Landscape Dynamics and Risk Modeling of Human Alveolar Echinococcosis

Danson, F. Mark; Craig, Philip S.; Man, Wai Kwong; Shi, Dongquan; Giraudoux, Patrick

doi:10.14358/pers.70.3.359

Cited by 37 publications

(30 citation statements)

References 19 publications

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“…Studies investigating the relationship between Em and landscape using remote sensing techniques in southern Gansu Province, China, have also previously identified strong links between landscape composition and HAE prevalence (Danson et al, 2004, Giraudoux, Raoul, Pleydell, et al, 2013b. These studies suggested that grassland and tree/shrub habitats capable of sustaining cyclically high populations of susceptible intermediate hosts were key spatial determinants of Em transmission (Danson et al, 2003), and indicated that landscape composition could provide a useful predictor of Em and HAE (Giraudoux et al, 2003;Giraudoux, Raoul, Pleydell, et al, 2013;Pleydell et al, 2008).…”

Section: Remote Sensing For Landscape-disease Studiesmentioning

confidence: 95%

“…Present within Europe, North America, Central Asia, China, Japan, and the former USSR, it is a highly pathogenic zoonosis (Ammann & Eckert, 1996), with over 94% mortality in untreated patients ten years after diagnosis (Wang et al, 2010). The spatial distribution of Em is highly variable, with significant regional and local differences in parasite prevalence resulting in patchy distributions of endemicity (Eckert et al, 2001;Giraudoux et al, 2006;Giraudoux, Raoul, Afonso, Ziadinov, Yan, et al, 2013) within which transmission hotspots of much larger prevalence may occur (Danson, Craig, Man, Shi, & Giraudoux, 2004;Said-Ali et al, 2013). Examples include Gansu and Sichuan Provinces, China, where prevalence rates of N 10% have been observed locally (Craig et al, 1992;Li et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling

Marston

Giraudoux

Armitage

et al. 2016

Remote Sensing of Environment

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International audienceEchinococcus multilocularis (Em), a parasitic tapeworm, is responsible for a significant burden of human disease across continental Asia. Here, we use a time-series of MODIS 16-day 250 m Enhanced Vegetation Index (EVI) satellite data to quantify the seasonal vegetation dynamics across a study area in Serxu County, Sichuan Province, China, in relation to the presence of the Em intermediate host Ochotona curzoniae (plateau pika) and Ochotona cansus (Gansu pika) (here merged to Ochotona spp.). A series of derived phenological metrics are analysed using the random forests statistical method to determine the relative importance of seasonal vegetation characteristics. Results indicate negative relationships between Ochotona spp. presence and EVI showing a preference for low-biomass habitats. However, EVI values during green-up and senescence periods are also shown to be important, potentially resulting from improved detectability of low-biomass grassland habitats at these times. Improved detection of Ochotona spp. preferred habitats via time-series EVI imagery offers better understanding of the distributions of this Em host, and the potential for monitoring the changes in Ochotona spp. optimal habitat distributions resulting from landscape change. This could aid the identification of villages at increased risk of infection, enabling preventive strategies to be adopted

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Section: Remote Sensing For Landscape-disease Studiesmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling

Marston

Giraudoux

Armitage

et al. 2016

Remote Sensing of Environment

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“…The spatial distribution of HAE is strongly correlated to land cover and land use (Danson et al, 2002(Danson et al, , 2004, both of which are temporally and spatially dynamic. Obtaining reliable estimates of land cover type and extent in China is difficult, with values differing depending on the source of the data.…”

Section: Hae Infection In Chinamentioning

confidence: 99%

“…Landscape classifications are not only used for mapping: one can analyse the landscape pattern for the purposes of modelling. This methodology has been followed by Danson et al (2004) in Gansu province for HAE. An empirical link between landscape and HAE was found using a stepwise multiple regression model with inputs including land cover proportions within buffer zones of radius 750 m, 1500 m, 1750 m and 3500 m from a village centre.…”

Section: Hae Infection In Chinamentioning

confidence: 99%

Ecological epidemiology: the role of landscape structure in the transmission risk of the fox tapeworm Echinococcus multilocularis (Leukart 1863) (Cestoda: Cyclophyllidea: Taeniidae)

Graham

Danson

Craig

2005

Progress in Physical Geography: Earth and Environment

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The larval form of the fox tapeworm Echinococcus multilocularis causes a fatal liver infection in humans and has high prevalence in western China. The tapeworm lifecycle involves small mammal populations and canids, such as foxes and dogs. Human contact with infected canids may lead to the transmission of the worm to humans, causing the disease human alveolar echinococcosis. This paper introduces the tapeworm and reviews the current understanding of its transmission ecology in relation to each component of its lifecycle. Recent research indicates that landscape plays an important role in creating the necessary habitat conditions for natural transmission. Defining the landscape involves the use of satellite imagery, land cover classification and spatial analysis. The link between disease, remote sensing and landscape ecology is an expanding research area and potentially an important one in relation to Echinococcus multilocularis and alveolar echinococcosis.

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“…This brings many difficulties to retrieve the vegetation cover in the basin. Neural networks are increasingly used for the interpretation of remotely sensed data and the estimation of surface biophysical properties [9][10] . This success is explained by their high computational efficiency and their ability to accurately approximate complex non-linear functions 11 .…”

Section: Introductionmentioning

confidence: 99%

Retrieving vegetation cover by using BP neural network based on Beijing-1 microsatellite data

Chen

Zhang

2008

SPIE Proceedings

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This paper presents a BP neural network method to retrieve vegetation cover of the Drainage basin of Miyun Reservoir based on the new remote sensing data -"Beijing-1" microsatellite data. And the retrieval result was compared with the one retrieved by the traditional methods. The compared results showed that for vegetation cover retrieval in mountainous areas, neural network has the advantage of precise simulation of non-linear transmission over traditional methods, especially for mountainous vegetation cover retrieval which traditional methods usually fail.

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Landscape Dynamics and Risk Modeling of Human Alveolar Echinococcosis

Cited by 37 publications

References 19 publications

Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling

Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling

Ecological epidemiology: the role of landscape structure in the transmission risk of the fox tapeworm Echinococcus multilocularis (Leukart 1863) (Cestoda: Cyclophyllidea: Taeniidae)

Retrieving vegetation cover by using BP neural network based on Beijing-1 microsatellite data

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