Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.
Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.
['Carvalho|B M|BM|', 'Rangel|E F|EF|', 'Vale|M M|MM|']
D000818:Animals D001179:Arthropod Vectors D057231:Climate Change D004175:Diptera D017753:Ecosystem D018884:Ixodes D008962:Models, Theoretical D014224:Triatoma
vector-borne diseases Aedes Anopheles Culicoides Ixodes Lutzomyia Phlebotomus Triatoma ensemble modelling spatial distribution