Background
The CHEERS 2022 statement provides a standardised framework to ensure transparency and completeness in reporting health economic evaluations (Husereau et al., 2022). However, as health technology assessment (HTA) bodies increasingly evaluate complex interventions, the core checklist requires targeted expansions. The recent validation of the CHEERS-AI extension (Elvidge et al., 2024) demonstrated that specific methodological fields require explicit, dedicated reporting standards to capture nuances that generic frameworks miss. A similarly important requirement exists for infectious disease economic evaluations.
Rationale
Infectious disease interventions (e.g., vaccination programmes, antimicrobial stewardship, quarantine protocols) differ fundamentally from interventions for other diseases due to the transmissible nature of pathogens (Pitman et al., 2012). Standard health economic models (e.g., Markov models, decision trees) assume static transition probabilities. In contrast, infectious disease evaluations rely heavily on dynamic transmission models where the risk of infection changes over time based on human interactions and the changing pool of infectious individuals.
A dedicated CHEERS-ID extension is crucial because:
Dynamic transmission models generate non-linear effects, such as herd immunity, which directly impact health economic outcomes by preventing downstream infections in unvaccinated populations (Pitman et al., 2012). Current reporting standards do not mandate clear descriptions of how these population-level externalities are captured or valued economically.
Infectious disease evaluations must report specific epidemiological complexities, including strain replacement, structural mixing matrices, and the emergence of antimicrobial resistance (Pitman et al., 2012). Incomplete reporting of these variables undermines the credibility of cost-effectiveness thresholds.
Unlike chronic diseases with predictable progression, infectious disease outbreaks involve volatile, time-dependent horizons. The rationale behind chosen model timelines, particularly regarding the capturing of post-epidemic steady states, remains poorly reported (Pitman et al., 2012).
Proposed methods The development of CHEERS-ID will mirror the rigorous, consensus-based approach utilised by previous extensions:
Scoping review: A systematic literature search to evaluate the reporting quality of current infectious disease economic evaluations and identify gaps in the application of CHEERS 2022.
Delphi process: A multi-round anonymous survey administered to an international, multidisciplinary panel of health economists, epidemiological modellers, HTA decision-makers, clinicians, and members of the public to score potential reporting items.
Consensus meeting: An online consensus meeting with key stakeholders to finalise outstanding or ambiguous checklist items.
Piloting and finalisation: A pilot phase where the drafted checklist is applied to a random sample of published infectious disease economic evaluations to ensure usability, followed by formalisation and publication.
Registered: 26 October 2026
Last updated:
Contact: Phuong Bich Tran Email: [email protected]