ArticlePLOS global public health2025
The utility of infectious disease modelling in informing decisions for outbreak response: A scoping review.
Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Implementation of AESOP early-warning system for respiratory disease: a pilot and validation study using routinely collected data in Amazonas, Brazil.Lancet regional health. Americas · 2026Article
- Basic Baseline model design choices can substantially influence performance in collaborative forecast hubs.medRxiv : the preprint server for health sciences · 2026Article
- The utility of infectious disease modelling in informing decisions for outbreak response: A scoping review.PLOS global public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Infectious disease modelling plays a critical role in guiding decisions during outbreaks. However, ongoing debates over the utility of these models highlight the need for a deeper understanding of their exact role in decision-making. In this scoping review we sought to fill this gap, focusing on challenges and facilitators of translating modelling insights into actionable policies. We searched the Ovid database to identify modelling studies that included an assessment of utility in informing policy and decision-making from January 2019 onwards. We further identified studies based on expert judgement. Results were analysed descriptively. The study was registered on the Open Science Framework platform. Out of 4007 screened and 12 additionally suggested studies, a total of 33 studies were selected for our review. None of the included articles provided objective assessments of utility but rather reflected subjectively on modelling efforts and highlighted individual key aspects for utility. 27 of the included articles considered the COVID-19 pandemic and 25 of the articles were from high-income countries. Most modelling efforts aimed to forecast outbreaks and evaluate mitigation strategies. Participatory stakeholder engagement and collaboration between academia, policy, and non-governmental organizations were identified as key facilitators of the modelling-for-decisions pathway. However, barriers such as data inconsistencies and quality, uncoordinated decision-making, limited funding and misinterpretation of uncertainties hindered effective use of modelling in decision-making. While our review identifies crucial facilitators and barriers for the modelling-for-decisions pathway, the lack of rigorous assessments of the utility of modelling for decisions highlights the need to systematically evaluate the impact of infectious disease modelling on decisions in future.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.