About: Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators
Creator	Lukman, Adewale Alabi, Olusegun Ayinde, Kayode Ayinde, Opeyemi Okon, Charles Rauf, Rauf
source	Elsevier; Medline; PMC
abstract	COVID-19 remains a major pandemic currently threatening all the countries of the world. In Nigeria, there were 1, 932 COVID-19 confirmed cases, 319 discharged cases and 58 deaths as of 30th April 2020. This paper, therefore, subjected the daily cumulative reported COVID-19 cases of these three variables to nine (9) curve estimation statistical models in simple, quadratic, cubic, and quartic forms. It further identified the best of the thirty-six (36) models and used the same for prediction and forecasting purposes. The data collected by the Nigeria Centre for Disease Control for sixty-four (64) days, two (2) months and three (3), were daily monitored and eventually analyzed. We identified the best models to be Quartic Linear Regression Model with an autocorrelated error of order 1 (AR(1)); and found the Ordinary Least Squares, Cochrane Orcutt, Hildreth–Lu, and Prais-Winsten and Least Absolute Deviation (LAD) estimators useful to estimate the models’ parameters. Consequently, we recommended the daily cumulative forecast values of the LAD estimator for May and June 2020 with a 99% confidence level. The forecast values are alarming, and so, the Nigerian Government needs to hastily review her activities and interventions towards COVID-19 to provide some tactical and robust structures and measures to avert these challenges.
has issue date	2020-06-09(xsd:dateTime)
bibo:doi	10.1016/j.chaos.2020.109911
bibo:pmid	32536757
has license	no-cc
sha1sum (hex)	14f48f16ecf45a264839c4b3144e178c67b0ebde
schema:url	https://doi.org/10.1016/j.chaos.2020.109911
resource representing a document's title	Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators
has PubMed Central identifier	PMC7282783
has PubMed identifier	32536757
schema:publication	Chaos Solitons Fractals
resource representing a document's body	covid:14f48f16ecf45a264839c4b3144e178c67b0ebde#body_text
is schema:about of	named entity 'This' named entity 'COVID-19' named entity 'forecast' named entity 'cubic' named entity 'order' named entity 'comparative' named entity 'CENTRE' named entity 'INTERVENTIONS' named entity 'Disease Control' named entity 'Centre' named entity 'measures' named entity 'models' named entity 'cumulative' named entity 'tactical' named entity 'discharged' named entity 'cumulative' named entity 'Least Absolute Deviation' named entity 'June' named entity 'cases' named entity 'confidence level' named entity 'autocorrelated' named entity 'Covid-19' named entity 'estimators' named entity 'COVID-19' named entity 'Ordinary Least Squares' named entity 'Linear Regression Model' named entity 'major pandemic' named entity 'estimator' named entity 'confidence level' named entity 'Nigeria Centre for Disease Control' named entity 'P-value' named entity '0.01' named entity 'Coronavirus' named entity 'COVID-19 in Nigeria' named entity 'Nigeria' named entity 'COVID-19' named entity 'linear model' named entity '23,254' named entity 'parameter estimation' named entity 'Nigerian Railway Corporation' named entity 'Japan' named entity 'Watson test' named entity 'Linear Regression Model' named entity 'P-value' named entity 'data set' named entity 'COVID-19' named entity 'autocorrelation' named entity 'P-value' named entity 'Linear Regression Model' named entity 'Coronavirus' named entity 'Logarithm' named entity 'fever' named entity 'COVID-19' named entity 'Linear Regression Model' named entity 'linear regression Model' named entity 'parameter estimation' named entity 'Americas' named entity 'Nigeria Centre for Disease Control' named entity 'Turkey' named entity 'Logarithm' named entity 'Linear Regression Model' named entity 'P-value' named entity '0.01' named entity 'Linear Regression Model' named entity 'COVID-19' named entity 'statistical curve' named entity 'coefficient of determination' named entity 'Linear Regression Model' named entity 'P-value' named entity 'United States' named entity 'Russia' named entity 'CORC' named entity 'Enugu' named entity 'Republic of Korea' named entity 'Germany' named entity 'South-East Asia'

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