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https://hdl.handle.net/1959.11/19700
Title: | Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia | Contributor(s): | Khormi, Hassan (author); Kumar, Lalit (author) | Publication Date: | 2016 | Open Access: | Yes | DOI: | 10.4081/gh.2016.416 | Handle Link: | https://hdl.handle.net/1959.11/19700 | Abstract: | We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model. The match between prediction and reality was found to be high. More than 90% of the observed malaria distribution points were associated with the currently known suitable climate conditions. Climate suitability for malaria is projected to decrease in India, southern Myanmar, southern Thailand, eastern Borneo, and the region bordering Cambodia, Malaysia and the Indonesian islands, while it is expected to increase in southern and south-eastern China and Taiwan. The climatic models for Anopheles mosquitoes presented here should be useful for malaria control, monitoring, and management, particularly considering these future climate scenarios. | Publication Type: | Journal Article | Source of Publication: | Geospatial Health, 11(3), p. 290-298 | Publisher: | Pagepress | Place of Publication: | Italy | ISSN: | 1970-7096 1827-1987 |
Fields of Research (FoR) 2008: | 090903 Geospatial Information Systems 050206 Environmental Monitoring |
Fields of Research (FoR) 2020: | 401302 Geospatial information systems and geospatial data modelling | Socio-Economic Objective (SEO) 2008: | 960303 Climate Change Models 960311 Social Impacts of Climate Change and Variability |
Socio-Economic Objective (SEO) 2020: | 190501 Climate change models 190103 Social impacts of climate change and variability |
Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Journal Article |
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