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Peer reviewedOpen accessAIDS

Modeling Scenarios for the End of AIDS

Clinical Infectious Diseases·

Viviane D. Lima, Harsha Thirumurthy, James G. Kahn, Jorge Saavedra, Carlos F. Cárceres, Alan Whiteside

DOI
10.1093/cid/ciu339
PMID
24926027
PMCID
PMC4141492
OpenAlex
W2162838583
Study type
Journal article
Publisher
Oxford University Press (OUP)
Article type
journal-article
Integrity
current

Why this research matters now

The article is relevant to HIV/AIDS control because it addresses transmission dynamics, prevention strategy, treatment coverage, and financing of the response in a setting of continuing global burden.

01

Structured evidence summary

Research question

To summarize HIV transmission epidemiology, modeling efforts in multiple settings, financing of the HIV response, and the potential role of treatment as prevention in ending the epidemic.

Study design

A brief narrative overview or review article, not an original empirical study.

Population and setting

The discussion is framed globally and refers to HIV/AIDS burden worldwide at the end of 2012, with modeling examples from different settings around the world.

Main findings

The abstract states that no cure or fully preventive vaccine was available at the time. It also reports that the global HIV burden remained high despite prevention efforts and growth in HAART coverage, and it highlights treatment as prevention as part of the forward-looking prevention agenda.

Public-health relevance

The article is relevant to HIV/AIDS control because it addresses transmission dynamics, prevention strategy, treatment coverage, and financing of the response in a setting of continuing global burden.

Important limitations

No explicit study limitations are stated in the abstract. This summary is therefore limited to the supplied single-article abstract and metadata; the original paper is needed for decision-grade interpretation.

GIDS interpretation

This is a contextual review article that is discoverable as background evidence on HIV/AIDS modeling and prevention themes. It should not be treated as surveillance data or as confirmation of a live signal.

02

Related GIDS surveillance

Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.

03

Evidence relationships

This article has 10 auditable classifier relationships to diseases, places, topics, and study design.

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