MODELING APPROACHES FOR VACCINE INDIRECT EFFECTS IN ECONOMIC EVALUATIONS: A SCOPING REVIEW OF PUBLISHED REVIEWS AND METHODOLOGICAL GUIDANCE
Author(s)
Min Huang, PhD1, Weiguang Xue, MSc2, Yanwen Xie, MSc3, Michael Xu, MSc2, Xin Chen, MSc4, Walter A. Orenstein, MD5, Zinan Yi, PhD1, Rachel J. Oidtman, PhD1, Elamin Elbasha, BSc, MA, PhD1, Michael Drummond, MCom, DPhil6;
1Merck & Co. Inc., Rahway, NJ, USA, 2Analysis Group Ltd., London, United Kingdom, 3Analysis Group, Inc., Los Angeles, CA, USA, 4Analysis Group, Inc., Beijing, China, 5School of Medicine, Emory University, Atlanta, GA, USA, 6Centre for Health Economics, University of York, York, United Kingdom
1Merck & Co. Inc., Rahway, NJ, USA, 2Analysis Group Ltd., London, United Kingdom, 3Analysis Group, Inc., Los Angeles, CA, USA, 4Analysis Group, Inc., Beijing, China, 5School of Medicine, Emory University, Atlanta, GA, USA, 6Centre for Health Economics, University of York, York, United Kingdom
OBJECTIVES: To assess how indirect effects have been incorporated in published vaccine health economic models.
METHODS: A scoping review of MEDLINE and Embase (from inception to May 7, 2025) identified literature reviews examining whether and how indirect effects (defined as herd immunity, serotype replacement and age shift) were modeled in vaccine economic evaluations. Extracted data included model structure, sources of indirect effect inputs, key assumptions, and justification for the chosen approach. A supplementary search identified methodological guidelines, supplemented with guidance from NITAGs and HTA agencies in seven countries. Data were extracted on recommended modeling approaches, structural assumptions, and input requirements related to indirect effects.
RESULTS: Twenty-two literature reviews and 11 methodological guidelines were included. All 22 reviews reported that herd immunity was discussed in the models they examined; 12 additionally identified models incorporating serotype replacement, and 2 identified models incorporating age shift. Most summarized studies used static models, typically adjusting parameters, such as applying fixed reductions in incidence among unvaccinated individuals, to approximate indirect effects rather than using dynamic transmission models. Approximately half of the reviews reported sources for indirect effect inputs, most commonly surveillance data or published dynamic models. Reviews consistently noted that indirect effects can substantially influence cost-effectiveness estimates, yet explicit incorporation was uncommon, potentially leading to underestimation of benefits (e.g., herd immunity) or omission of risks (e.g., age shift or serotype replacement). Dynamic models were widely recommended but remain underused due to complexity and data constraints. Guidance from WHO, ISPOR, NACI, and STIKO outlines general principles, but methodological heterogeneity persists and few frameworks provide operational detail.
CONCLUSIONS: Indirect effects critically influence results of vaccine cost-effectiveness analysis yet remain inconsistently modeled. Clearer methodological standards and better quality data are needed to support consistent and policy-relevant implementation.
METHODS: A scoping review of MEDLINE and Embase (from inception to May 7, 2025) identified literature reviews examining whether and how indirect effects (defined as herd immunity, serotype replacement and age shift) were modeled in vaccine economic evaluations. Extracted data included model structure, sources of indirect effect inputs, key assumptions, and justification for the chosen approach. A supplementary search identified methodological guidelines, supplemented with guidance from NITAGs and HTA agencies in seven countries. Data were extracted on recommended modeling approaches, structural assumptions, and input requirements related to indirect effects.
RESULTS: Twenty-two literature reviews and 11 methodological guidelines were included. All 22 reviews reported that herd immunity was discussed in the models they examined; 12 additionally identified models incorporating serotype replacement, and 2 identified models incorporating age shift. Most summarized studies used static models, typically adjusting parameters, such as applying fixed reductions in incidence among unvaccinated individuals, to approximate indirect effects rather than using dynamic transmission models. Approximately half of the reviews reported sources for indirect effect inputs, most commonly surveillance data or published dynamic models. Reviews consistently noted that indirect effects can substantially influence cost-effectiveness estimates, yet explicit incorporation was uncommon, potentially leading to underestimation of benefits (e.g., herd immunity) or omission of risks (e.g., age shift or serotype replacement). Dynamic models were widely recommended but remain underused due to complexity and data constraints. Guidance from WHO, ISPOR, NACI, and STIKO outlines general principles, but methodological heterogeneity persists and few frameworks provide operational detail.
CONCLUSIONS: Indirect effects critically influence results of vaccine cost-effectiveness analysis yet remain inconsistently modeled. Clearer methodological standards and better quality data are needed to support consistent and policy-relevant implementation.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
HTA12
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes, Value Frameworks & Dossier Format
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, STA: Vaccines