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Record W1908748014

The Economic Benefits of Malaria Prevention: A Contingent Valuation Study in Marracuene, Mozambique

2003· article· en· W1908748014 on OpenAlexvenueno aff
Dale Whittington, Armando Castelar Pinheiro, Maureen Cropper

Bibliographic record

VenueWorld health & population · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsContingent valuationMalariaWillingness to payRespondentSocioeconomicsRevenueEnvironmental healthCost–benefit analysisEconomic costEconomicsGeographyMedicineBiologyPolitical scienceEcology
DOInot available

Abstract

fetched live from OpenAlex

A contingent valuation (CV) survey was conducted in Marracuene Mozambique a very low-income malaria-endemic community about 50 kilometers north of Maputo to estimate adults’ perceived economic benefits of avoiding malaria. Interviews were conducted with 282 individuals in which respondents were asked whether they would purchase a hypothetical malaria vaccine that would prevent malaria for one year if it cost them a specified price. The average respondent’s willingness to pay to avoid the (high) risk of contracting malaria for one year was approximately US$14 equivalent to about seven chickens in the local economy. Their responses to these CV questions suggest that the economic benefits to even very poor individuals are larger than many observers have assumed and that the potential revenues available from low-income rural communities may be substantial. The estimates of the average adult’s willingness to pay for the malaria vaccine are the three to four times higher than estimates based on a simple cost-of-illness approach. (authors)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.125
GPT teacher head0.296
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2003
Admission routes1
Has abstractyes

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