accessible have greater benefits • Access can be more important than test performance • For many diseases, a more accurate test is not needed • For example, current rapid tests for malaria could lead to significant benefits if made more widely available • Current diagnostics do not pay enough attention to harm of overtreatment • Tests are typically better at identifying people with disease than identifying those without • Reducing overtreatment provides a public health benefit