Evidence map›Paper›PMID 40034656›Full record

ArticleIJID regions2025

Factors predictive of epidemic waves of COVID-19 in Africa during the first 2 years of the pandemic.

Patient Wimba, Aboubacar Diallo, Amna Klich, Léon Tshilolo, Jean Iwaz, Jean François Étard, Philippe Vanhems, René Ecochard, Muriel Rabilloud

Abstract read
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In one paragraph

Article in IJID regions, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Patient WimbaUniversité Lyon 1, Villeurbanne, France.
Aboubacar DialloUniversité Lyon 1, Villeurbanne, France.
Amna KlichHospices Civils de Lyon, Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Lyon, France.
Léon TshiloloUniversité Officielle de Mbujimayi (UOM), Mbuji-Mayi, Democratic Republic of the Congo.
Jean IwazHospices Civils de Lyon, Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Lyon, France.
Jean François ÉtardIRD UMI 233, INSERM U1175, Université de Montpellier, Unité TransVIHMI, Montpellier, France.
Philippe VanhemsUniversité Lyon 1, Villeurbanne, France.
René EcochardUniversité Lyon 1, Villeurbanne, France.
Muriel RabilloudUniversité Lyon 1, Villeurbanne, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The objective was to study the epidemic wave curves, according to the characteristics of the countries, to identify the differences and the predictive factors of evolution. Methods: We have carried out modeling of the COVID-19 epidemic data from validated databases for 53 African countries. Results: All countries recorded at least four waves. The duration of the waves had decreased over time ( Conclusions: The duration of the waves was influenced by the seasons and the study periods, the incidences by the economic development, and health indicators. The appearance of new variants seemed associated with the start of the waves. None of the factors studied is associated with an inflection and a decrease in the curve.

Indexed as

AfricaClimate impactCOVID-19 wavesEconomic indicatorsPredictive factors

Identifiers

PMID40034656
PMCPMC11874724

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.