National and sub-national HIV/AIDS-related mortality in Iran, 1990–2015: a population-based modeling study
Bibliographic record
Abstract
Surveillance of HIV/AIDS mortality is crucial to evaluate a country’s response to the disease. With a modified estimation approach, this study aimed to provide more accurate estimates on deaths due to HIV/AIDS in Iran from 1990 to 2015 at national and sub-national levels. Using a comprehensive data set, death registration incompleteness and misclassification were addressed by demographical and statistical methods. Trends of mortality due to HIV/AIDS at national and sub-national levels were estimated by applying a set of models. A total of 474 men (95% uncertainty interval [UI]: 175–1332) and 256 women (95% UI: 36–1871) died due to HIV/AIDS in 2015 in Iran. Peaked in 1995, HIV/AIDS-related mortality has steadily declined among both genders. Mortality rates were remarkably higher among men than women during the period studied. At the sub-national level, the highest and the lowest annual percent change were found at 10.97 and −1.36% for women, and 4.04 and −3.47% for men, respectively. The findings of our study (731 deaths) were remarkably lower than the Joint United Nations Programme on HIV and AIDS (4000) but higher than Global Burden of Disease (339) estimates in 2015. The overall decrease in mortality due to HIV/AIDS may be attributed to the increasing burden of noncommunicable diseases; however, the role of the national and international organizations to fight HIV/AIDS should not be overlooked. To decrease HIV/AIDS mortality and to achieve international goals, evidence-based action is required. To fast-track targets, the priority must be to prevent infection, promote early diagnosis, provide access to treatment, and to ensure treatment adherence among patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".