Satellite Earth Observation Data in Epidemiological Modeling of Malaria, Dengue and West Nile Virus: A Scoping Review
| Autor: | Ioannis Kioutsioukis, Alexia Tsouni, Elisavet Parselia, Nikolaos I. Stilianakis, Gkikas Magiorkinis, Christos Hadjichristodoulou, Charalampos Kontoes |
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| Rok vydání: | 2019 |
| Předmět: |
Earth observation
West Nile virus Science 030231 tropical medicine malaria medicine.disease_cause Dengue fever 03 medical and health sciences 0302 clinical medicine Medizinische Fakultät vector-borne diseases medicine epidemiological modeling West Nile Virus ddc:610 030212 general & internal medicine biology Ensemble forecasting Transmission cycle biology.organism_classification medicine.disease dengue Data science Variety (cybernetics) mosquito-borne infectious diseases Geography Earth Observation for health entomological data General Earth and Planetary Sciences Satellite (biology) scoping review Satellite Earth Observation data Malaria |
| Zdroj: | Remote Sensing, Vol 11, Iss 16, p 1862 (2019) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs11161862 |
| Popis: | Earth Observation (EO) data can be leveraged to estimate environmental variables that influence the transmission cycle of the pathogens that lead to mosquito-borne diseases (MBDs). The aim of this scoping review is to examine the state-of-the-art and identify knowledge gaps on the latest methods that used satellite EO data in their epidemiological models focusing on malaria, dengue and West Nile Virus (WNV). In total, 43 scientific papers met the inclusion criteria and were considered in this review. Researchers have examined a wide variety of methodologies ranging from statistical to machine learning algorithms. A number of studies used models and EO data that seemed promising and claimed to be easily replicated in different geographic contexts, enabling the realization of systems on regional and national scales. The need has emerged to leverage furthermore new powerful modeling approaches, like artificial intelligence and ensemble modeling and explore new and enhanced EO sensors towards the analysis of big satellite data, in order to develop accurate epidemiological models and contribute to the reduction of the burden of MBDs. |
| Databáze: | OpenAIRE |
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