Browsing by Author "Sivanantharajah, S."

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    Cross-sectional study to assess risk factorsfor leishmaniasis in an endemic region in Sri Lanka
    (American Society of Tropical Medicine and Hygiene, 2013) Ranasinghe, S.; Wickremasinghe, R*.; Munasinghe, A.; Hulangamuwa, S.; Sivanantharajah, S.; Seneviratne, K.; Bandara, S.; Athauda, I.; Navaratne, C.; Silva, O.; Wackwella, H.; Matlashewski, G.; Wickremasinghe, R.
    Sri Lanka reports significantly more cutaneous leishmaniasis (CL) cases than visceral leishmaniasis (VL) cases, both of which are caused by Leishmania donovani MON-37. A cross-sectional study conducted in an area with a high prevalence of CL prevalent included 954 participants of an estimated population of 61,674 to estimate the number of CL cases, ascertain whether there is a pool of asymptomatic VL cases, and identify risk factors for transmission. A total of 31 cases of CL were identified, of whom 21 were previously diagnosed and 10 were new cases. Using rK39 rapid diagnostic test to detect antibodies against Leishmania spp., we found that only one person was seropositive but did not have clinical symptoms of CL or VL, which indicated low transmission of VL in this area. χ(2) test, independent sample t-test, and multivariate analysis of socio demographic and spatial distribution of environmental risk factors showed that living near paddy fields is associated with increased risk for transmission of CL (P ≤ 0.01).
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    Green Space Planning Using GIS and Remote Sensing for City of Colombo, Sri Lanka
    (Department of Zoology, University of Kelaniya, Kelaniya, Sri Lanka, 2014-06) Siriwardane, M. S. P. M.; Gunatilake, Jagath; Sivanantharajah, S.
    The rapid growth of human population, their demands, and constructed environment have replaced the natural environment in a significant way. Therefore, people reconsider building up natural environment with artificial constructions. This study is focused on sustainable development of Urban Green Spaces (UGS), Geographic Information Systems (GIS) and Remote Sensing (RS) technologies are very important for the study as they have powerful spatial scientific approaches. The present study area was Colombo Municipal Council (CMC) administrative area with three objectives. Identification and analyzing of existing green areas and their patterns was one objective. This was done through supervised image classification method using high resolution satellite images. After extracting the vegetation cover, central place theory was used to understand the existing patterns. The second objective was to analyze the green areas with the natural and human factors, such as, buildings, transportation networks, bare lands, urban heat hot spots, air pollution contaminations etc. These factors were weighted under existing urban regulations in Sri Lanka and developed a multi criteria model for analyzing the suitability of expanding green spaces. According to the results, the most suitable area is less than 1% of the total area. But 39% of the land is suitable for expanding green spaces while another 40% cannot be expanded. Moderate suitable area is around 20%. Using these results three dimensional models and accessibility models were developed to understand the applicability of green spaces in selected portions of land. Cartographic and web based GIS outputs were created to disseminate the results as the third objective to engage responsible parties for the planning operations. Urban planners, designers and decision makers can use the results as a decision support system with the comments submitted by the community. The applicability of GIS and Remote Sensing improves the decision making power for planning green spaces towards sustainable conservation processes in urban environment.