MSPTM 2019 Annual Scientific Conference
13 - 14 March 2019
InterContinental Kuala Lumpur

Abstract

Title

SPATIO-TEMPORAL DISTRIBUTION AND HOT SPOT ANALYSIS OF P. KNOWLESI INFECTIONS IN KAPIT DIVISION, SARAWAK

Type
Oral Presentation
Theme
Scaling Up Efforts in Tropical Disease and Vector Control through Evidence-Based Research
Topic
Malaria

Authors

Main Author
Nur Emyliana Yunos1
Presenting Author
Nur Emyliana Yunos1
Co-Author
Tarmiji Masron2
Hamidi Mohamad Sharkawi3
Balbir Singh1
Paul Cliff Simon Divis 1

Authors' Institution

Department / Institution / Country
Malaria Research Centre, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak / Universiti Malaysia Sarawak / Malaysia1
Centre of Spatially Integrated Digital Humanities, Faculty of Social Sciences and Humanities, / Universiti Malaysia Sarawak / Malaysia2
Sarawak State Health Department / Kapit Divisional Health Office / Malaysia3
Content
Abstract Content
Plasmodium knowlesi in human is a zoonotic infection acquired from forest-dwelling monkeys, creating a new threat to public health and in the malaria elimination efforts in Malaysia due to their nature of infection. Man-made activities and natural factors that modify the environment triggers the infection. Since there is a steady increase of P. knowlesi infections over the past decade in Sarawak, particularly in the Kapit division, we conducted a spatial and temporal distribution of this zoonotic malaria and identified the geographical hot spots of infection. A total of 471 P. knowlesi infections occurring from 2014 – 2017 in Kapit and Song districts, Sarawak were included in this study and confirmed by nested PCR assays. The demographic data showed that the most frequently infected were females (53%) and those involved in farming activities (46%). The result also showed that 73% of the total infected cases are at the age of 31 and above. The geolocations for each infection were mapped and analyzed using the Geographic Information System (GIS) tool. Using the Average Nearest Neighbor (ANN) and Moran’s I analyses, it was revealed that P. knowlesi infections in these two districts exhibit a clustering pattern of distribution. The Kernel Density Analysis (KDA) indicates that the hot spot locations surrounding Kapit (within 25 km along the river from Kapit town) and Song town (within 5 km radius) are classified as high-risk areas for malaria transmission. Malaria hot spot analysis based on the relevant information provides a useful method to overcome malaria by planning, control, and prevention of the morbidity, however, time-consistent updates are necessary. 
Keywords: Plasmodium knowlesi; Malaria; Geographic Information System (GIS); Hot spot
Requires Audio or Video system for Presentation?: Yes