Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius
This paper proposes some high-ordered integer-valued auto-regressive time series process of order p (INAR(p)) with Zero-Inflated and Poisson-mixtures innovation distributions, wherein the predictor functions in these mentioned distributions allow for covariate specification, in particular, time-depe...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824322/?tool=EBI |
| _version_ | 1818282397590880256 |
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| author | Ashwinee Devi Soobhug Homeswaree Jowaheer Naushad Mamode Khan Neeshti Reetoo Kursheed Meethoo-Badulla Laurent Musango Célestin C. Kokonendji Azmi Chutoo Nawel Aries |
| author_facet | Ashwinee Devi Soobhug Homeswaree Jowaheer Naushad Mamode Khan Neeshti Reetoo Kursheed Meethoo-Badulla Laurent Musango Célestin C. Kokonendji Azmi Chutoo Nawel Aries |
| author_sort | Ashwinee Devi Soobhug |
| collection | DOAJ |
| description | This paper proposes some high-ordered integer-valued auto-regressive time series process of order p (INAR(p)) with Zero-Inflated and Poisson-mixtures innovation distributions, wherein the predictor functions in these mentioned distributions allow for covariate specification, in particular, time-dependent covariates. The proposed time series structures are tested suitable to model the SARs-CoV-2 series in Mauritius which demonstrates excess zeros and hence significant over-dispersion with non-stationary trend. In addition, the INAR models allow the assessment of possible causes of COVID-19 in Mauritius. The results illustrate that the event of Vaccination and COVID-19 Stringency index are the most influential factors that can reduce the locally acquired COVID-19 cases and ultimately, the associated death cases. Moreover, the INAR(7) with Zero-inflated Negative Binomial innovations provides the best fitting and reliable Root Mean Square Errors, based on some short term forecasts. Undeniably, these information will hugely be useful to Mauritian authorities for implementation of comprehensive policies. |
| first_indexed | 2024-12-13T00:20:22Z |
| format | Article |
| id | doaj.art-687d897f0854444a8bd34cae6bc3ec52 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T00:20:22Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-687d897f0854444a8bd34cae6bc3ec522022-12-22T00:05:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01172Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in MauritiusAshwinee Devi SoobhugHomeswaree JowaheerNaushad Mamode KhanNeeshti ReetooKursheed Meethoo-BadullaLaurent MusangoCélestin C. KokonendjiAzmi ChutooNawel AriesThis paper proposes some high-ordered integer-valued auto-regressive time series process of order p (INAR(p)) with Zero-Inflated and Poisson-mixtures innovation distributions, wherein the predictor functions in these mentioned distributions allow for covariate specification, in particular, time-dependent covariates. The proposed time series structures are tested suitable to model the SARs-CoV-2 series in Mauritius which demonstrates excess zeros and hence significant over-dispersion with non-stationary trend. In addition, the INAR models allow the assessment of possible causes of COVID-19 in Mauritius. The results illustrate that the event of Vaccination and COVID-19 Stringency index are the most influential factors that can reduce the locally acquired COVID-19 cases and ultimately, the associated death cases. Moreover, the INAR(7) with Zero-inflated Negative Binomial innovations provides the best fitting and reliable Root Mean Square Errors, based on some short term forecasts. Undeniably, these information will hugely be useful to Mauritian authorities for implementation of comprehensive policies.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824322/?tool=EBI |
| spellingShingle | Ashwinee Devi Soobhug Homeswaree Jowaheer Naushad Mamode Khan Neeshti Reetoo Kursheed Meethoo-Badulla Laurent Musango Célestin C. Kokonendji Azmi Chutoo Nawel Aries Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius PLoS ONE |
| title | Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius |
| title_full | Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius |
| title_fullStr | Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius |
| title_full_unstemmed | Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius |
| title_short | Re-analyzing the SARS-CoV-2 series using an extended integer-valued time series models: A situational assessment of the COVID-19 in Mauritius |
| title_sort | re analyzing the sars cov 2 series using an extended integer valued time series models a situational assessment of the covid 19 in mauritius |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824322/?tool=EBI |
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