Spatial-Epidemiological Modelling in Megacities: Statistical and Spatial Analysis for Urban Health under a Changing Climate

University of Bielefeld, School of Public Health03-07 September 2012

University of Bielefeld, School of Public Health, Department of Public Health Medicine

Background
Global climate change and urban health are of global concern because the majority of the world’s population live in urban areas. Health problems are particularly prevalent in the rapidly urbanising megacities of developing countries, where a growing number of residents live in slums. Moreover, urban health in developing countries is increasingly affected by the diverse effects of global climate change, e.g. through droughts, inundations and an increased burden of infectious and non-infectious diseases and injuries. Research on the complex of health and the environment in urban areas of developing countries is urgently needed. Although transdisciplinary research in this scientific area is gaining importance, capacity building measures are still rare.

Approach
We offer a one-week seminar that focuses on statistical analysis and spatial-epidemiological modelling in the context of urban health in megacities of developing countries. Seminar topics are concentrating on health and the urban environment under a changing climate, including megacity development, burden of disease, and socio-ecological health determinants. The aim is to combine theoretical and lab work on statistical analysis and spatial-epidemiological modelling techniques in a transdisciplinary approach. We expect 30 participants with at least half of them being from developing countries.

Expected outcomes
Our participants will get a deeper understanding of the spatial and epidemiological dimensions of urban health under the view of climate change. Participants will be able to understand the multiple dimensions of health problems in megacities of developing countries and to apply statistical techniques which are commonly used in health sciences and in geography. They will further be able to work more effectively in collaboration with other disciplines for understanding and investigating multidisciplinary problems. These measures will enable them to develop sustainable strategies for the improvement of living conditions in megacities of developing countries.

Exploring Spatial Analysis Techniques for Quantifying Landscape Structure and Pygmy Rabbit Habitat Selection at Multiple Scales

Society for Range Management ConferenceSociety for Range Management Conference, Spokane, WA, 28 January to 03 February 2012

Virginia Harris

“High resolution remotely sensed images (~ 1 m pixels) are becoming increasingly accessible at little to no cost. These images present new opportunities to explore landcover mapping and wildlife habitat modeling at finer scales. These fine scale images may be particularly useful for mapping rangeland vegetation composed of smaller life forms (e.g. shrubs and grasses rather than trees) and habitat for wildlife species in these rangelands. The pygmy rabbit (Brachylagus idahoensis) is a species of special concern in the Great Basin shrub steppe and adjacent mountain ranges in the western US. Its primary habitat is in the sagebrush steppe dominated by plant communities that include big sagebrush (Artemisia tridentata) and rabbit brush (Chrysothamnus spp.), however its selection for levels of shrub cover and spatial arrangement of shrubs is not well known. This study evaluated selection for landscape structure by pygmy rabbits at two study sites in the Lemhi Valley of east central Idaho across a series of extents and landscape metrics. Specifically the landscape composition and spatial patterns of shrub cover within 6, 60, and 120-m buffers around known pygmy rabbit locations were quantified on a map with 3-m pixel resolution and four shrub canopy cover classes (0-5%, 5-15%, 15-25%,and >25%). A sum rank nonparametric test wasused to evaluate habitat selection in proportion to different shrub cover classes, patch shape, evenness, and patch interspersion. Selection by pygmy rabbits differed between study sites and among buffer sizes. Results indicated that pygmy rabbits were selecting habitat based on landscape structure. Specifically, the rabbits showed selection for areas of 15-25% shrub cover within the smallest buffer size, and interspersion of cover levels across the landscape as indicated by the largest buffer size.  Furthermore, it was demonstrated that fine scale remote sensing and landscape pattern analysis are useful  tools in assessments of habitat selection by pygmy rabbits at multiple scales.”