ArticleInfectious Disease Modelling2020
Modelling the dynamics of exchanged novel coronavirus (2019-nCov) between regions in terms of time and space.
Article in Infectious Disease Modelling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Response of vaccination on community transmission of COVID-19: a dynamical approach.The European physical journal. Special topics · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To date, many models have been proposed which estimate the transmission risk of COVID-19 in terms of time; however, its dependency on space dimensions has been ignored. In this research, by multiplying risk parameters in certain regions and bridging, we obtain a stable action, which means that the transmission risk worldwide could shrink to a constant. Thus, by increasing the risk parameters in one region, the risk parameters in other regions decrease. Then, by adding space dimensions to the parameters in transmission risk models, and using the wave equations of manifolds for the regions, we obtain the dynamics of the exchanged novel coronavirus (2019-nCov) between countries. We calculate the risk factors of COVID19 for different regions in this model, and observe that they are in good agreement with experimental data.
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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.