Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica
Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa R...
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ftdoajarticles:oai:doaj.org/article:78e8f38019c24ae3b958021aa63cb5f4 2023-05-15T15:05:04+02:00 Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica Paola Vásquez Fabio Sanchez Luis A. Barboza Yury E. García Juan G. Calvo Shu-Wei Chou-Chen Gustavo Mery 2022-08-01T00:00:00Z https://doi.org/10.26633/RPSP.2022.113 https://doaj.org/article/78e8f38019c24ae3b958021aa63cb5f4 EN ES PT eng spa por Pan American Health Organization https://iris.paho.org/handle/10665.2/56286 https://doaj.org/toc/1020-4989 https://doaj.org/toc/1680-5348 1020-4989 1680-5348 doi:10.26633/RPSP.2022.113 https://doaj.org/article/78e8f38019c24ae3b958021aa63cb5f4 Revista Panamericana de Salud Pública, Vol 46, Iss 113, Pp 1-5 (2022) vector-borne diseases models theoretical public health costa rica Medicine R Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2022 ftdoajarticles https://doi.org/10.26633/RPSP.2022.113 2022-12-30T20:11:56Z Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Revista Panamericana de Salud Pública 46 1 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English Spanish Portuguese |
topic |
vector-borne diseases models theoretical public health costa rica Medicine R Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
vector-borne diseases models theoretical public health costa rica Medicine R Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Paola Vásquez Fabio Sanchez Luis A. Barboza Yury E. García Juan G. Calvo Shu-Wei Chou-Chen Gustavo Mery Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
topic_facet |
vector-borne diseases models theoretical public health costa rica Medicine R Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning. |
format |
Article in Journal/Newspaper |
author |
Paola Vásquez Fabio Sanchez Luis A. Barboza Yury E. García Juan G. Calvo Shu-Wei Chou-Chen Gustavo Mery |
author_facet |
Paola Vásquez Fabio Sanchez Luis A. Barboza Yury E. García Juan G. Calvo Shu-Wei Chou-Chen Gustavo Mery |
author_sort |
Paola Vásquez |
title |
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
title_short |
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
title_full |
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
title_fullStr |
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
title_full_unstemmed |
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica |
title_sort |
mathematical and statistical models for the control of mosquito-borne diseases: the experience of costa rica |
publisher |
Pan American Health Organization |
publishDate |
2022 |
url |
https://doi.org/10.26633/RPSP.2022.113 https://doaj.org/article/78e8f38019c24ae3b958021aa63cb5f4 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Revista Panamericana de Salud Pública, Vol 46, Iss 113, Pp 1-5 (2022) |
op_relation |
https://iris.paho.org/handle/10665.2/56286 https://doaj.org/toc/1020-4989 https://doaj.org/toc/1680-5348 1020-4989 1680-5348 doi:10.26633/RPSP.2022.113 https://doaj.org/article/78e8f38019c24ae3b958021aa63cb5f4 |
op_doi |
https://doi.org/10.26633/RPSP.2022.113 |
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Revista Panamericana de Salud Pública |
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46 |
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1 |
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