The Economic Evaluation of Adult Immunization Programs: The Importance of Local Context and the Example of Pneumococcal Vaccination
Bibliographic record
Abstract
Infectious diseases represent a unique challenge in healthcare policy decision-making, as the risk of disease is subject to change based on factors specific to the local context, which can evolve over time. Given this dynamic nature, it is critical to tailor economic evaluations of interventions targeting these diseases to the jurisdiction and timeframe in which they will be applied. The research comprising this thesis sought to address these challenges through a systematic review, population-based studies of health administrative data, and an economic evaluation. This was implemented through the example of evaluating a potential pneumococcal vaccination program, with a specific focus on publicly funding the 13-valent pneumococcal conjugate vaccine (PCV13) for older adults (65+). Streptococcus pneumoniae is a gram-positive bacterium that represents one of the most common causes of community-acquired pneumonia (CAP), imposing a significant health and financial burden across the world. Due to the decline in vaccine-type pneumococcal disease among older adults since PCV13's inclusion in the Ontario infant immunization program, the cost-effectiveness of publicly funding PCV13 for immunocompetent older adults remains unclear. The first study was a systematic review examining the impact of pneumococcal disease on health state utility values, focusing specifically on the syndromes of acute otitis media, CAP, bacteremia and meningitis. The second study was a population-based retrospective matched cohort study assessing the incidence of disease and healthcare costs attributable to CAP from the Ontario healthcare payer perspective using health administrative data. Exposed subjects were found to have substantially higher healthcare costs than comparable unexposed subjects for up to one year post index date. The third study applied the data developed in the first two studies to conduct an economic evaluation of adding PCV13 to the current immunization program in Ontario. The cost-utility analysis employed a microsimulation health state transition model, with the results indicating that adding PCV13 is unlikely to be cost-effective due to the substantial decline in disease caused by vaccine serotypes. Overall, this thesis demonstrates an approach to assessing the cost-effectiveness of vaccination programs, highlighting the influence of local factors such as serotype distribution on cost-effectiveness.
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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 | 0.120 | 0.294 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".