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Record W2171639414 · doi:10.1001/jama.286.15.1886

Do Patents for Antiretroviral Drugs Constrain Access to AIDS Treatment in Africa?

2001· article· en· W2171639414 on OpenAlexaff
Amir Attaran

Bibliographic record

VenueJAMA · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIntellectual propertyMarket accessScarcityDeveloping countryAccess to medicinesDe factoAntiretroviral treatmentBusinessUniversal designHuman immunodeficiency virus (HIV)Economic growthDevelopment economicsInternational tradeMedicinePolitical scienceAntiretroviral therapyGeographyEconomicsVirologyLaw

Abstract

fetched live from OpenAlex

Public attention and debate recently have focused on access to treatment of acquired immunodeficiency syndrome (AIDS) in poor, severely affected countries, such as those in Africa. Whether patents on antiretroviral drugs in Africa are impeding access to lifesaving treatment for the 25 million Africans with human immunodeficiency virus infection is unknown. We studied the patent statuses of 15 antiretroviral drugs in 53 African countries. Using a survey method, we found that these antiretroviral drugs are patented in few African countries (median, 3; mode, 0) and that in countries where antiretroviral drug patents exist, generally only a small subset of antiretroviral drugs are patented (median and mode, 4). The observed scarcity of patents cannot be simply explained by a lack of patent laws because most African countries have offered patent protection for pharmaceuticals for many years. Furthermore, in this particular case, geographic patent coverage does not appear to correlate with antiretroviral treatment access in Africa, suggesting that patents and patent law are not a major barrier to treatment access in and of themselves. We conclude that a variety of de facto barriers are more responsible for impeding access to antiretroviral treatment, including but not limited to the poverty of African countries, the high cost of antiretroviral treatment, national regulatory requirements for medicines, tariffs and sales taxes, and, above all, a lack of sufficient international financial aid to fund antiretroviral treatment. We consider these findings in light of policies for enhancing antiretroviral treatment access in poor countries.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.129
GPT teacher head0.336
Teacher spread0.207 · 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 designNot applicable
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

Citations11
Published2001
Admission routes1
Has abstractyes

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