Table 1.

Categories and objectives of main modeling techniques collected in this review.

Category	Model	Objective
Regression models	Generalized linear models (GLM)	Investigate the levels of tick aggregation at different spatial ranges, determine and disaggregate the drivers of tick density and probability of presence, and provide robust estimates of tick densities between landscape segments. Study the effect of environmental conditions on the prevalence of different stages of ticks and in the epidemiology of the tick-borne disease (TBD).
Species distribution modeling	Maximum entropy (MaxEnt)	Explore the limits of the potential distribution by extrapolating the environmental requirements of ticks. Analyze the possible spatial range of tick species, to explore how climate changes can shape the distribution of these species.
	Classification and regression tree (CART)	Review data on tick distribution and prevalence of TBD for a national TBD management approach using the current ecological and epidemiological information on ticks and the related diseases they transmit.
	Species distribution modeling (SDM)	Discuss and illustrate the precise boundaries of the present range of ticks based on computational map modeling and demonstrate the way in which local populations of these ticks differ in abundance towards the boundaries of the range.
	Ecological niche factor analysis (ENFA)	Measuring the extent to which the requirements of a given species deviate from average conditions and the extent to which the species is selective over the range of environmental conditions available in a country. Develop a rigorous definition of the climatic niche of a set of relevant tick species in a geographical area.