Developing a predictive model for plasmodium knowlesi-susceptible areas in Malaysia using geospatial data and artificial neural networks
Plasmodium knowlesi is an emerging species for malaria in Malaysia, particularly in East Malaysia. This infection contributes to almost half of all malaria cases and deaths in Malaysia and poses a challenge in eradicating malaria. The aim of this study was to develop a predictive model for P. knowle...
Main Authors: | Hod, Rozita, Mokhtar, Siti Aisah, Muharam, Farrah Melissa, Shamsudin, Ummi Kalthom, Hashim, Jamal Hisham |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publications
2021
|
Online Access: | http://psasir.upm.edu.my/id/eprint/96673/1/ABSTRACT.pdf |
Similar Items
-
Geospatial and Ethnic Mapping of Plasmodium Knowlesi
Genetic Variants in Sabah
by: Daw Khin Saw Naing, et al.
Published: (2014) -
Reimagining zoonotic malaria control in communities exposed to Plasmodium knowlesi infection
by: Nurul Athirah Naserrudin, et al.
Published: (2022) -
The role of human behavior in Plasmodium knowlesi Malaria infection: a systematic review
by: Nurul Athirah Naserrudin, et al.
Published: (2022) -
The emerging threat of Plasmodium knowlesi Malaria infection: a concept paper on the vulnerable factors in human
by: Nurul Athirah Naserrudin, et al.
Published: (2022) -
Plasmodium knowlesi exhibits distinct in vitro drug susceptibility profiles from those of Plasmodium falciparum
by: van Schalkwyk, Donelly A., et al.
Published: (2019)