Ecology and prevention of Lyme borreliosis 351 Marieta A.H. Braks, Sipke E. van Wieren, Willem Takken and Hein Sprong (eds.) Ecology and prevention of Lyme borreliosis Ecology and control of vector-borne diseases Volume 4 DOI 10.3920/978-90-8686-838-4_25, © Wageningen Academic Publishers 2016 25. Grasping risk mapping Marieta A.H. Braks 1* , Annemieke C. Mulder 1 , Arno Swart 1 and William Wint 2 1 National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Antonie van Leeuwenhoeklaan 9, 3720 BA Bilthoven, the Netherlands; 2 Environmental Research Group Oxford, Department of Zoology, University of Oxford, South Parks Road, OX1 3PS, United Kingdom; marieta.braks@rivm.nl Abstract A picture is worth a thousand words, and so many Lyme borreliosis risk maps have been produced and published in the scientific and grey literature or on websites. The focus of these is usually on the technical and scientific aspects, and facilitating interpretation by their users is frequently overlooked. Designing the maps is made difficult by the complexities of the disease system, the often black box methods used to produce the models from which the maps are derived, and the fact that many of the maps are of risk indicators rather than direct risk measures used by the public health community. In the current chapter, we explore the various research questions, data and tools that underlie available risk maps. We investigate how risk maps fit in a risk analysis framework of Lyme borreliosis, including risk assessment, risk management and risk communication, exemplified with risk maps at Pan-European, national and local scale. Keywords: exposure, hazard, risk maps, risk analyses, scale Introduction Risk maps used in public health are visual representations of intricate geographic data that provide a quick overview of the health risks. Ample examples of Lyme borreliosis risk maps for Europe and the United States have emerged, usually depicting the spatial distribution of (infected) ticks or (less often) disease incidence. The users often interpret these intuitively, rather than objectively understanding the full scope of the model output, which is often derived from spatial modelling techniques (Mannelli et al. 2016, Vanwambeke et al. 2016a). The intuitive aspect of a risk map is both its strength and its weakness. In this chapter, we aim to provide some guidance on the objective interpretation of risk maps. First, we examine two topics that largely determine the features of a risk map, namely: (1) the underlying research question (what kind of risk metric is mapped and for whom and why?); and (2) availability of data and tools (how can available data be mapped usefully?). Second, we review different kinds of risk maps available for Lyme borreliosis, with special attention to those concerning the Netherlands. It is not our objective to review the various spatial modelling techniques (Ozdenerol 2015), but rather to evaluate the utility of the output maps for risk analysis of Lyme borreliosis. In conclusion, we provide guidance for the stakeholders (i.e. risk map consumers) and for researchers (i.e. map developers) confronted with these issues. Research question While most people have strong intuitive ideas about what ‘risk’ entails, defining, interpreting and subsequently dealing with risks in evidence-based policy making appears to be rather an intricate task. Because risk can mean different things to different people or in different circumstances, risk cannot be captured in a single definition. An important source of confusion in the interpretation is https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-838-4_25 - Sunday, December 19, 2021 5:04:26 AM - IP Address:54.152.42.200