Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands

Smith, Jason, Tahani, Lloyd, Bobogare, Albino, Bugoro, Hugo, Otto, Francis, Fafale, George, Hiriasa, David, Kazazic, Adna, Beard, Grant, Amjadali, Amanda and Jeanne, Isabelle 2017, Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands, Malaria journal, vol. 16, no. 1, pp. 1-16, doi: 10.1186/s12936-017-2120-5.

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Title Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands
Author(s) Smith, Jason
Tahani, Lloyd
Bobogare, Albino
Bugoro, Hugo
Otto, Francis
Fafale, George
Hiriasa, David
Kazazic, Adna
Beard, Grant
Amjadali, Amanda
Jeanne, IsabelleORCID iD for Jeanne, Isabelle
Journal name Malaria journal
Volume number 16
Issue number 1
Article ID 472
Start page 1
End page 16
Total pages 16
Publisher Springer Nature
Place of publication London, Eng.
Publication date 2017-11-21
ISSN 1475-2875
Keyword(s) Anopheles farauti
Early warning
Solomon Islands
Climate Change
Environmental Monitoring
Mosquito Vectors
Summary BACKGROUND: Malaria control remains a significant challenge in the Solomon Islands. Despite progress made by local malaria control agencies over the past decade, case rates remain high in some areas of the country. Studies from around the world have confirmed important links between climate and malaria transmission. This study focuses on understanding the links between malaria and climate in Guadalcanal, Solomon Islands, with a view towards developing a climate-based monitoring and early warning for periods of enhanced malaria transmission. METHODS: Climate records were sourced from the Solomon Islands meteorological service (SIMS) and historical malaria case records were sourced from the National Vector-Borne Disease Control Programme (NVBDCP). A declining trend in malaria cases over the last decade associated with improved malaria control was adjusted for. A stepwise regression was performed between climate variables and climate-associated malaria transmission (CMT) at different lag intervals to determine where significant relationships existed. The suitability of these results for use in a three-tiered categorical warning system was then assessed using a Mann-Whitney U test. RESULTS: Of the climate variables considered, only rainfall had a consistently significant relationship with malaria in North Guadalcanal. Optimal lag intervals were determined for prediction using R2 skill scores. A highly significant negative correlation (R = - 0.86, R2 = 0.74, p < 0.05, n = 14) was found between October and December rainfall at Honiara and CMT in northern Guadalcanal for the subsequent January-June. This indicates that drier October-December periods are followed by higher malaria transmission periods in January-June. Cross-validation emphasized the suitability of this relationship for forecasting purposes [Formula: see text]  as did Mann-Whitney U test results showing that rainfall below or above specific thresholds was significantly associated with above or below normal malaria transmission, respectively. CONCLUSION: This study demonstrated that rainfall provides the best predictor of malaria transmission in North Guadalcanal. This relationship is thought to be underpinned by the unique hydrological conditions in northern Guadalcanal which allow sandbars to form across the mouths of estuaries which act to develop or increase stagnant brackish marshes in low rainfall periods. These are ideal habitats for the main mosquito vector, Anopheles farauti. High rainfall accumulations result in the flushing of these habitats, reducing their viability. The results of this study are now being used as the basis of a malaria early warning system which has been jointly implemented by the SIMS, NVBDCP and the Australian Bureau of Meteorology.
Language eng
DOI 10.1186/s12936-017-2120-5
Field of Research 1108 Medical Microbiology
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, The Authors
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Document type: Journal Article
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