Excel file containing extracted data for "The utility of infectious disease modelling in informing decisions for outbreak response: A scoping review"
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.
Keywords
COVID 19; Infectious disease modeling; Database searching; Low and middle income countries; Pandemics| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Dataset Quantitative |
| Capture method | Aggregation |
| Date | 2 September 2025 |
| Language(s) of written materials | English |
| Creator(s) |
Rao, D |
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
| Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Funders |
Project Funder Grant Number Funder URI |
| Date Deposited | 02 Feb 2026 13:16 |
| Last Modified | 02 Feb 2026 13:16 |
| Publisher | PLOS Global Public Health |
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