Evaluating the Impact of Population-Based and Cohort-Based Models in Cost-Effectiveness Analysis: A Case Study of Pneumococcal Conjugate Vaccines in Infants in Germany
Bibliographic record
Abstract
Abstract Introduction Cost-effectiveness analysis (CEA) is crucial when evaluating the health and economic value of vaccines compared to the current standard of care (SoC) and provides essential information to assist decision-makers in maximizing health gains when allocating resources. The design of the CEA should address the specific policy questions, disease area, vaccine characteristics, and consider all relevant vaccination effects on the population. Areas covered We presented a case study on the CEA of pneumococcal conjugate vaccines (PCVs) in infants in Germany using a closed single cohort-based approach versus a population-based approach. Except for the design of the modelled population/cohort, all other inputs and characteristics were kept identical in the cost-effectiveness model. We contrasted model results, inferences, and conclusions between both design approaches. Expert Opinion CEA must carefully consider the included population in the analysis based on their specific policy questions and the characteristics of the vaccine being evaluated. The choice between population-based and closed single-cohort models fundamentally depends on whether the vaccine affects disease transmission dynamics. Population models are essential for vaccines that disrupt transmission patterns across population groups, such as PCVs in infants, while closed single-cohort models are suitable for vaccines impacting only vaccinated individuals without affecting disease transmission. Article highlights Identifying the appropriate model design is crucial for conducting cost-effectiveness analyses (CEAs) of vaccines, particularly when addressing vaccine technical committee (VTC) policy questions, which aim to optimize individual and population health benefits. Closed single cohort-based designs track a group of individuals, while population-based designs evaluate an entire cross-sectional population, making the choice between the two designs vital when vaccines have secondary, indirect effects. We presented a case study comparing PCV20 with PCV13 and PCV15 in infants in Germany using a closed single cohort-based approach and a population-based approach. Modelled results highlighted that the closed single cohort-based approach substantially underestimated public health benefits and economic advantages associated with PCV20, whereas the population-based approach demonstrated PCV20 as cost-saving strategy while offering superior health outcomes, indicating it as a dominant vaccination option when accounting for Germany’s entire population. Selecting an inappropriate model design for CEAs of vaccines could result in unintended consequences, such as adversely affecting national recommendations, policies, and programs, leading to suboptimal decision-making for population health. Researchers and policymakers must carefully select appropriate population frameworks and adhere to methodological guidelines to ensure accurate inferences in vaccine economic evaluations.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".