Space–Time Clustering Characteristics of Malaria in Bhutan at the End Stages of Elimination

Kinley Wangdi, Kinley Penjor, Tobgyal, Saranath Lawpoolsri, Ric N. Price, Peter W. Gething, Darren J. Gray, Elivelton Da Silva Fonseca and Archie C. A. Clements
Additional contact information
Kinley Wangdi: Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia
Kinley Penjor: Vector-Borne Diseases Control Program, Department of Public Health, Ministry of Health, Gelephu 31101, Bhutan
Tobgyal: Vector-Borne Diseases Control Program, Department of Public Health, Ministry of Health, Gelephu 31101, Bhutan
Saranath Lawpoolsri: Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand
Ric N. Price: Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT 0810, Australia
Peter W. Gething: Faculty of Health Sciences, Curtin University, Bentley, WA 6102, Australia
Darren J. Gray: Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia
Elivelton Da Silva Fonseca: Institute of Geography, Federal University of Uberlândia, Uberlândia, MG 38408-100, Brazil
Archie C. A. Clements: Faculty of Health Sciences, Curtin University, Bentley, WA 6102, Australia

IJERPH, 2021, vol. 18, issue 11, 1-12

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 Plasmodium falciparum and Plasmodium vivax 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%) P. vivax 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 P. falciparum 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 P. vivax 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 P. vivax and P. falciparum 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.

Keywords: Bhutan; malaria; space; time; clustering; SaTScan (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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