ArticleBMC infectious diseases2025
Guidelines on reporting and assessing dynamic mathematical models of infectious diseases: a scoping review.
Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMathematical models are valuable tools for guiding public health policy decisions to combat the spread of infectious diseases. Nevertheless, a lack of appropriate quality assessment tools and reporting guidelines hinders the comprehensibility, transparency, and credibility of infectious disease modelling studies and the ability to assess their quality. In a first step towards addressing the need for reporting guidelines and quality assessment tools specific to infectious disease modelling, this scoping review identified common themes in existing reporting and quality assessment guidance for infectious disease modelling studies and adjacent fields.
methodsWe conducted temporally-unrestricted searches on Medline (via Ovid), Web of Science, medRxiv, and bioRxiv in January 2024 to find articles that provide guidance on writing or assessing modelling studies within infectious disease modelling and adjacent fields including but not limited to healthcare and, more specifically, health economics. Articles were double-screened for eligibility via title-and-abstract screening and full-text screening. Recommendations made by eligible articles were classified into 31 subdimensions which were categorised into seven overarching dimensions (1. applicability; 2. model structure; 3. parameterisation and calibration; 4. validity; 5. uncertainty; 6. interpretation; 7. reproducibility, clarity, and transparency). We followed the PRISMA extension for reporting scoping reviews.
resultsOur final review included 53 articles. All dimensions except for interpretation were covered by most articles (81%-98%). However, we found substantial heterogeneity in the frequency with which subdimensions were addressed (11%-96%). Subdimensions pertaining to parameter uncertainty and transparency about parameter values were mentioned in most articles (91%-96%); conversely, discussions about auxiliary publication details and software implementation were covered less frequently (11%-23%).
conclusionsThis review shows that many recommendations made by reporting guidelines and quality assessment tools have thematic similarities and address common topics that are also relevant to infectious disease modelling. These identified themes and recommendations can be used as a starting point to inform the development of standardised guidelines for infectious disease modelling. REGISTRATION DOI: https://doi.org/10.17605/OSF.IO/AB6D3 . CLINICAL TRIAL NUMBER: Not applicable.
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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 Socratic graph.