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:

New staff member Luisa Pflumm

New staff member Luisa Pflumm

Luisa Pflumm joined the Earth Observation Research Cluster in May 2024 as part of the EcoGlob project and is working with the UAS team in the context of remote sensing for biodiversity and nature conservation. She received her Bachelor's degree in Geography from the...

New team member: Ása Dögg Adalsteinsdottir

New team member: Ása Dögg Adalsteinsdottir

Ása Dögg Adalsteinsdottir joined the Earth Observation Research Cluster in May 2024 as a member of the EO4CAM project team. After earning a bachelor's degree in geography from the University of Iceland, she moved to Germany to study in our EAGLE master's program. She...

NEW TEAM MEMBER: CHRISTIAN SCHÄFER

NEW TEAM MEMBER: CHRISTIAN SCHÄFER

Christian Schäfer joined the EO4CAM project in May 2024. He received his Master's degree in 2017 from Julius-Maximilians-Universität Würzburg (JMU), focusing on GIS-based synthesis of transboundary soil maps. During his work in the JMU BigData@Geo project, he enhanced...

GGW talk on geodata, mobility and social media

GGW talk on geodata, mobility and social media

On Monday the 13th of May our PhD students Ariane Droin and Johannes Mast were holding a talk at the Geographische Gesellschaft Würzburg organised by the Fachschaft Geographie about 'Geodaten, Mobilität und soziale Medien. Big data und die lokale Perspektive der...

NetCDA kick-off workshop

NetCDA kick-off workshop

Yesterday, on May 16th, the partners of the project "European Academic Network for Capacity Development in Climate Change Adaptations in Africa" (NetCDA) met to jointly and officially kick-off their project. The NetCDA team at the University of Würzburg invited all...