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Space-Time Clustering Characteristics of Malaria in Bhutan at the End Stages of Elimination. | LitMetric

AI Article Synopsis

  • Malaria cases in Bhutan have significantly decreased in the past decade, and a study was conducted to analyze trends from 2010 to 2019 as the country aims for malaria elimination in 2022.
  • Researchers used data from the Bhutan Vector-Borne Disease Control Program and employed space-time cluster analysis to identify patterns, finding 768 confirmed malaria cases, with significant clusters occurring between April and September.
  • The most notable clusters were located in central Bhutan, particularly in Sarpang District from January 2010 to June 2012, revealing high-risk areas and highlighting the need for further research to understand the causes of persistent malaria transmission.

Article Abstract

Malaria in Bhutan has fallen significantly over the last decade. As Bhutan attempts to eliminate malaria in 2022, this study aimed to characterize the space-time clustering of malaria from 2010 to 2019. Malaria data were obtained from the Bhutan Vector-Borne Disease Control Program data repository. Spatial and space-time cluster analyses of and cases were conducted at the sub-district level from 2010 to 2019 using Kulldorff's space-time scan statistic. A total of 768 confirmed malaria cases, including 454 (59%) cases, were reported in Bhutan during the study period. Significant temporal clusters of cases caused by both species were identified between April and September. The most likely spatial clusters were detected in the central part of Bhutan throughout the study period. The most likely space-time cluster was in Sarpang District and neighboring districts between January 2010 to June 2012 for cases of infection with both species. The most likely cluster for infection had a radius of 50.4 km and included 26 sub-districts with a relative risk (RR) of 32.7. The most likely cluster for infection had a radius of 33.6 km with 11 sub-districts and RR of 27.7. Three secondary space-time clusters were detected in other parts of Bhutan. Spatial and space-time cluster analysis identified high-risk areas and periods for both and malaria. Both malaria types showed significant spatial and spatiotemporal variations. Operational research to understand the drivers of residual transmission in hotspot sub-districts will help to overcome the final challenges of malaria elimination in Bhutan.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196969PMC
http://dx.doi.org/10.3390/ijerph18115553DOI Listing

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