abstract

• Dengue is a major public health concern mainly in tropical and subtropical environments worldwide. Despite several attempts to prevent this disease occurring in tropical regions of Mexico, it has not yet been controlled. This work focused on spatial modeling of confirmed dengue fever cases that occurred during the period 2010–2014 in the Huasteca Potosina region of Mexico. Multivariable Logistic Regression Modeling (MLRM) was used to determine the relationship between explanatory variables and the presence/absence of dengue. Model performance was evaluated using the area under curve (AUC) of the relative operating characteristic (ROC); AUC > 0.95. A high spatial resolution map was created to reveal the most probable patterns of dengue risk. Our results can be used for targeted control and prevention programs at local and regional levels. This methodology can be applied to other major diseases that are spatially distributed in accordance with environmental factors. © 2019, © 2019 Informa UK Limited, trading as Taylor %26 Francis Group.

authors

• Aguirre Salado Carlos Arturo
• Aguirre-Salado A.I.
• Reyes Cárdenas Oscar
• Reyes Hernández Humberto
• Santana-Juárez M.V.
• Soubervielle Montalvo Carlos
• Sánchez Díaz Guillermo
• Sánchez-Hernández D.

publication date

• 2019-01-01

published in

• International Journal of Environmental Health Research  Journal

keywords

• Dengue fever; Landsat 8 OLI; neglected tropical disease

Digital Object Identifier (DOI)

• 10.1080/09603123.2019.1700938

PubMed ID

• 31835907

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