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

• Published in: Malaria Journal
• Main Authors: Jason Smith, Lloyd Tahani, Albino Bobogare, Hugo Bugoro, Francis Otto, George Fafale, David Hiriasa, Adna Kazazic, Grant Beard, Amanda Amjadali, Isabelle Jeanne
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2017
• Subjects: Malaria; Solomon Islands; Guadalcanal; Climate; Rainfall; Early warning; Arctic medicine. Tropical medicine; RC955-962; Infectious and parasitic diseases; RC109-216; Arctic
• Online Access: https://doi.org/10.1186/s12936-017-2120-5; https://doaj.org/article/483938ef7a7a4c139a8421490f550872

Abstract 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 $${\text{R}}^{2}{_{\text{LOOCV}}} = 0. 6 3$$ R 2 LOOCV = 0.63 as did Mann–Whitney U test results showing that rainfall below or above specific thresholds was significantly associated with above or below ...