Susceptible-Infectious-Susceptible Epidemic Model with Symmetrical Fluctuations: Equilibrium States and Stability Analyses for Finite Systems
Acta Biotheoretica, ISSN: 1572-8358, Vol: 72, Issue: 4, Page: 13
2024
- 2Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures2
- Readers2
Article Description
Accurate prediction of epidemic evolution faces challenges such as understanding disease dynamics and inadequate epidemiological data. A recent approach faced these issues by modeling susceptible-infectious-susceptible (SIS) dynamics based on the first two statistical moments. Here, we improve this approach by including finite-size populations and analyzing the stability of the resulting model. Results underscore the influence of uncertainties and population size in the natural history of the epidemic.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85209213515&origin=inward; http://dx.doi.org/10.1007/s10441-024-09490-0; http://www.ncbi.nlm.nih.gov/pubmed/39535581; https://link.springer.com/10.1007/s10441-024-09490-0; https://dx.doi.org/10.1007/s10441-024-09490-0; https://link.springer.com/article/10.1007/s10441-024-09490-0
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know