OBJECTIVES: Following clinical research of potential COVID-19 treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence has been limited and modelling choices were made under great uncertainty. This study aimed to analyze key methodological choices made in model-based economic evaluations of COVID-19 treatments, and specifically focused on model choices which pertain to disease dynamics, model structure, and long-term sequelae.

METHODS: We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focusing on vaccines, diagnostic techniques, and non-pharmaceutical interventions were excluded. The search was last rerun on June 14, 2023. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist was used to assess the completeness of reporting. Results were narratively synthesized in tabular form. Several aspects were categorized into rubrics to enable comparison across studies.

RESULTS: Of the 1000 records identified, 27 were included. Disease dynamics of COVID-19 patients in the acute phase were incorporated in 25 studies (92.6%). Hypothetical cohorts were mainly stratified by respiratory support and level of care management. A Markov model was applied in 59.3% of studies, whether or not preceded by a decision tree or an epidemiological model. Number of health states used in Markov models ranged from 2 up to 17 health states. Of 10 studies with a lifetime horizon, 7 made adjustments to general population estimates to account for long-term sequelae, lasting for one year, five years or a patient’s lifetime for patients discharged after mechanical ventilation or with moderate or severe health issues.

CONCLUSIONS: The results illustrate the differences in modelling COVID-19 treatments and could serve as a starting point in the discussion on an adequate response from a health economic perspective towards future healthcare related emergencies.