Identification of Suitable Areas for African Horse Sickness Virus Infections in Spanish Equine Populations

Abstract

African horse sickness (AHS) is one of the most important vector-borne viral infectious diseases of equines, transmitted mainly by Culicoides spp. The re-emergence of Culicoides-borne diseases in Europe, such as the recent bluetongue (BT) or Schmallenberg outbreaks, has raised concern about the potential re-introduction and further spread of AHS virus (AHSV) in Europe. Spain has one of the largest European equine populations. In addition, its geographical, environmental and entomological conditions favour AHSV infections, as shown by the historical outbreaks in the 1990s. The establishment of risk-based surveillance strategies would allow the early detection and rapid control of any potential AHSV outbreak. This study aimed to identify the areas and time periods that are suitable or at high risk for AHS occurrence in Spain using a GIS-based multicriteria decision framework. Specifically risk maps for AHS occurrence were produced using a weighted linear combination of the main risk factors of disease, namely extrinsic incubation period, equine density and distribution of competent Culicoides populations. Model results revealed that the south-western and north-central areas of Spain and the Balearic Islands are the areas at the highest risk for AHSV infections, particularly in late summer months. Conversely, Galicia, Castile and Leon and La Rioja can be considered as low-risk regions. This result was validated with historical AHS and BT outbreaks in Spain, and with the Culicoides vector distribution area. The model results, together with current Spanish equine production features, should provide the foundations to design risk-based and more cost-effective surveillance strategies for the early detection and rapid control potential of AHS outbreaks in Spain.

Modeling the global distribution of Culicoides imicola: an Ensemble approach

“…The expansion is believed to be facilitated by northward distribution of the infected Culicoides species mainly C. imicola and availability of competent and efficient vectors such as C. obsoletus and C. pulicaris 10–12 . AHS is an infectious disease considered to be the most lethal viral disease of equines, especially horses 7,13 and is endemic in sub-Saharan Africa 7 . Schmallenberg virus is a recently emerged virus, identified in North Rhine-Westphalia, Germany, during the summer of 2011 14 , which has since spread across Europe inflicting congenital deformities in the offspring of infected adult ruminants 15 .…”

“…Schmallenberg virus is a recently emerged virus, identified in North Rhine-Westphalia, Germany, during the summer of 2011 14 , which has since spread across Europe inflicting congenital deformities in the offspring of infected adult ruminants 15 . The recent emergence of two Culicoides-borne diseases (Bluetongue and Schmallenberg) in Europe has raised concerns around the potential introduction and further spread of AHS virus into temperate parts of the world 13 .…”

Updating the global occurrence of Culicoides imicola, a vector for emerging viral diseases

“…AHS is native to sub-Saharan Africa 4 . It is an infectious disease considered to be the most lethal viral disease of equines, especially in horses 4,11 . The recent emergence of the two Culicoides-borne diseases (BT and Schmallenberg) in Europe has raised a concern for the potential introduction and further spread of AHS virus in temperate parts of the world as well 11 .…”

Spatial and temporal epidemiological analysis in the Big Data era

“…de Glanville et al (2014) generated suitability maps for African swine fever for Africa and used Monte-Carlo sensitivity analysis to express uncertainty in relation to model outputs. Other animal health applications of spatial MCDA have addressed animal diseases such as African horse sickness in Spain and Rift Valley fever in Italy (Tran et al, 2013;Sanchez-Matamoros et al, 2014). The increasing use of MCDA in the environmental sciences has resulted in further development of MCDA methodologies to reduce the influence of subjectivity of individual criteria weights on the risk score outcome (Yemshanov et al, 2013;Feizizadeh et al, 2014;Jankowski et al, 2014;Ligmann-Zielinska and Jankowski, 2014).…”