Evidence map›Paper›PMID 33078072›Full record

ArticleHealth information science and systems2020

Impact of COVID-19 prevalence and mode of transmission on mortality cases over WHO regions.

Olusola Samuel Makinde, Olubukola Olayemi Olusola-Makinde, Emmanuel Idowu Olamide, Gbenga Jacob Abiodun

Abstract read
In one paragraph

Article in Health information science and systems, 2020. 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

4 authors.

Olusola Samuel MakindeDepartment of Statistics, Federal University of Technology, P.M.B. 704, Akure, Nigeria.ORCID 0000-0003-3786-354X
Olubukola Olayemi Olusola-MakindeDepartment of Microbiology, Federal University of Technology, P.M.B. 704, Akure, Nigeria.
Emmanuel Idowu OlamideDepartment of Statistics, Federal University of Technology, P.M.B. 704, Akure, Nigeria.
Gbenga Jacob AbiodunDepartment of Mathematics, Southern Methodist University, Dallas, TX 75275 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the current outbreak of coronavirus disease 2019 (COVID-19), countries have been on rising preparedness to detect and isolate any imported and locally transmitted cases of the disease. It is observed that mode of transmission of the disease varies from one country to the other. Recent studies have shown that COVID-19 cases are not influenced by race and weather conditions. In this study, effect of modes of transmission of COVID-19 is considered with respect to prevalence and mortality counts in World Health Organisation (WHO) regions. Also, a negative binomial model is formulated for new death cases in all WHO regions as a function of confirmed cases, confirmed new cases, total deaths and modes of transmission, with the goal of identifying a model that predicts the total new death cases the best. Results from this study show that there is strong linear relationship among the COVID-19 confirmed cases, total new deaths and mode of transmission in all WHO regions. Findings highlight the significant roles of modes of transmission on total new death cases over WHO regions. Mode of transmission based on community transmission and clusters of cases significantly affects the number of new deaths in WHO regions. Vuong test shows that the formulated negative binomial model fits the data better than the null model.

Indexed as

COVID-19Mode of transmissionMortalityPredictive modelWHO regions

Identifiers

PMID33078072
PMCPMC7557305

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.