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Development of a mechanistic dengue simulation model for Guangzhou
Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This st...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518829/ https://www.ncbi.nlm.nih.gov/pubmed/30869038 http://dx.doi.org/10.1017/S095026881900030X |
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author | Mincham, G. Baldock, K. L. Rozilawati, H. Williams, C. R. |
author_facet | Mincham, G. Baldock, K. L. Rozilawati, H. Williams, C. R. |
author_sort | Mincham, G. |
collection | PubMed |
description | Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies. |
format | Online Article Text |
id | pubmed-6518829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65188292019-06-04 Development of a mechanistic dengue simulation model for Guangzhou Mincham, G. Baldock, K. L. Rozilawati, H. Williams, C. R. Epidemiol Infect Original Paper Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies. Cambridge University Press 2019-03-01 /pmc/articles/PMC6518829/ /pubmed/30869038 http://dx.doi.org/10.1017/S095026881900030X Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Mincham, G. Baldock, K. L. Rozilawati, H. Williams, C. R. Development of a mechanistic dengue simulation model for Guangzhou |
title | Development of a mechanistic dengue simulation model for Guangzhou |
title_full | Development of a mechanistic dengue simulation model for Guangzhou |
title_fullStr | Development of a mechanistic dengue simulation model for Guangzhou |
title_full_unstemmed | Development of a mechanistic dengue simulation model for Guangzhou |
title_short | Development of a mechanistic dengue simulation model for Guangzhou |
title_sort | development of a mechanistic dengue simulation model for guangzhou |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518829/ https://www.ncbi.nlm.nih.gov/pubmed/30869038 http://dx.doi.org/10.1017/S095026881900030X |
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