ArticleHIV/AIDS (Auckland, N.Z.)2026
The Future of Newly Diagnosed HIV Cases in Iran Through 2030: A Mixed-Methods Trend Impact Analysis.
Article in HIV/AIDS (Auckland, N.Z.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Despite substantial progress in the global HIV response, the MENA region continues to face important challenges in HIV prevention and control. In Iran, fluctuations in the number of newly diagnosed HIV cases indicate an ongoing public health challenge and underscore the need to anticipate factors that may shape future diagnosis patterns. Methods: This study applied Trend Impact Analysis (TIA) to develop conditional projections of newly diagnosed HIV cases in Iran through 2030. Monthly surveillance data from 1998 to 2023 were modeled using an ARIMA(2,0,2) to establish a baseline trend which was subsequently modified through TIA based on expert-informed estimates of the timing and magnitude of key drivers. A panel of 30 experts in HIV/AIDS, epidemiology, public health, and health policy identified and assessed key drivers that could influence future trends. Expert- informed estimates of the timing, magnitude, and persistence of impacts, were then incorporated into the baseline projection to construct alternative future scenarios. Results: Expert panels identified 13 key drivers: eight adverse influences, including conflict risk, increased sex work, new stimulant drug use, online sexual platforms, socioeconomic crises, emerging epidemics, developing sex tourism, and HIV drug resistance, expected to increase the future number of newly diagnosed HIV cases. Conversely, five positive influences, including AI healthcare, effective vaccination access, efficient surveillance toward the 95-95-95 objectives, PEP/PrEP implementation, and advanced therapies, expected to reduce the future number of newly diagnosed HIV cases. Quantitative estimates project 1698 new cases if current trends persist. Under optimistic scenarios, cases may decline by 51%, whereas pessimistic scenarios suggest an increase of 102%. The integrated TIA scenario projected an approximately 51% increase in newly diagnosed HIV cases by 2030, reaching 2558 cases by 2030, with an approximate 95% uncertainty interval of 2120-2996 (±2 SD). Conclusion: The scenario projections represent conditional future trajectories based on specified assumptions about the impact of different key drivers, The scenarios illustrate substantial uncertainty in the future number of newly diagnosed HIV cases in Iran, with scenario estimates ranging from approximately a 50% decrease to a 100% increase relative to the baseline projection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.