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DOI 10.3934/mbe.2026084

Медицинская библиотека · Mathematical biosciences and engineering : MBE · 2026

Why accurate risk stratification matters in HIV population modeling.

Dimitrov Dobromir, Matrajt Laura, Ren Xinze, Stansfield Sarah E, Moore Mia

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Аннотация

Accurate representation of behavioral risk heterogeneity significantly influences the projections of Human Immunodeficiency Virus transmission models without receiving the deserved attention when models are structured. As a result, models widely vary in how they stratify risk and how individuals progress through risk groups. We systematically evaluated how these two structural features-the number of risk groups and assumptions about risk progression (comparing three mechanisms of fixed, age-based, or mixed risk)-shape epidemic projections. Using deterministic HIV models stratified by HIV stage and behavioral risk, we simulated populations over 250 years under standardized initial conditions. Our results show that risk-progression mechanisms strongly influence long-term epidemic behavior. Fixed-risk models gradually shift the population toward lower-risk groups, thus reducing HIV incidence over time. In contrast, age-based progression sustains a larger high-risk population and produces a substantially higher long-term incidence, while mixed progression yields intermediate outcomes. The granularity of risk stratification further modifies the projections: models with more risk groups generate significantly different incidence trajectories and equilibrium population sizes under age-based and mixed progression, whereas fixed-risk models produce similar long-term results with a different number of risk groups. These findings highlight that both risk-progression assumptions and the level of stratification can meaningfully alter HIV forecasts. Therefore, the careful treatment of population risk heterogeneity is essential to generate reliable projections and to guide intervention strategies.

Для цитирования: Dimitrov Dobromir, Matrajt Laura, Ren Xinze, Stansfield Sarah E, Moore Mia. Why accurate risk stratification matters in HIV population modeling.. Mathematical biosciences and engineering : MBE. 2026. DOI: 10.3934/mbe.2026084.

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