Long-Term Forecast of HIV/AIDS Epidemic in China with Fear Effect and 90-90-90 Strategies
Bibliographic record
Abstract
We formulate a compartmental model considering behavioral changes of susceptible individuals due to fear to assess the transmission dynamics of HIV/AIDS in mainland China. Stability and uniform persistence are analyzed. Markov chain Monte Carlo simulations and Latin hypercube sampling are used to estimate the basic reproduction number and its sensitivity to parameter variations. The estimated mean reproduction number is 1.2138 (95% CI 1.0834–1.3442). The basic reproduction numbers of aware susceptible individuals and high-risk susceptible individuals are $$5.6776 \times {10^{-10}}$$ (95% CI $$4.7883\times {10^{{-10}}}$$ – $$6.7039 \times {10^{{-10}}}$$ ) and 1.2138 (95% CI 1.0834–1.3442), respectively. Global sensitivity analysis shows that preventive measures are more effective than post-infection measures in eliminating the epidemic. We incorporate 90-90-90 strategies to predict the new HIV/AIDS cases in China in the next few decades, and the results show that it takes at least 26 years to achieve the goal of zero new HIV/AIDS cases.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".