ArticleJournal of acquired immune deficiency syndromes (1999)2024
The AIDS Epidemic Model 2023 for Estimating HIV Trends and Transmission Dynamics in Asian Epidemic Settings.
Article in Journal of acquired immune deficiency syndromes (1999), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- HIV Pre-Exposure Prophylaxis Service Cascade and Risk Factors Associated with Loss to Follow-Up Among Key Populations in Indonesia: Data from a Real-World Pilot Implementation 2021-2023.AIDS and behavior · 2026Article
- HIV incidence and adherence after pre-exposure prophylaxis initiation in key populations in Indonesia: Findings from a real-world pilot program 2021-2023.IJID regions · 2025Article
- Including transgender populations in mathematical models for HIV treatment and prevention: current barriers and policy implications.Journal of the International AIDS Society · 2024Article
- Updated Data and Methods for the 2023 UNAIDS HIV Estimates.Journal of acquired immune deficiency syndromes (1999) · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundThirteen Asian countries use the AIDS Epidemic Model (AEM) as their HIV model of choice. This article describes AEM, its inputs, and its application to national modeling.
settingAEM is an incidence tool used by Spectrum for the Joint United Nations Programme on HIV/AIDS global estimates process.
methodsAEM simulates transmission of HIV among key populations (KPs) using measured trends in risk behaviors. The inputs, structure and calculations, interface, and outputs of AEM are described. The AEM process includes (1) collating and synthesizing data on KP risk behaviors, epidemiology, and size to produce model input trends; (2) calibrating the model to observed HIV prevalence; (3) extracting outputs by KP to describe epidemic dynamics and assist in improving responses; and (4) importing AEM incidence into Spectrum for global estimates. Recent changes to better align AEM mortality with Spectrum and add preexposure prophylaxis are described.
resultsThe application of AEM in Thailand is presented, describing the outputs and uses in-country. AEM replicated observed epidemiological trends when given observed behavioral inputs. The strengths and limitations of AEM are presented and used to inform thoughts on future directions for global models.
conclusionsAEM captures regional HIV epidemiology well and continues to evolve to meet country and global process needs. The addition of time-varying mortality and progression parameters has improved the alignment of the key population compartmental model of AEM with the age-sex-structured national model of Spectrum. Many of the features of AEM, including tracking the sources of infections over time, should be incorporated in future global efforts to build more generalizable models to guide policy and programs.
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