new article: ecological modelling to improve remote sensing disease risk analysis

new article: ecological modelling to improve remote sensing disease risk analysis

November 30, 2015

A new article by our former PhD student Dr. Yvonne Walz just got published. The article “Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling” aims at the advantages of using spatial modelling approaches for disease risk analysis using remote sensing. Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

http://geospatialhealth.net/index.php/gh/article/view/398

you may also like:

Snow and ice research in the Arctic

Snow and ice research in the Arctic

Our colleagues Dr. Mirjana Bevanda and Dr. cand. Jakob Schwalb-Willmann recently conducted another UAS-based fieldwork in the Arctic, focusing on temporal variability of snow and ice property. Utilizing VTOL UAS platforms equipped with LiDAR, multispectral, and...

Exploring Wetland Ecosystems in the Rhön Biosphere Reserve

Exploring Wetland Ecosystems in the Rhön Biosphere Reserve

As part of our ongoing collaboration with our EOCap4Africa project partners, two members of the EORC (Dr. Insa Otte, Lilly Schell) at the University of Würzburg recently took a field trip to the Rhön Biosphere Reserve with our visiting scientists. We visited two...

Spring Vibes on Our Lunch Break

Spring Vibes on Our Lunch Break

With the first warm days of spring finally arriving, a small fraction of our team already took full advantage of the sunshine during lunch break—gathering outside to soak up the mild weather and enjoy a few well-earned moments of relaxation. Some of us have just...

Terrabyte Workshop at EORC

Terrabyte Workshop at EORC

Tag: Meeting, Workshop Terrabyte Workshop at EORC This week, a two-day terrabyte workshop took place at EORC (Earth Observation Research Cluster), hold by staff members of DLR ( Dr. Jonas Eberle, Julian Zeidler, Peter Zellner). Thanks to many hours of presentations...