Literature DB >> 24652258

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

Guillermo L Rúa-Uribe1, Carolina Suárez-Acosta1, José Chauca2, Palmira Ventosilla2, Rita Almanza3.   

Abstract

INTRODUCTION: Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease.
OBJECTIVE: To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease.
MATERIALS AND METHODS: The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models.
RESULTS: The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay.
CONCLUSIONS: In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

Entities:  

Mesh:

Year:  2013        PMID: 24652258

Source DB:  PubMed          Journal:  Biomedica        ISSN: 0120-4157            Impact factor:   0.935


  6 in total

1.  Distance to public transit predicts spatial distribution of dengue virus incidence in Medellín, Colombia.

Authors:  Laura C Harrington; Guillermo Rúa-Uribe; Talya Shragai; Juliana Pérez-Pérez; Marcela Del Pilar Quimbayo-Forero; Raúl Rojo
Journal:  Sci Rep       Date:  2022-05-18       Impact factor: 4.996

Review 2.  A systematic review and meta-analysis of dengue risk with temperature change.

Authors:  Jingchun Fan; Wanxia Wei; Zhenggang Bai; Chunling Fan; Shulan Li; Qiyong Liu; Kehu Yang
Journal:  Int J Environ Res Public Health       Date:  2014-12-23       Impact factor: 3.390

Review 3.  [Climate-sensitive diseases in Brazil and the world: systematic reviewEnfermedades sensibles al clima en Brasil y el mundo: revisión sistemática].

Authors:  Tatiane Cristina Moraes de Sousa; Flavia Amancio; Sandra de Sousa Hacon; Christovam Barcellos
Journal:  Rev Panam Salud Publica       Date:  2018-07-20

4.  Multilevel analysis of social, climatic and entomological factors that influenced dengue occurrence in three municipalities in Colombia.

Authors:  Gustavo Ordoñez-Sierra; Diana Sarmiento-Senior; Juan Felipe Jaramillo Gomez; Paola Giraldo; Alexandra Porras Ramírez; Víctor Alberto Olano
Journal:  One Health       Date:  2021-03-05

5.  Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

Authors:  Michael A Johansson; Nicholas G Reich; Aditi Hota; John S Brownstein; Mauricio Santillana
Journal:  Sci Rep       Date:  2016-09-26       Impact factor: 4.379

6.  Bayesian dynamic modeling of time series of dengue disease case counts.

Authors:  Daniel Adyro Martínez-Bello; Antonio López-Quílez; Alexander Torres-Prieto
Journal:  PLoS Negl Trop Dis       Date:  2017-07-03
  6 in total

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