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Spatially structured models of viral dynamics: a scoping review
Thomas Williams1, James M McCaw1,2, James M Osborne1
1School of Mathematics & Statistics, University of Melbourne, Parkville, Victoria, Australia.
Spatially explicit models enhance understanding of viral infection dynamics within hosts. This review consolidates diverse modeling approaches to guide future research and applications in virology.
Area of Science:
- Virology
- Mathematical Biology
- Computational Biology
Background:
- Growing recognition of spatial structure's importance in within-host viral dynamics.
- Recent surge in spatially explicit models driven by computational power and biological insights, accelerated by the COVID-19 pandemic.
- Spatially structured models offer greater biological realism than conventional mean-field approaches.
Purpose of the Study:
- To provide an exhaustive update on the state of spatially structured viral dynamics models.
- To address the underuse of these models in biological applications due to methodological diversity.
- To identify key themes for future model development to enhance robustness and utility.
Main Methods:
- Scoping review of the literature on spatially structured viral dynamics models.
- Analysis structured along two axes: methodology and viral species.
- Examination of the breadth of techniques and biological application requirements.
Main Results:
- Identified a huge variety in modeling approaches, hindering consensus and wider application.
- Highlighted the contributions of mathematical and computational modeling to understanding spatially structured viral dynamics.
- Provided a comprehensive overview of current techniques and their biological context.
Conclusions:
- Spatially structured models are crucial for understanding viral dynamics but face adoption challenges.
- Standardization and clear guidelines are needed for implementing these models effectively.
- Future research should focus on improving model robustness and biological utility for broader applications.
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