Thirty years of use and improvement of remote sensing, applied to epidemiology: From early promises to lasting frustration
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Cited by (94)
Geoinformatics, spatial epidemiology, and public health
2023, Geoinformatics for Geosciences: Advanced Geospatial Analysis using RS, GIS and Soft ComputingThe role of remote sensing during a global disaster: COVID-19 pandemic as case study
2022, Remote Sensing Applications: Society and EnvironmentClimate variability, satellite-derived physical environmental data and human leptospirosis: A retrospective ecological study in China
2019, Environmental ResearchCitation Excerpt :In addition to climate, the role of the physical environment on leptospirosis transmission is also important, such as the presence of water bodies or flooding and variation in land cover (Della Rossa et al., 2016; Ledien et al., 2017; Matsushita et al., 2018). Currently, remote-sensing (RS) technologies provide a broad range of physical environment data at various spatial and temporal scales, which can help to better understand disease epidemiology (Hamm et al., 2015; Herbreteau et al., 2007). Such satellite-derived data have been widely used to identify environmental drivers of vector-borne disease such as malaria (Ebhuoma and Gebreslasie, 2016) or water-borne diseases such as cholera (Xu et al., 2015), but very few leptospirosis studies to date have used these RS data to quantify the role of environmental risk factors in the temporal pattern of leptospirosis incidence.
Emerging challenges of infectious diseases as a feature of land systems
2019, Current Opinion in Environmental SustainabilityCitation Excerpt :We further propose concrete areas of collaboration between disease ecologists and land use scientists in this context. Since the advent of remote sensing, numerous studies have looked into associations between land use and land use changes and infectious pathogens, reservoir hosts, and vectors, at a range of spatial scales [6,12•,13,14] have reviewed such studies. Gottdenker et al. [12•] identified biases, toward certain pathogens (e.g. vector-borne), certain environments (with higher Net Primary Productivity), and toward the effects of land use changes on host or vector community composition.