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Development of a Snakebite risk map for Sri Lanka

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dc.contributor.author Ediriweera, D.S. en
dc.contributor.author Kasturiratne, A. en
dc.contributor.author Pathmeswaran, A. en
dc.contributor.author Gunawardena, N.K.
dc.contributor.author Wijayawickrama, B.A.
dc.contributor.author Jayamanne, S.F.
dc.contributor.author Isbister, G.K.
dc.contributor.author Dawson, A.
dc.contributor.author Giorgi, E.
dc.contributor.author Diggle, P.J.
dc.contributor.author Lalloo, D.G.
dc.contributor.author de Silva, H.J.
dc.date.accessioned 2017-09-08T08:55:23Z
dc.date.available 2017-09-08T08:55:23Z
dc.date.issued 2016
dc.identifier.citation Sri Lanka Medical Association, 129th Anniversary International Medical Congress. 2016: 128 en_US
dc.identifier.issn 0009-0895
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/17364
dc.description Oral Presentation Abstract (OP 43), 129th Anniversary International Medical Congress, Sri Lanka Medical Association, 25-27 July 2016 Colombo, Sri Lanka en_US
dc.description.abstract INTRODUCTION: Snakebite is a public health problem in Sri Lanka and about 37,000 patients are treated in government hospitals annually. At present, health care resources which are required to manage snakebite are distributed based on the administrative boundaries, rather than based on scientific risk assessment. OBJECTIVES: The aim of the study is to develop a snakebite risk map for Sri Lanka. METHOD: Epidemiological data was obtained from a community-based island-wide survey. The sample was distributed equally among the nine provinces. 165,665 participants (0.8%of the country’s population) living in 1118 Grama Niladhari divisions were surveyed. Generalized linear and generalized additive models were used for exploratory data analysis. Model-based geostatistics was used to determine the geographical distribution of snakebites. Monte Carlo maximum likelihood method was used to obtain parameter estimates and plug-in spatial predictions were obtained. Probability contour maps (PCM) were developed to demonstrate the spatial variation in the probability that local incidence does or does not exceed national snakebite incidence. RESULTS: Individual point estimate snakebite incidence map and PCM were developed to demonstrate the national incidence of snakebite in Sri Lanka. Snakebite hotspots and cold spots were identified in relation to the national snakebite incidence rate. Risk maps showed a within-country spatial variation in snakebites. CONCLUSIONS: The developed risk maps provide useful information for healthcare decision makers to allocate resources to manage snakebite in Sri Lanka. en_US
dc.language.iso en_US en_US
dc.publisher Sri Lanka Medical Association en_US
dc.subject Snake Bites en_US
dc.title Development of a Snakebite risk map for Sri Lanka en_US
dc.type Conference Abstract en_US


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    Papers presented at local and international conferences by the Staff of the Faculty of Medicine

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