Rabies is a zoonosis of great relevance in public health and responsible for considerable
economic losses to livestock. To determine the risk of rabies transmission to herbivores in the
state of Tocantins, a knowledge-driven predictive model was developed in which a
questionnaire contained in the Geographic Information System environment of the QGIS®
software (version 3.4.10), was filled up internally through Boolean logic and database queries.
This, composed of information plans containing data related to epidemiological surveillance
such as outbreaks of herbivores, positive bats and registered roosts, in addition to data on land
use, for the year 2015. The risk assesment was based on scenario trees based on the concepts
of receptivity and vulnerability, which ordered the questionnaire responses hierarchically. The
trees were joined by an association matrix to obtain the risk scores, which were grouped into
space-time series with a 90-day interval. The obtaining of the risk on a continuous spatial
surface was performed by interpolating the scores using the ordinary kriging algorithms in the
GS + ® software (version 7). The predictive model was validated by overlapping the occurrence
of outbreaks with the risk estimates, and its global accuracy was assessed using a ROC Curve
developed in the R® software (version 3.6). The proposed model was able to estimate the risk
of circulation of variant 3 of the rabies virus in herbivores, with the ROC curve showing
moderate accuracy in predicting the occurrence of outbreaks, of which out of a total of 25
outbreaks in 2015, 22 occurred in areas classified as most at risk. These results allow us to
affirm that the proposed model can be used in directing disease control actions in areas of higher
risk, allowing for a better allocation of resources by the official veterinary service, and can be
applied in other regions according to the need.
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