Interpreting predictive maps of disease:highlighting the pitfalls of distribution models in epidemiology

Wardrop, Nicola A. and Geary, Matthew and Osborne, Patrick E. and Atkinson, Peter M. (2014) Interpreting predictive maps of disease:highlighting the pitfalls of distribution models in epidemiology. Geospatial Health, 9 (1). pp. 237-246. ISSN 1827-1987

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Abstract

The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps). These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread) can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

Item Type:
Journal Article
Journal or Publication Title:
Geospatial Health
Additional Information:
M1 - 1
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700
Subjects:
ID Code:
77196
Deposited By:
Deposited On:
16 Dec 2015 15:28
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Oct 2020 03:41