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Enhancing the rational use of antimalarials: The costeffectiveness of rapid immunochromatographic dipsticks in sub-Saharan Africa 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 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? Simple decision tree model Suspected malaria Malaria True Positive False Negative Sensitivity No Malaria True Negative False Positive Specificity PT: 100% 0% 0% 100% Dip: 86-94% 6-14% 72-99% 1-28% 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 Probability Cost-Effective Probability cost-effective Ceiling Ratio = $150/DALY averted 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% This is where a large graphic or chart can go. 0% 20% 40% 60% Malaria Prevalence 80% 100% $40 $20 -$40 -$60 -$80 Malaria Prevalence 10 0% 80 % 70 % 60 % 50 % 40 % 30 % 20 % This is where a large graphic or chart can go. 10 % -$20 90 % $0 0% Incremental Net Benefit Incremental Net-benefit Calculation of EVPI Ceiling Ratio = $150/DALY averted Iterations Net Benefit Dipsticks Net Benefit PT Net Benefit WPI 1 $40 $20 $40 2 $20 $25 $25 3 $35 $25 $35 4 $25 $30 $30 Average $30 $25 $32.50 EVPI = $32.50 - $30 = $2.50 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% $2.50 $2.00 EVPI per person Probability costeffective EVPI according to prevalence Probability This is where a large graphic$1.50 or chart can go. cost- $1.00 $0.50 0% $0.00 20% 40% 60% 80% 100% Malaria Prevalence effective EVPI per per person 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 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 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 Acknowledgements Chris Whitty Sarah Staedke Shunmay Yeung Andrew Briggs Funders: UK Department for International Development, LSHTM Health Economics and Financing Programme