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Satellite Earth Observation data in epidemiological modeling of malaria, dengue and West Nile Virus: A scoping review

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Autore
Parselia E., Kontoes C., Tsouni A., Hadjichristodoulou C., Kioutsioukis I., Magiorkinis G., Stilianakis N.I.
Data
2019
Language
en
DOI
10.3390/rs11161862
Soggetto
Electrooptical devices
Learning algorithms
Machine learning
Observatories
Satellites
Viruses
Dengue
Earth observation data
Earth observations
Entomological data
Epidemiological modeling
Infectious disease
Malaria
Scoping review
Vector-borne disease
West Nile Virus
Diseases
MDPI AG
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Abstract
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. © 2019 by the authors.
URI
http://hdl.handle.net/11615/77955
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19743]
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