ArticleBMJ open2024
Mathematical modelling and analysis for the co-infection of viral and bacterial diseases: a systematic review protocol.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mechanistic Models of Virus-Bacteria Co-Infections in Humans: A Systematic Review of Methods and Assumptions.Pathogens (Basel, Switzerland) · 2025Pooled it
- The neglected model validation of antimicrobial resistance transmission models - a systematic review.Antimicrobial resistance and infection control · 2025Pooled it
- Survey on mathematical modeling of infectious disease dynamics: insights and applications.BMC infectious diseases · 2026Review
- Protocol for an Integrative Meta-Analysis of the Application of Machine Learning Algorithms in the Prediction of Chronic Disease Risks and Outcomes.Chronic diseases and translational medicine · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionBreaking the chain of transmission of an infectious disease pathogen is a major public health priority. The challenges of understanding, describing and predicting the transmission dynamics of infections have led to a wide range of mathematical, statistical and biological research problems. Advances in diagnostic laboratory procedures with the ability to test multiple pathogens simultaneously mean that co-infections are increasingly being detected, yet little is known about the impact of co-infections in shaping the course of an infection, infectivity, and pathogen replication rate. This is particularly true of the apparent synergistic effects of viral and bacterial co-infections, which present the greatest threats to public health because of their lethal nature and complex dynamics. This systematic review protocol is the foundation of a critical review of co-infection modelling and an assessment of the key features of the models. METHODS AND ANALYSIS: MEDLINE through PubMed, Web of Science, medRxiv and Scopus will be systematically searched between 1 December 2024 and 31 January 2025 for studies published between January 1980 and December 2024. Three reviewers will screen articles independently for eligibility, and quality assessment will be performed using the TRACE (TRAnsparent and Comprehensive Ecological) standard modelling guide. Data will be extracted using an Excel template in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis standard reporting guidelines. This systematic review will apply the SWiM (Synthesis Without Meta-analysis) approach in its narrative synthesis coupled with tables and figures to present data. The synthesis will highlight key dynamical co-infection model features such as assumptions, data fitting and estimation methods, validation and sensitivity analyses, optimal control analyses, and the impact of co-infections. ETHICS AND DISSEMINATION: Ethics approval is not required for a systematic review since it will be based on published work. The output of this study will be submitted for publication in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023481247.
Indexed as
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.