Cost-utility analysis of strategies to
combat Malaria in developed countries
(Chantal M. Morel, Jeremy A. Lauer, David B. Evans, BMJ,
doi:10.1136/bmj.38639.702384.AE (published 10 November 2005))
Presented by Nelly BIONDI, SACEMA
Makerere University, 24th July 2009
Background
•
Each year more than 1 million people, mostly children and pregnant
women die from malaria worldwide.
•
Most of these deaths could be averted, as effective and affordable ways
to prevent and treat malaria exist.
•
It is important to ask whether current interventions are used
appropriately and what is the most cost-effective way to scale-up
prevention and treatment activities to the levels needed.
•
The autors used a cost-utility analysis to examine the costs and the
effects of scaling-up seven interventions against malaria and their
promising combinations.
2
Methods
Geographical focus
•
90% of deaths from malaria
occur in sub-Saharan Africa.
•
Focus on 2 sub-Saharan African
regions: Afr-E (predominantly
Southern and Eastern Africa)
and Afr-D (predominantly
Western Africa).
•
Both regions are predominantly
areas with endemic high
transmission of malaria due to
Plasmodium falciparum.
4
Interventions
•
A limited number of means are available to fight malaria:
5
Population at risk and coverage
•
Interventions were evaluated at 50%, 80% and 95% target coverage to
allow for unit costs and effectiveness that may vary with coverage.
•
Effective coverage = target coverage x population at risk.
•
Region-wide estimates of population at risk (proportion living in a
malaria endemic areas) based on country specific figures.
– 98% for Afr-D
– 69% for Afr-E
•
Estimates of current coverage were used for calculating the null
scenario.
6
Current coverage
7
Estimating the net effectiveness
of interventions
•
The net efficacy of bed nets and indoor spraying were expressed as a
reduction in incidence and thereby a reduction in mortality modelled
through case fatality (table 2).
•
The net effectiveness of treatment was estimated taking into account:
– Patients’behaviour (adherence to regimen)
– Pharmacokinetics (probability of success when the regimen is not followed)
– Biogenetics (resistance of the parasite to the drug).
•
These factors determine the number of expected failures which we
substracted from a common baseline of 98% efficacy (table 3).
•
The net effectiveness of bed nets, but not spraying was reduced to
account for imperfect adherence.
8
Baseline efficay
9
Net efficacy of the interventions
10
Population Model
•
The model combines estimates of incidence, prevalence and mortality
with estimates of prevalence (table 5) and severity from the burden of
disease study to project the population impact of intervention scenarios
in terms of healthy years of live lived.
•
Differences in total population healthy years under the intervention and
baseline scenarios are expressed as DALYs averted.
11
Estimating the costs of
interventions
•
Estimated costs measure the value of resources needed to provide the
intervention and are expressed in international dollars.
•
Costs were calculated in the light of experience from effectiveness
trials, existing literature and expert opinions.
•
Costs were classified by programme costs or patient costs. Training
costs were assumed to be a substancial part of malaria interventions so
they have been reported separatly from programme costs.
•
The CostIt model (WHO,2002) was used to aggregate cost components
and total costs for the 10 year implementation horizon.
12
Cost profile Afr-D
13
Cost profile for Afr-E
14
Results
Cost-effectiveness estimates
16
Cost-effectiveness planes
17
Cost-effectiveness planes
18
Incremental and average costeffectiveness ratios
19
Incremental and average costeffectiveness ratios
20
Conclusion
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The end…