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Malaria Diagnosis

Enhancing the rational use of antimalarials: The cost-effectiveness of rapid immunochromatographic dipsticks in sub-Saharan Africa. Malaria Diagnosis. Current practice – presumptive treatment (WHO,1999) ACTs are expensive Misdiagnosis

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Malaria Diagnosis

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  1. Enhancing the rational use of antimalarials: The cost-effectiveness of rapid immunochromatographic dipsticks in sub-Saharan Africa

  2. Malaria Diagnosis • Current practice – presumptive treatment (WHO,1999) • ACTs are expensive • Misdiagnosis • Rapid dipstick tests are being developed for simple diagnosis WHO (1996) IMCI Information Package

  3. Study Questions • At what levels of malaria prevalence is dipstick diagnosis cost-effective? • How much should we be willing to pay for further information about model parameters before making a decision?

  4. Simple decision tree model Sensitivity Specificity PT: 100% 0% 0% 100% Dip: 86-94% 6-14% 72-99% 1-28%

  5. Probabilistic sensitivity analysis • Uncertainty around most parameters represented by lognormal and beta distributions • Incremental cost-effectiveness ratios (ICERs) calculated probabilistically using Monte-Carlo simulation • ICERs converted to net-benefit Net Benefit = Effects * λ – Costs • The ceiling ratio (λ) is US $150 per DALY averted (WHO, 1996) WHO (1996) Report of the Ad Hoc Committee on Health Research Relating to Future Investment Options

  6. Probability Cost-EffectiveCeiling Ratio = $150/DALY averted This is where a large graphic or chart can go.

  7. Incremental Net-benefit This is where a large graphic or chart can go.

  8. Calculation of EVPICeiling Ratio = $150/DALY averted

  9. EVPI according to prevalence This is where a large graphic or chart can go.

  10. Discussion • Cost-effectiveness most sensitive to • Epidemiological setting • Cost and accuracy of dipsticks • Probability patients return for treatment • Further benefits • Reduce drug pressure and development of drug resistance • Encourage use of treatment facilities • Epidemiological surveillance

  11. Limitations of the model • Assumes that health workers and patients trust and follow dipstick results • False positive diagnoses are not well defined • Does not consider private sector • Not applicable in areas where microscopy is currently in use • EVPI depends on number of variables you include in your model

  12. Further work • Conduct a EVSI analysis to determine which parameters warrant further testing • Consider parasite density, immunity, and health worker behaviour • Determine affordability of dipsticks at a national level • Predict impact on drug resistance

  13. Acknowledgements • Chris Whitty • Sarah Staedke • Shunmay Yeung • Andrew Briggs Funders: UK Department for International Development, LSHTM Health Economics and Financing Programme

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