Evidence map›Paper›PMID 33225115›Full record

ArticleInfectious Disease Modelling2021

Predictive models on COVID 19: What Africans should do?

Habte Tadesse Likassa, Wen Xain, Xuan Tang, Gizachew Gobebo

Open access · goldAbstract read
In one paragraph

Article in Infectious Disease Modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 34% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Influential Usage of Big Data and Artificial Intelligence in Healthcare.Computational and mathematical methods in medicine · 2021
    Review
  7. 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

4 authors at 3 institutions in 2 countries.

Habte Tadesse LikassaDepartement of Statistics, College of Natural and Computational Sciences, Addis Ababa University, Ethiopia.
Wen XainChinese Academy of Sciences, Fujian Institute of Research on the Structure of Matter Fuzhou, China.
Xuan TangChinese Academy of Sciences, Fujian Institute of Research on the Structure of Matter Fuzhou, China.
Gizachew GobeboDepartement of Statistics, College of Natural and Computational Sciences, Addis Ababa University, Ethiopia.
Addis Ababa University · ETChinese Academy of Sciences · CNFujian Institute of Research on the Structure of Matter · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, predictive models are proposed to accurately estimate the confirmed cases and deaths due to of Corona virus 2019 (COVID-19) in Africa. The study proposed the predictive models to determine the spatial and temporal pattern of COVID 19 in Africa. The result of the study has shown that the spatial and temporal pattern of the pandemic is varying across in the study area. The result has shown that cubic model is best outperforming compared to the other six families of exponentials (

Indexed as

COVID 19Mitigation mechanisms and transmissionPrediction models

Identifiers

PMID33225115
PMCPMC7670905
OpenAlexW3103942963

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.