ArticleChaos, solitons, and fractals2020
A new modelling of the COVID 19 pandemic.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Global Dynamics of SARS-CoV-2 Infection with Antibody Response and the Impact of Impulsive Drug Therapy.Vaccines · 2022Article
- Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement.Chaos, solitons, and fractals · 2022Article
- Merits and Limitations of Mathematical Modeling and Computational Simulations in Mitigation of COVID-19 Pandemic: A Comprehensive Review.Archives of computational methods in engineering : state of the art reviews · 2022Review
- Fuzzy Clustering Methods to Identify the Epidemiological Situation and Its Changes in European Countries during COVID-19.Entropy (Basel, Switzerland) · 2021Article
- Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.Results in physics · 2021Article
- Mathematical model, forecast and analysis on the spread of COVID-19.Chaos, solitons, and fractals · 2021Article
- The Cyclicity of coronavirus cases: "Waves" and the "weekend effect".Chaos, solitons, and fractals · 2021Article
- Complex dynamics in susceptible-infected models for COVID-19 with multi-drug resistance.Chaos, solitons, and fractals · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
А model of coronavirus incidence is proposed. Process of disease development is represented as analogue of first- and second order phase transition in physical systems. The model is very simple in terms of the data necessary for the calculations. To verify the proposed model, only data on the current incidence rate are required. However, the determination coefficient of model R2 is very high and exceeds 0.95 for most countries. The model permits the accurate prediction of the pandemics dynamics at intervals of up to 10 days. The ADL(autoregressive distributed lag)-model was introduced in addition to the phase transition model to describe the development of the disease at the exponential phase.The ADL-model allows describing nonmonotonic changes in relative infection over the time, and providing to governments and health care decision makers the possibility to predict the outcomes of their decisions on public health.
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.