ArticleFrontiers in public health2021
Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- An analysis of spatial and temporal uncertainty propagation in agent-based models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
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- Modeling COVID-19 transmission between age groups in the United States considering virus mutations, vaccinations, and reinfection.Scientific reports · 2022Article
- Computational simulations to dissect the cell immune response dynamics for severe and critical cases of SARS-CoV-2 infection.Computer methods and programs in biomedicine · 2021Article
- Article
- How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study.Frontiers in medicine · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.
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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 OpenQuestion graph.