Evidence map›Paper›PMID 34853486›Full record

ArticleTechnological forecasting and social change2022

On the global time evolution of the Covid-19 pandemic: Logistic modeling.

Tessaleno Devezas, L C M Miranda

Abstract read
In one paragraph

Article in Technological forecasting and social change, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Tessaleno DevezasAtlântica - Instituto Universitário - Oeiras, Lisbon, Portugal, C-MAST (Center for Aerospace Science and Technologies), FCT, Lisbon, Portugal.
L C M MirandaM2 Consultores, 12243-360 São José dos Campos, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this article it is presented a multi-logistic model to describe the time evolution of the Covid-19 pandemics. The model is not intended as paragon for the accurate prediction of the future number of people infected, but instead as a useful phenomenological approach for a comprehensive understanding of the pandemic development, able to uncover some hidden aspects of its unfolding. Our results, using OWID data of total cases and daily cases of Covid-19 from March 12, 2020, up to September 27, 2021, brought to light that the pandemic has unfolded globally as a multi-step logistic, namely six logistic phases, each with its own characteristic duration and intensity. Moreover, it is demonstrated how differently the pandemics spread among different countries and continents. The methodology is tested regarding its ability of forecasting, and is demonstrated that it works well in the range of circa 30 days within a margin of less than 3% error while a given phase is still in development. The case study of Portugal demonstrates the benefit of preventive sanitary measures, as well as shows how disastrous it may be the absence of such measures due to hesitations and/or political positions. Completing the article, a qualitative analysis is presented to scrutinize the possible causes of the asymmetry observed in the diffusion of Covid-19 among the different continents and countries.

Identifiers

PMID34853486
PMCPMC8612819

What OpenQuestion holds

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Registered trials

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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.