ArticlePhysica D. Nonlinear phenomena2020
Hamiltonian structure of compartmental epidemiological models.
Article in Physica D. Nonlinear phenomena, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil.Physica D. Nonlinear phenomena · 2022Article
- Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States.The European physical journal. Special topics · 2022Article
- Trends in COVID-19 prevalence and mortality: A year in review.Physica D. Nonlinear phenomena · 2021Article
- Nonlinear science against the COVID-19 pandemic.Physica D. Nonlinear phenomena · 2021Article
- Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19.Physica A · 2021Article
- Association between COVID-19 cases and international equity indices.Physica D. Nonlinear phenomena · 2021Article
- Apparent scaling of virus surface roughness-An example from the pandemic SARS-nCoV.Physica D. Nonlinear phenomena · 2020Article
- Social distancing versus early detection and contacts tracing in epidemic management.Chaos, solitons, and fractals · 2020Article
- Size and timescale of epidemics in the SIR framework.Physica D. Nonlinear phenomena · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Any epidemiological compartmental model with constant population is shown to be a Hamiltonian dynamical system in which the total population plays the role of the Hamiltonian function. Moreover, some particular cases within this large class of models are shown to be bi-Hamiltonian. New interacting compartmental models among different populations, which are endowed with a Hamiltonian structure, are introduced. The Poisson structures underlying the Hamiltonian description of all these dynamical systems are explicitly presented, and their associated Casimir functions are shown to provide an efficient tool in order to find exact analytical solutions for epidemiological models, such as the ones describing the dynamics of the COVID-19 pandemic.
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.