COMIDENCO - Construction of a Dengue Incidence Model Applied to Communities of Paraguay

Executor Support  Asociated      
CIMA ProCiencia CONACYT Universidad Nacional de Caaguazú CEDIC Universidad Nacional de Concepción Facultad Politécnica - UNA

Conacyt Project PINV15-706

Objective

Construct and verify a mathematical model to predict the incidence rate of dengue fever, according to environmental, health and epidemiological variables and in the presence of anti-dengue intervention actions. This translates into 4 specific objectives:

  1. Use historical data to identify and define environmental, health and epidemiological variables that allow the construction and evaluation of a mathematical model that predicts the incidence rate of dengue in the city of Asunción.
  2. Evaluate the generalization capacity of this model in similar communities of Paraguay.
  3. Identify the most appropriate algorithmic techniques to generate the mathematical model; design and implement software to help decision-making for the establishment actions against dengue according to the predicted incidence rate. 
  4. Identify the most appropriate algorithmic techniques to generate the mathematical model; design and implement software to help decision-making and to establish actions against dengue according to the predicted incidence rate.
  5. Consolidate a network team to apply this methodology in related cases in Paraguay using the newly developed software.

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Director

Magna María Monteiro (from 06/01/2018)
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Daniel Romero (from 03/01/2017 to 05/31/2018)

 

Researchers

 

Communications

To Society
  • Jul/13/2017 First Comidenco Meeting, carried out on the San Lorenzo campus, with participation of all the researchers and invited students..
  • Aug/22/2017 Second Meeting of Researchers organized by the Scientific Society of Paraguay -- Poster presented..
In Indexed Journals:
  • Jorge Mello-Román and Julio Mello-Román and Santiago Gómez-Guerrero and Miguel García-Torres. Predictive Models for the Medical Diagnosis of Dengue: A Case Study in Paraguay, DOI 10.1155/2019/7307803. Computational and Mathematical Methods in Medicine. 2019. URL: https://www.hindawi.com/journals/cmmm/2019/7307803/?utm_medium=author&utm_source=Hindawi
  • Gustavo Sosa-Cabrera and Miguel García-Torres and Santiago Gómez-Guerrero and Christian E. Schaerer and Federico Divina, A Multivariate approach to the Symmetrical Uncertainty Measure: Application to Feature Selection Problem, DOI 10.1016/j.ins.2019.04.046. Information Sciences, Elsevier. 2019.
    URL: https://authors.elsevier.com/a/1YzDL4ZQDzkkp
In Congresses and Seminars:
  • Juan V. Bogado, Diego Stalder, Santiago Gómez, Christian Schaerer. Deep Learning-Based Dengue Cases Forecasting with Synthetic Data. Acepted to: Congresso Nacional de Matemática Aplicada e Computacional (CNMAC). Uberlandia, MG, 2019.
  • Gustavo Sosa-Cabrera, Miguel García-Torres, Santiago Gómez-Guerrero, Christian E. Schaerer, Federico Divina. Understanding a multivariate semi-metric in the search strategies for attributes subset selection. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2506
  • Emilio G. Sotto, Santiago Gómez-Guerrero, Christian E. Schaerer. Categorical PCA and multiple correlation in the study of the incidence of dengue fever in communities of Paraguay. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2391
  • Fabricio Mendoza, Sergio O. Mercado, Marcos Villagra. Deterministic graph spectral sparsification. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2311
  • Rodrigo Villalba, Christian Schaerer, Miguel García-Torres, Manuel Vázquez-Marrufo. Diagnosis of multiple sclerosis from EEG signal analysis using empirical mode decomposition and support vector machine. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2636
  • Marcos Ortega, Santiago Gómez-Guerrero, Fredy Ramı́rez, Héctor Estigarribia. Feature Selection with Multivariate Symmetrical Uncertainty to predict Dengue Cases using Deep Learning. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2341
  • Adrián Martínez, Francisco Medina, Jorge Daniel Mello. Principal component analysis in mixed epidemiological data. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, volume 6, number 2 (2018).
    https://proceedings.sbmac.org.br/sbmac/article/view/2404
  • Gustavo Sosa-Cabrera and Santiago Gómez-Guerrero and Christian E. Schaerer and Miguel García-Torres. Effect of Sample Representativeness in Multivariate Symmetrical Uncertainty for Categorical Attributes. 3rd Conference on Business Analytics in Finance and Industry, Santiago, Chile (2018).URL: http://www.bafi.cl/bafi2018/
  • Santiago Gómez-Guerrero. Nuevas métricas para análisis estadísticos. Presentación oral, workshop Ciencia de Datos 2018, Universidad Comunera, Asunción, Paraguay.
  • Emilio G. Sotto, Santiago Gómez-Guerrero, Christian Schaerer. Categorical PCA and Multiple Correlation in the Study of the Incidence of Dengue Fever. Poster format, workshop Ciencia de Datos 2018, Universidad Comunera, Asunción, Paraguay.

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