Mapping a Plasmodium transmission spatial suitability index in Solomon Islands: a malaria monitoring and control tool
Abstract Background Malaria remains a challenge in Solomon Islands, despite government efforts to implement a coordinated control programme. This programme resulted in a dramatic decrease in the number of cases and mortality however, malaria incidence remains high in the three most populated provinc...
Published in: | Malaria Journal |
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Main Authors: | , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
BMC
2018
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Subjects: | |
Online Access: | https://doi.org/10.1186/s12936-018-2521-0 https://doaj.org/article/a6703eb2fe544fe79ad6c615e161764b |
Summary: | Abstract Background Malaria remains a challenge in Solomon Islands, despite government efforts to implement a coordinated control programme. This programme resulted in a dramatic decrease in the number of cases and mortality however, malaria incidence remains high in the three most populated provinces. Anopheles farauti is the primary malaria vector and a better understanding of the spatial patterns parasite transmission is required in order to implement effective control measures. Previous entomological studies provide information on the ecological preferences of An. farauti but this information has never before been gathered and “translated” in useful tools as maps that provide information at both the national level and at the scale of villages, thus enabling local targeted control measures. Methods A literature review and consultation with entomology experts were used to determine and select environmental preferences of An. farauti. Remote sensing images were processed to translate these preferences into geolocated information to allow them to be used as the basis for a Transmission Suitability Index (TSI). Validation was developed from independent previous entomological studies with georeferenced locations of An. farauti. Then, TSI was autoscaled to ten classes for mapping. Results Key environmental preferences for the An. farauti were: distance to coastline, elevation, and availability of water sources. Based on these variables, a model was developed to provide a TSI. This TSI was developed using GIS and remote sensing image processing, resulting in maps and GIS raster layer for all the eight provinces and Honiara City at a 250 m spatial resolution. For a TSI ranging from 0 as not suitable to 13 as most suitable, all the previous collections of An. farauti had mean TSI value between 9 and 11 and were significantly higher than where the vector was searched for and absent. Resulting maps were provided after autoscaling the TSI into ten classes from 0 to 9 for visual clarity. Conclusions The TSI model ... |
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