Spatial and Temporal Epidemiology of Zoonotic Malaria Subpopulations in Kapit Division, Sarawak
Humans acquire Plasmodium knowlesi from forest-dwelling macaque monkeys through Anopheles mosquitoes, creating a new threat to public health and to the national efforts in eliminating malaria. Previous population genetic and genomic studies demonstrate that human infections in Malaysian Borneo are d...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/40164/6/3.Thesis%20Master%20Sc._Nur%20Emyliana%20Binti%20Yunos_fulltext.pdf |
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| Summary: | Humans acquire Plasmodium knowlesi from forest-dwelling macaque monkeys through Anopheles mosquitoes, creating a new threat to public health and to the national efforts in eliminating malaria. Previous population genetic and genomic studies demonstrate that human infections in Malaysian Borneo are divided into two divergent subpopulations, each associated with long-tailed macaque (termed Cluster 1 subpopulation) and pig-tailed macaque (Cluster 2 subpopulation) reservoir hosts. It was suggested that man-made activities and environmental modifications trigger the increasing cases of knowlesi malaria. Since there is a steady increase of these zoonotic infections over the past decade in Sarawak, particularly in the Kapit division, this study aimed to identify hotspots of P. knowlesi infections and to determine the association with risk activities at a geographical scale using the Geographic Information System (GIS) tool. A total of 1,064 P. knowlesi infections from 2014 to 2019 in the Kapit and Song districts of Kapit Division, Sarawak were identified by nested PCR assays. The demographic data showed that the median age were 41 years old with more males (64%) were infected. Activities associated with forest or forest fringe which include farming less than two kilometres from the longhouse (33.1%), longhouses activities (18.2%) and logging (14.6%) made the top three activities related to the acquisition of P. knowlesi infections. The overall P. knowlesi infections as well as both for subpopulations exhibited clustering pattern of distribution throughout the 6-year period (Average Nearest Neighbour, R < 1; P < 0.01), except for 2015 and 2019 where a random distribution pattern of infections was observed for the Cluster 2 subpopulation (P > 0.5). The Kernel Density Analysis (KDA) indicated that areas within a 20 km radius of Kapit town and within a 5 km radius of Song town were classified as high risk for knowlesi malaria transmission. Spatial pattern for the overall P. knowlesi infections identified as high-risk areas were mainly associated with land-use particularly for logging and tree planting. Areas that were potentially becoming high risk for both Cluster 1- and Cluster 2-type infections were also observed, and these areas were mainly used for logging activities. The satellite images revealed a widespread network of logging road trails at these areas with changes in forest density over the years. This potentially provided easy access to the forest for more activities such as hunting and opening of new longhouses near forest fringe. Continued identification of malaria hotspots provides useful information for the Vector-Borne Disease Control Programme in their efforts to control and plan proper elimination strategies and surveillance systems to mitigate P. knowlesi transmission to humans. |
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