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Standard Membrane Feeding Assay for the Detection of Plasmodium falciparum Infection in Anopheles Mosquito Vectors
Published on: May 12, 2022
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Spatial analyses of Plasmodium knowlesi vectors with reference to control interventions in Malaysia
Sandthya Pramasivan1, Romano Ngui2, Nantha Kumar Jeyaprakasam3
1Department of Parasitology, Faculty of Medicine, Universiti Malaya (UM), Kuala Lumpur, Malaysia.
Parasites & Vectors
|October 9, 2023
Summary
Understanding Anopheles mosquito distribution in Malaysia is key to controlling Plasmodium knowlesi malaria. This study maps vector presence, aiding healthcare professionals in targeted malaria elimination efforts.
Area of Science:
- Medical Entomology
- Spatial Epidemiology
- Vector-borne Diseases
Background:
- The Leucosphyrus Group of Anopheles mosquitoes transmits malaria parasites like Plasmodium knowlesi from macaques to humans.
- Plasmodium knowlesi is the most common zoonotic malaria parasite in Malaysia, necessitating vector distribution knowledge for control.
Purpose of the Study:
- To map the distribution of the Leucosphyrus Group of Anopheles mosquitoes in Malaysia.
- To correlate vector distribution with Plasmodium knowlesi malaria cases for targeted interventions.
Main Methods:
- Utilized historical vector data (1957-2021) and created distribution maps.
- Developed a predictive logistic regression model incorporating significant environmental factors.
- Employed Inverse Distance Weighting (IDW) for interpolation and overlaid with environmental variables.
Main Results:
- High vector abundances identified in specific regions of Sarawak, Pahang, and Sabah.
- Anopheles mosquitoes predominantly found in Peninsular Malaysia, Sabah, and Sarawak, with lower densities in southern Peninsular Malaysia and western Sarawak.
- The predictive model achieved 75.3% overall accuracy, with water bodies, elevation, temperature, forest loss, and cover as significant factors.
Conclusions:
- Provides crucial insights into the spatial distribution of Anopheles mosquitoes in Malaysia.
- The predictive vector map aligns with P. knowlesi malaria occurrences.
- Informs public health strategies for effective malaria control and elimination.

