Sellers’ Revisited: A Big Data Reassessment of Historical Outbreaks of Bluetongue and African Horse Sickness due to the Long-Distance Wind Dispersion of Culicoides Midges

摘要

The possibility that outbreaks of bluetongue (BT) and African horse sickness (AHS) might occur via long distance wind dispersion (LDWD) of their insect vector (Culicoides spp.) was proposed by R.F. Sellers in a series of papers published between 1977 and 1991. These investigated the role of LDWD in outbreaks, including that of BT in Portugal (1956) and AHS in Spain (1966), by means of examining synoptic chart inferred trajectories. Using internationally accessible climate data-sets of atmospheric conditions, we investigated six of the scenarios described in Sellers’ papers, but allowing for the dispersal of individual midges, modelled as particles, from the purported sources. For this re-analysis, we used a custom-built Big Data application (“TAPPAS”) which couples a user-friendly web-interface with an established atmospheric dispersal model (“HYSPLIT”). For the two AHS outbreaks (Cyprus 1960 and Spain 1966) there was strong support from our re-analysis of the role of LDWD, but for the BT outbreaks, the reassessments were more complex, and for one of these (Western Turkey in 1977) we could discount LDWD as the means of direct introduction of the virus. By contrast, while the outbreak in Cyprus (1977) showed LDWD was a plausible means of introduction, there is an apparent inconsistency in that the outbreaks were localised whilst the dispersion events covered much of the island. For Portugal (1956), LDWD from Morocco on the dates suggested by Sellers is very unlikely to have been the pathway for introduction, and for the detection of serotype 2 in Florida (1982) LDWD from Cuba would require an assumption of a very long survival time for the midges (i.e. 30 hours) in the air column. Except for the western Turkey example, the BT reanalyses show the limitation of LDWD modelling when used by itself, and indicate the need for the integration of susceptible host population distribution (and other covariate) data into the modelling process. We predict that molecular methods, and particularly the comparison of full genome sequences of the virus at the purported source and the incursion site, will have an increasingly important role in providing validation for inferred LDWD.