Evidence map›Paper›PMID 38624717›Full record

ArticleAnnals of data science2022

Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions.

Muhammad Ahsan-Ul-Haq, Mukhtar Ahmed, Javeria Zafar, Pedro Luiz Ramos

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Generalization of the Lindley distribution with application to COVID-19 data.International journal of data science and analytics · 2022
    Article
  3. Article
  4. 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.

Muhammad Ahsan-Ul-HaqCollege of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.ORCID 0000-0002-0902-8080
Mukhtar AhmedSchool of Statistics, Minhaj University Lahore, Lahore, Pakistan.
Javeria ZafarCollege of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.
Pedro Luiz RamosInstitute of Mathematical Science and Computing, University of São Paulo, São Carlos, SP Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Coronavirus Disease (COVID-19) is a respiratory disease that caused a large number of deaths all over the world since its outbreak. The World Health Organization (WHO) has declared the outbreak a global pandemic. The understanding of the random process related to the behavior infection of COVID-19 is an important health and economic problem. In the proposed study, we analyze the frequency of daily confirmed cases of COVID-19 using different two-parameter lifetime probability distributions. We consider the data from the period of March 11, 2020, to July 25, 2020, of Pakistan. We consider nine lifetime probability distributions for the analysis purpose and the selection of best fit was carried out using log-likelihood, AIC, BIC, RMSE, and R

Indexed as

CoronavirusDaily confirmed casesData analysisGoodness-of-fitLifetime distributions

Identifiers

PMID38624717
PMCPMC8095477

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.