The cost effectiveness of rotavirus vaccination in Iran
Bibliographic record
Abstract
Rotavirus is the most common cause of severe diarrhea leading to hospitalization or disease-specific death among young children. Effective vaccines have recently been approved and successful vaccination program implemented. The aim of this study was to evaluate the cost effectiveness of mass rotavirus vaccination program in Iran. We developed a Markov model that reflects key features of rotavirus natural history. Parameters of the model were assessed by field study or developed through literature search and published data. We applied the model to the 2009 Iranian birth cohort and evaluated the cost-effectiveness of including the rotavirus vaccine (Rotarix®) into Iranian expanded immunization program (EPI). With an estimated hospitalization rate of 0.05 and outpatient rate of 0.23 cases per person-year, vaccinating cohort of 1231735 infants in Iran with 2 doses of (Rotarix®), would prevent 32092 hospitalizations, 158750 outpatient visits, and 1591 deaths during 5 y of follow-up. Under base-case assumption of $10 cost per course of vaccine, the vaccination would incur an extra cost of $1,019,192 from health care perspective and would avert 54680 DALYs. From societal perspective, there would be $15,192,568 saving for the society with the same averted DALYs. The incremental cost effectiveness ratio showed a cost of $19 US dollars per averted DALY from health care perspective and a saving of $278 US dollars for each averted DALY from societal perspective. Introducing rotavirus vaccine into EPI program would be highly cost-effective public health intervention in Iran.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".