Evidence map›Paper›PMID 32834630›Full record

ArticleChaos, solitons, and fractals2020

A stretched logistic equation for pandemic spreading.

Giuseppe Consolini, Massimo Materassi

Abstract read
In one paragraph

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Quantifying Social Interventions for Combating COVID-19 via a Symmetry-Based Model.International journal of environmental research and public health · 2022
    Article
  3. Article
  4. Gompertz model in COVID-19 spreading simulation.Chaos, solitons, and fractals · 2022
    Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Giuseppe ConsoliniINAF-Istituto di Astrofisica e Planetologia Spaziali, Roma 00133, Italy.
Massimo MaterassiIstituto dei Sistemi Complessi, CNR, Sesto Fiorentino 50019, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this brief work we present a novel approach to the logistic dynamics of populations and epidemic spreading that can take into account of the complex nature of such a process in several real situations, where due to different agents the dynamics is no longer characterized by a single characteristic timescale, but conversely by a distribution of time scales, rendered via a time-dependent growth rate. In detail, a differential equation containing a power-law time dependent growth rate is proposed, whose solution, named

Indexed as

Complex dynamicsCOVID-19Logistic regressionPandemic spreading

Identifiers

PMID32834630
PMCPMC7374175

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.