Objective.
Estimate the probabilistic potential of introduction of the causative agent of influenza type A in Mexico, using geo-intelligence applied to health.
Methods.
Ecological study of 1,973 influenza outbreaks with a high degree of pathogenicity, worldwide during the period 2014-2016. Geospatial modeling was developed with geo-intelligence tools such as spatial representation, a relational model, spatial characterization of the inoculum source with the maximum entropy model and the receiver operating characteristic (ROC) curve, using multicriteria spatial analysis. This was validated with the Moran index and geographically weighted regression.
Results.
Isochrones (at an initial distance of 548 km) were estimated for health risks and their exponential growth; at the fourth isochrone, the east and west coasts of the United States of America and a part of Central America were identified as possible areas that favor the introduction of the pathogen. Also, a COR curve = 0.923 was obtained; two risk periods for introduction were identified (September-March and April-August, with north-south and south-north trajectories, respectively) with high positive autocorrelation for geospatial modeling; and in one scenario, more than half of Mexico was found to be at high risk of introduction, with an estimated 78 million people exposed. A positive association was identified between significant risk areas (p < 0.001).
Conclusion.
More than 50% of Mexican territory was found to be at risk of introduction of the causative agent of influenza type A, with approximately 70% of the population exposed.