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Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling

In this work, we predict the prevalence of type 2 diabetes among adult Rwandan people. We used the Metropolis-Hasting method that involved calculating the metropolis ratio. The data are those reported by World Health Organiation in 2015. Considering Suffering from diabetes, Overweight, Obesity, Dead...

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Autores principales: Dukunde, Angelique, Ntaganda, Jean Marie, Kasozi, Juma, Nzabanita, Joseph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Makerere Medical School 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8568256/
https://www.ncbi.nlm.nih.gov/pubmed/34795726
http://dx.doi.org/10.4314/ahs.v21i2.28
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author Dukunde, Angelique
Ntaganda, Jean Marie
Kasozi, Juma
Nzabanita, Joseph
author_facet Dukunde, Angelique
Ntaganda, Jean Marie
Kasozi, Juma
Nzabanita, Joseph
author_sort Dukunde, Angelique
collection PubMed
description In this work, we predict the prevalence of type 2 diabetes among adult Rwandan people. We used the Metropolis-Hasting method that involved calculating the metropolis ratio. The data are those reported by World Health Organiation in 2015. Considering Suffering from diabetes, Overweight, Obesity, Dead and other subject as states of mathematical model, the transition matrix whose elements are probabilities is generated using Metropolis-Hasting sampling. The numerical results show that the prevalence of type 2 diabetes increases from 2.8% in 2015 to reach 12.65% in 2020 and to 22.59% in 2025. Therefore, this indicates the urgent need of prevention by Rwandan health decision makers who have to play their crucial role in encouraging for example physical activity, regular checkups and sensitization of the masses.
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spelling pubmed-85682562021-11-17 Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling Dukunde, Angelique Ntaganda, Jean Marie Kasozi, Juma Nzabanita, Joseph Afr Health Sci Articles In this work, we predict the prevalence of type 2 diabetes among adult Rwandan people. We used the Metropolis-Hasting method that involved calculating the metropolis ratio. The data are those reported by World Health Organiation in 2015. Considering Suffering from diabetes, Overweight, Obesity, Dead and other subject as states of mathematical model, the transition matrix whose elements are probabilities is generated using Metropolis-Hasting sampling. The numerical results show that the prevalence of type 2 diabetes increases from 2.8% in 2015 to reach 12.65% in 2020 and to 22.59% in 2025. Therefore, this indicates the urgent need of prevention by Rwandan health decision makers who have to play their crucial role in encouraging for example physical activity, regular checkups and sensitization of the masses. Makerere Medical School 2021-06 /pmc/articles/PMC8568256/ /pubmed/34795726 http://dx.doi.org/10.4314/ahs.v21i2.28 Text en © 2021 Dukunde A et al. https://creativecommons.org/licenses/by/4.0/Licensee African Health Sciences. This is an Open Access article distributed under the terms of the Creative commons Attribution License (https://creativecommons.org/licenses/BY/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Dukunde, Angelique
Ntaganda, Jean Marie
Kasozi, Juma
Nzabanita, Joseph
Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title_full Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title_fullStr Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title_full_unstemmed Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title_short Prediction of prevalence of type 2 diabetes in Rwanda using the metropolis-hasting sampling
title_sort prediction of prevalence of type 2 diabetes in rwanda using the metropolis-hasting sampling
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8568256/
https://www.ncbi.nlm.nih.gov/pubmed/34795726
http://dx.doi.org/10.4314/ahs.v21i2.28
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