Geographic information systems and the distribution of Schistosoma mansoni in the Nile delta

Malone, John B.; Abdelrahman, Mahmoud A. E.; Bahy, Mohamed M. El; Huh, Oscar K.; Shafik, Magda A.; Bavia, Maria Emília

doi:10.1016/s0169-4758(97)01009-0

Cited by 66 publications

(32 citation statements)

References 13 publications

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“…Malone et al (1997) for Schistosoma mansoni and S. haematobium in the Nile Delta in Egypt and Bavia et al (1999) for S. mansoni in the state of Bahia in Brazil, developed a GIS model using various satellite sources to obtain normalized difference vegetation index (NDVI) and Tmax data which -together with other factors -were correlated to schistosomiasis transmission in the aforementioned human schistosomiasis endemic areas. Malone et al (1998) and Yilma and Malone (1998) developed a GIS model to forecast transmission and control animal fasciolosis in the east of Africa using climate as well as remote sensing data.…”

Section: Remote Sensing Datamentioning

confidence: 99%

Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary project

Fuentes

2006

Geospat Health

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Abstract. Fasciolosis caused by Fasciola hepatica in various SouthAmerican countries located on the slopes of the Andes has been recognized as an important public health problem. However, the importance of this zoonotic hepatic parasite was neglected until the last decade. Countries such as Peru and Bolivia are considered to be hyperendemic areas for human and animal fasciolosis, and other countries such as Chile, Ecuador, Colombia and Venezuela are also affected. At the beginning of the 1990s a multidisciplinary project was launched with the aim to shed light on the problems related to this parasitic disease in the Northern Bolivian Altiplano. A few years later, a geographic information system (GIS) was incorporated into this multidisciplinary project analysing the epidemiology of human and animal fasciolosis in this South American Andean region. Various GIS projects were developed in some Andean regions using climatic data, climatic forecast indices and remote sensing data.Step by step, all these GIS projects concerning the forecast of the fasciolosis transmission risk in the Andean mountain range were revised and in some cases updated taking into account new data. The first of these projects was developed on a regional scale for the central Chilean regions and the proposed model was validated on a local scale in the Northern Bolivian Altiplano. This validated mixed model, based on both fasciolosis climatic forecast indices and normalized difference vegetation index values from Advanced Very High Resolution Radiometer satellite sensor, was extrapolated to other human and/or animal endemic areas of Peru and Ecuador. The resulting fasciolosis risk maps make it possible to show the known human endemic areas of, mainly, the Peruvian Altiplano, Cajamarca and Mantaro Peruvian valleys, and some valleys of the Ecuadorian Cotopaxi province. Nevertheless, more climate and remote sensing data, as well as more accurate epidemiological reports, have to be incorporated into these GIS projects, which should be considered the key in understanding fasciolosis transmission in the Andes.

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Section: Remote Sensing Datamentioning

confidence: 99%

Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary project

Fuentes

2006

Geospat Health

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“…The influence of climate and environmental variables to the distribution of schistosomiasis was documented by Brown (1994) and Appleton (1978). The use of GIS for the study of schistosomiasis was also done in several other countries: in Asia (Cross et al 1996), China , Seto et al 2002, Yang et al 2005, Ethiopia , Egypt (Malone et al 1994, 1997, Abdel-Rahman et al 2001, Uganda (Kabatereine et al 2004), Tanzania (Brooker et al 2001), Chad . In Brazil, one of the first studies trying to correlate disease distribution with environmental variables was conducted by Bavia et al (2001), in Bahia.…”

mentioning

confidence: 99%

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

Guimarães

Freitas

Dutra

et al. 2006

Mem. Inst. Oswaldo Cruz

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“…Literature reports on GIS medical and veterinary applications include malaria (Beck et al, 1994), Rift Valley fever (Linthicum et al, 1987), filariosis (Thompson et al, 1996), African trypanosomosis (Rogers and Randolph, 1993), theileriosis (Lessard et al, 1990), Onchocerca (Richards, 1993), Leishmania (Cross et al, 1996), Amblyomma variegatum (Hugh-Jones et al, 1992), Lyme disease (Kitron et al, 1992), Fasciola (Zukowski et al, 1991;Malone, 1997), and Schistosoma (Cross and Bailey, 1984;Malone et al, , 1997.…”

Section: Introductionmentioning

confidence: 99%

Veterinary Parasitology

Taylor¹,

Coop²,

Wall³

2015

177

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Geographic information systems and the distribution of Schistosoma mansoni in the Nile delta

Cited by 66 publications

References 13 publications

Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary project

Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary project

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

Veterinary Parasitology

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