Characterisation of malaria vector habitats using remote sensing and GIS

被引:0
作者
Jeganathan C. [1 ]
Khan S.A. [2 ]
Chandra R. [3 ]
Singh H. [4 ]
Srivastava V. [1 ]
Raju P.L.N. [1 ]
机构
[1] Geoinformatics Division, Indian Institute of Remote Sensing, Dehradun, Uttaranchai
[2] Regional Medical Research Centre, NE Region, ICMR, Dibrugarh, Assam
[3] Department of Zoology, M.G. Chitrakoot Gramoday, Vishwavidyalay, Chitrakoot, Satna, M.P.
[4] Forestry and Ecology Division, Indian Institute of Remote Sensing, Dehradun, Uttaranchal
关键词
Malaria; Geographical Information System; Remote Sensing; Malaria Case; Malaria Vector;
D O I
10.1007/BF02989911
中图分类号
学科分类号
摘要
As per the World Health Organisation, about 260 million people worldwide are infected with malaria and 1.5 to 2.7 million patients die annually due to this most significant infectious parasite. In this study two important species. Anopheles dirus and Anopheles minimus, have been studied in North Lakhimpur and Dibrugarh districts of Assam in the North-Eastern India. Remote sensing has certainly provided a clue in identifying the symptoms of mosquito habitat and Geographical Information System (GIS) has helped us to analyse and identify two species with several environmental parameters. Remote sensing inputs have made a difference in understanding the presence of these species in two districts which are having similar meteorological conditions. It has been found that the nature of the breeding ground for mosquitoes and their spreading patterns are not so complex as generally expected.
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页码:31 / 36
页数:5
相关论文
共 14 条
[1]  
Barnes C.M., Cibula W.G., Some implications of remote sensing technology in insect control programmes including mosquitoes, Mosquito News, 39, pp. 271-282, (1979)
[2]  
Census of India, (1991)
[3]  
Connor S.J., Thomson M.C., Flasse S.P., Environmental Information systems in malaria risk mapping and epidemic forecasting, Disaster, 22, 1, pp. 39-56, (1998)
[4]  
Connor S.J., Thomson M.C., Molyneux D.H., Forecasting and prevention of epidemic malaria-new perspectives on an old problem, Parasitilogia, 41, pp. 439-448, (1999)
[5]  
Gazetteer of India: Assam State Gazetteer, (1999)
[6]  
Hay S.I., Packer M.J., Rogers D.J., The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors lbr disease, Int. J. Remote Sensing, 18, 14, pp. 2899-2930, (1997)
[7]  
Hay S.I., Omumbo J.A., Crag M.H., Earth observation, GIS and Plasmodium falciparum malaria in Sub-Saharan Africa, Advances in Parasitol., 47, pp. 172-215, (2000)
[8]  
Hugh Jones M., Applications of remote sensing to the identification of the habitats of parasites and disease vectors, Parasitology Today, 5, 8, pp. 244-251, (1989)
[9]  
Srivastava A., Nagpal B.N., Saxena R., Subbarao S.K., Predictive habitat modelling for forest malaria vector species An. dirus in India-A GIS based approach, Current science, 80, 9, pp. 1129-1134, (2001)
[10]  
Thomson M.C., Connor S.J., Milligan P.J.M., The ecology of malaria-as seen from earth observation satellites, Annals of Trop. Med. and Parasitol, 90, 3, pp. 243-264, (1996)