Early mathematical models of COVID-19 vaccination in high-income countries: a systematic review.

ABSTRACT

OBJECTIVES: Since COVID-19 first emerged in 2019, mathematical models have been developed to predict transmission and provide insight into disease control strategies. A key research need now is for models to inform long-term vaccination policy. We aimed to review the early modelling methods utilised during the pandemic period (2019-2023) in order to identify gaps in the literature and highlight areas for future model development. STUDY DESIGN: This study was a systematic review. METHODS: We searched PubMed, Embase and Scopus from 1 January 2019 to 6 February 2023 for peer-reviewed, English-language articles describing age-structured, dynamic, mathematical models of COVID-19 transmission and vaccination in high-income countries that include waning immunity or reinfection. We extracted details of the structure, features and approach of each model and combined them in a narrative synthesis. RESULTS: Of the 1109 articles screened, 47 were included. Most studies used deterministic, compartmental models set in Europe or North America that simulated a time horizon of 3.5 years or less. Common outcomes included cases, hospital utilisation and deaths. Only nine models included long COVID, costs, life years or quality of life-related measures. Two studies explored the potential impact of new variants beyond Omicron. CONCLUSIONS: This review demonstrates a need for long-term models that focus on outcome measures such as quality-adjusted life years, the population-level effects of long COVID and the cost effectiveness of future policies - all of which are essential considerations in the planning of long-term vaccination strategies.