ArticlePhysica D. Nonlinear phenomena2021
A simple but complex enough
Article in Physica D. Nonlinear phenomena, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Mathematical Contact Tracing Models for the COVID-19 Pandemic: A Systematic Review of the Literature.Healthcare (Basel, Switzerland) · 2025Review
- Disentangling the role of virus infectiousness and awareness-based human behavior during the early phase of the COVID-19 pandemic in the European Union.Applied mathematical modelling · 2023Article
- The stochasticCommunications in nonlinear science & numerical simulation · 2022Article
- A population structure-sensitive mathematical model assessing the effects of vaccination during the third surge of COVID-19 in Italy.Journal of mathematical analysis and applications · 2022Article
- Predictive approach of COVID-19 propagation via multiple-terms sigmoidal transition model.Infectious Disease Modelling · 2022Article
- Measuring the impact of social-distancing, testing, and undetected asymptomatic cases on the diffusion of COVID-19.PloS one · 2022Article
- Modeling the impact of SARS-CoV-2 variants and vaccines on the spread of COVID-19.Communications in nonlinear science & numerical simulation · 2021Article
- International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors.Environmental research · 2021Article
- Nonlinear science against the COVID-19 pandemic.Physica D. Nonlinear phenomena · 2021Article
- Epidemic models with discrete state structures.Physica D. Nonlinear phenomena · 2021Article
- A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia.Advances in difference equations · 2021Article
- COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.Stochastic environmental research and risk assessment : research journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the start of the COVID-19 pandemic in China many models have appeared in the literature, trying to simulate its dynamics. Focusing on modeling the biological and sociological mechanisms which influence the disease spread, the basic reference example is the SIR model. However, it is too simple to be able to model those mechanisms (including the three main types of control measures: social distancing, contact tracing and health system measures) to fit real data and to simulate possible future scenarios. A question, then, arises: how much and how do we need to complexify a SIR model? We develop a
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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.