Escobar, L. E., Qiao, H., & Peterson, A. T. (2016). Forecasting Chikungunya spread in the Americas via data-driven empirical approaches. Parasites & Vectors, 1–12. http://doi.org/10.1186/s13071-016-1403-y
The goal of this paper was to predict the spread of Chikungunya in the Americas during the epidemic using 1) ecological niche models of Aedes aegypti and Aedes albopictus, 2) air travel data as a measure of imported cases and 3) fitted curves to reported CHIKV data as a measure of local transmission. Case data was reported from the Pan-American Health Organization by country for the Americas. In addition to the lack of standardization in reporting, the case data showed ‘surveillance fatigue’, in which reporting became erratic and uneven in the later stages of the epidemic, suggesting that reports from earlier in the epidemic may create more accurate models. By combining imported and local cases, the model predictions based on earlier reports matched later case data, suggesting that air travel is an important and accurate predictor of country-to-country transmission.
The ecological niches were estimated using climate envelopes, which create ellipsoids, similar to a convex hull method. The minimum-volume ellipsoid method of climate envelopes creates semi-axes which reduce the Euclidian distances between occurrence points in environmental space. Rather than using all of the WorldClim variables, the authors used a principle components analysis to reduce any correlation amongst them, and chose the first three principle components as their environmental axes. The authors chose to use occurrence data from the global distribution of the vectors, in an attempt to estimate the fundamental niche and not the realized niche. The output of the climate envelope was a niche centroid, where the semi-axes crossed in environmental space. Hotspots were defined as areas closest to the niche centroid in environmental space. It seems, then, that the envelope is not a boundary classifier, but ranks locations based on distance to the niche centroid, so may not perform as well at the edges of the species range as estimators such as support vector machines. They found that the niche models generally agreed with CHIKV case data, with areas closest to the niche centroid in the Carribean, where CHIKV was first introduced in the Americas.
The use of a minimum-volume ellipsoid was well suited to the study of the start of the CHIKV epidemic because this is also the area most well-suited for the vector. I do not think it would be as appropriate when applied to more temperate areas further from the niche centroid, because the centroid seems to be where the model is most accurate.