Monitoring and evaluation of community interventions for viral hepatitis among migrants and refugees: a Delphi-based study

Background: Migrants and refugees in Europe carry a disproportionate burden of chronic hepatitis B and C and face barriers accessing health systems. Community-based interventions can improve screening, prevention, and care, yet no framework exists to track their performance. This study aimed to generate a consensus set of indicators for monitoring and evaluating such interventions. Methods: A scoping review of PubMed from January 2005 to June 2024 identified 70 studies and 275 candidate indicators. After removing redundancies, 38 primary and 17 additional indicators were submitted to a two-round online Delphi panel. Fourteen experts from six countries (five from Spain, three from the UK, two each from Italy and from Greece, and one each from Belgium and the USA) rated each indicator on relevance, measurability, accuracy, ethics and clarity. Indicators with >67% combined 'agree/somewhat agree' were revised and advanced to Round 2 (R2), and were re-rated and ranked by experts. Results: Thirty-eight primary indicators and 10/17 additional indicators advanced to R2. Fifteen indicators were re-rated in R2; none were rejected. The final set comprised 50 indicators across six domains: Prevention (six), Testing (nine), Linkage to care (six), Treatment & Care (nine), Morbidity (seven) and Health System (13). Overall combined agreement averaged 95.3% (standard deviation = 7.0), with 29 indicators achieving unanimous support. Testing and Morbidity domains showed the strongest consensus. Ranking highlighted screening acceptability, infection prevalence, rapid testing results, referral success and treatment initiation as highest priorities. Conclusions: This Delphi study delivers the first consensus-driven indicator set for monitoring and evaluating community hepatitis B/C services targeting migrants and refugees. Adoption of the 50-indicator framework, and its streamlined core set, can harmonise monitoring, guide resource allocation and strengthen data-driven progress toward elimination goals. Registration: Open Science Framework.