Spatial multi-criteria decision analysis for modelling suitable habitats of Ornithodoros soft ticks in the Western Palearctic region

Authors: VIAL, LAURENCE - Centro De Cooperation Internationale En Recherche Agronomique Pour Le Development (CIRAD); DUCHEYNE, ELS - Institute For Agricultural And Fisheries Research (ILVO); FILATOV, SERHII - National Scientific Center; McVey, David; SINDRYAKOVA, IRINA - Institute Of Virology; MORGUNOV, S YU - Institute Of Virology; Perez De Leon, Adalberto - Beto; KOLBASOV, DENIS - Institute Of Virology; DE CLERCQ, EVA - Catholic University Of Leuven

Submitted to: Veterinary Parasitology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2017
Publication Date: 10/30/2017
Citation: Vial, L., Ducheyne, E., Filatov, S., McVey, D.S., Sindryakova, I., Morgunov, S., Perez de Leon, A.A., Kolbasov, D., De Clercq, E. 2017. Spatial multi-criteria decision analysis for modelling suitable habitats of Ornithodoros soft ticks in the Western Palearctic region. Veterinary Parasitology. 249:2-16. https://doi.org/10.1016/j.vetpar.2017.10.022.

Interpretive Summary: This paper describes the use of a knowledge-based method for modelling the distribution of Ornithodoros ticks considered to be a threat for animal and human health in the Western Palearctic region. It presents a map for the region covering North Africa, Europe and the Caucasus and indicates areas suitable for the survival and establishment of such tick species. The aim of this exercise is to provide a basis to target ongoing vector surveillance programs, as is ongoing for example in European countries currently threatened by African swine fever. Many papers are published on the distribution of hard ticks, such as Ixodes ricinus causing Lyme borreliosis, or Rhipicephalus microplus causing babesiosis, but papers on soft tick distribution are rare. This is not because these soft ticks do not cause harm, but because they are more difficult to study and to collect in the field. As a consequence, reliable occurrence data for Ornithodoros soft ticks are scarce and the MCDA (Multi-Criteria Decision Analysis) method, which is based on literature review and expert knowledge, was preferred. We think that this paper is important in advancing not only the study of the occurrence of this tick community, but also the wider discussion on species models, its approaches and its application to entomology, epidemiology, and decision-making. In this study, we developed a broad scale distribution model for Ornithodoros soft ticks that are considered a threat for animal and human health in the Western Palearctic region. Although this model may not be able to capture the small-scale environments suited to the selected Ornithodoros tick community, its efficacy at a regional level was clearly demonstrated. It provides a very useful tool for the instigation of further soft tick vector surveillance programs and for cost-efficient collection of the data required to explore more data-driven models. This is the first time that a distribution model is provided for Western Palearctic soft ticks, which are hitherto poorly known and which present ecological features that complicate the determination of explanatory variables and model building.

Technical Abstract: Ticks are economically and medically important due to the injuries inflicted through their bite, and their ability to transmit pathogens to humans, livestock, and wildlife. Whereas hard ticks have been intensively studied, little is known about soft ticks, even though they can transmit several pathogens, including African Swine Fever Virus (ASFV) affecting domestic and wild suids or borreliae causing tick-borne relapsing fever (TBRF) in humans. As these represent a disease risk, we developed a regional model to identify suitable spatial areas for a community of nine Ornithodoros tick species (O. erraticus, O. sonrai, O. alactagalis, O. nereensis, O. tholozani, O. papillipes, O. tartakovskyi, O. asperus, O. verrucosus), which are considered a threat for animal and human health in the Western Palearctic region. Multi-Criteria Decision Analysis was used due to the relative scarcity of high-quality occurrence data. After an in-depth literature review on the ecological requirements of the selected tick community, five factors appeared critical for feeding activity and tick development. Two were linked to temperature: spring temperature exceeding 10°C to induce the end of winter soft tick quiescent period and a three-months summer temperature above 20°C to allow tick physiological activities. The other criteria concerned minimum and maximum limiting moisture, reflected either by precipitation, relative humidity or other factors able to retain moisture in arid zones. Annual precipitation above 750mm is detrimental, but Ornithodoros ticks struggle with less than 60mm, unless dry seasons are interrupted by small rain showers or water is provided by perennial rivers. A sensitivity analysis was done by performing multiple runs of the model altering the environmental variables, their suitability function, and their attributed weights. To validate the models, we used 355 occurrence data points, complemented by random points within sampled ecoregions. All models indicated suitable areas in the Mediterranean Basin and semi-desert areas in South-West and Central Asia. Most variability between models was observed along northern and southern edges of highly suitable areas. The predictions featured a relatively good accuracy with an average Area Under Curve (AUC) of 0.779. These first models provide a useful tool for estimating the global distribution of Ornithodoros ticks and targeting their surveillance in the Western Palearctic region.