Modeling spatial pattern of dengue in North Central Mexico using survey data and logistic regression

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.

KEYWORDS:

• Dengue fever
• neglected tropical disease
• Landsat 8 OLI

Acknowledgments

We express our gratitude to the Ministry of Health of the State Government of San Luis Potosí for providing the database used in this research. The authors also want to thank three anonymous reviewers whose insightful comments and suggestions greatly improved earlier versions of this manuscript.

Declaration of conflict statement

Authors declare no conflict of interest.