Tracking the distribution and impacts of diseases with biological records and distribution modelling

Purse, Bethan V. ORCID: https://orcid.org/0000-0001-5140-2710; Golding, Nick. 2015 Tracking the distribution and impacts of diseases with biological records and distribution modelling [in special issue: Fifty years of the Biological Records Centre] Biological Journal of the Linnean Society, 115 (3). 664-677. https://doi.org/10.1111/bij.12567

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Abstract/Summary

Species distribution modelling is widely used in epidemiology for mapping spatial patterns and the risk of introduction of diseases and vectors and also for predicting how exposure may alter given future environmental change, motivated by the high societal impact and the multiple environmental drivers of disease outbreaks. Although pathogens and vectors have historically been sparsely recorded, monitoring systems and media sources are generating novel, online data sources on occurrence. Moreover, increasing ecological realism is being incorporated into distribution modelling techniques, focussing on dispersal, biotic interactions and evolutionary constraints that shape species distributions alongside abiotic factors and biases in recording effort, common to pathogens and vectors and wildlife species. Considering pathogens and arthropod vector systems with high impact on plant, animal and human health, the present review describes how biological records for vectors and pathogens arise, introduces the concepts behind distribution models and illustrates the potential for ecologically realistic distribution models to yield insight into the establishment and spread of pathogens. Because distribution modellers aim to provide policy makers with evidence and maps for planning and evaluation of disease mitigation measures, we highlight factors that currently constrain direct translation of models to policy. Disease distributions will be better understood and mapped in the future given improved occurrence data access and integration and combined (correlative and mechanistic) modelling approaches that are developed iteratively in concert with stakeholders.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/bij.12567
UKCEH and CEH Sections/Science Areas:	Reynard
ISSN:	0024-4066
Additional Keywords:	biotic interactions, environmental change, niche concept, risk maps, species
NORA Subject Terms:	Ecology and Environment Data and Information
Date made live:	14 Aug 2015 09:40 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/511541

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