Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.

ABSTRACT:

Objectives

To systematically review data-driven modelling studies that evaluated the effectiveness of interventions implemented during the COVID-19 pandemic and to identify which measures were most frequently reported as effective in controlling disease spread.

Design

Systematic review of modelling studies focused on data-driven, model-informed decision-making for COVID-19 interventions.

Data sources

A comprehensive literature search was conducted in PubMed, Web of Science and Embase, covering publications from 1 January 2020 to 16 October 2024.

Eligibility criteria

Studies were included if they: (1) used real-world data; (2) had sufficient sample sizes and (3) assessed at least one intervention with measurable outcomes.Meta-analyses and purely theoretical mode

SUBMITTER: Lotfi M 

PROVIDER: S-EPMC12815138 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature