Using species distribution models to predict potential hot-spots for Rift Valley Fever establishment in the United Kingdom

Simons, R. R.L., Croft, S., Rees, E. , Tearne, O., Arnold, M. E. and Johnson, N. (2019) Using species distribution models to predict potential hot-spots for Rift Valley Fever establishment in the United Kingdom. PLoS ONE, 14(12), e0225250. (doi: 10.1371/journal.pone.0225250) (PMID:31869335) (PMCID:PMC6927579)

Abstract

Vector borne diseases are a continuing global threat to both human and animal health. The ability of vectors such as mosquitos to cover large distances and cross country borders undetected provide an ever-present threat of pathogen spread. Many diseases can infect multiple vector species, such that even if the climate is not hospitable for an invasive species, indigenous species may be susceptible and capable of transmission such that one incursion event could lead to disease establishment in these species. Here we present a consensus modelling methodology to estimate the habitat suitability for presence of mosquito species in the UK deemed competent for Rift Valley fever virus (RVF) and demonstrate its application in an assessment of the relative risk of establishment of RVF virus in the UK livestock population. The consensus model utilises observed UK mosquito surveillance data, along with climatic and geographic prediction variables, to inform six independent species distribution models; the results of which are combined to produce a single prediction map. As a livestock host is needed to transmit RVF, we then combine the consensus model output with existing maps of sheep and cattle density to predict the areas of the UK where disease is most likely to establish in local mosquito populations. The model results suggest areas of high suitability for RVF competent mosquito species across the length and breadth of the UK. Notable areas of high suitability were the South West of England and coastal areas of Wales, the latter of which was subsequently predicted to be at higher risk for establishment of RVF due to higher livestock densities. This study demonstrates the applicability of outputs of species distribution models to help predict hot-spots for risk of disease establishment. While there is still uncertainty associated with the outputs we believe that the predictions are an improvement on just using the raw presence points from a database alone. The outputs can also be used as part of a multidisciplinary approach to inform risk based disease surveillance activities.

• Item Type: Articles
• Additional Information: Funding: This work was funded through the Animal Health and Welfare ERA-NET consortium (https://www.anihwa.eu/) under ARBONET (‘Epidemiological models for control of arboviral disease for Europe'). This work was conducted by the UK consortium members. The UK funder is acknowledged as the Department for the Environment, Food and Rural Affairs, and the Scottish and Welsh Governments through grant SE0550.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Rees, Dr Eleanor
• Authors: Simons, R. R.L., Croft, S., Rees, E., Tearne, O., Arnold, M. E., and Johnson, N.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: PLoS ONE
• Publisher: Public Library of Science
• ISSN: 1932-6203
• ISSN (Online): 1932-6203
• Copyright Holders: Copyright: © 2019 Simons et al.
• First Published: First published in PLoS ONE 14(12):e0225250
• Publisher Policy: Reproduced under a Creative Commons license