期刊论文详细信息
Parasites & Vectors | |
Spatial analyses of Plasmodium knowlesi vectors with reference to control interventions in Malaysia | |
Research | |
Nantha Kumar Jeyaprakasam1  Romano Ngui2  Indra Vythilingam3  Sandthya Pramasivan3  Jonathan Wee Kent Liew4  Van Lun Low5  | |
[1]Biomedical Science Program, Center for Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia | |
[2]Department of ParaClinical Sciences, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak (UNIMAS), Sarawak, Malaysia | |
[3]Department of Parasitology, Faculty of Medicine, Universiti Malaya (UM), Kuala Lumpur, Malaysia | |
[4]Environmental Health Institute, National Environment Agency, Singapore, Singapore | |
[5]Tropical Infectious Diseases Research & Education Centre (TIDREC), Universiti Malaya (UM), Kuala Lumpur, Malaysia | |
关键词: Anopheles; Distribution; Leucosphyrus group; Predictive vector map; Malaysia; | |
DOI : 10.1186/s13071-023-05984-x | |
received in 2023-07-31, accepted in 2023-09-25, 发布年份 2023 | |
来源: Springer | |
![]() |
【 摘 要 】
BackgroundMalaria parasites such as Plasmodium knowlesi, P. inui, and P. cynomolgi are spread from macaques to humans through the Leucosphyrus Group of Anopheles mosquitoes. It is crucial to know the distribution of these vectors to implement effective control measures for malaria elimination. Plasmodium knowlesi is the most predominant zoonotic malaria parasite infecting humans in Malaysia.MethodsVector data from various sources were used to create distribution maps from 1957 to 2021. A predictive statistical model utilizing logistic regression was developed using significant environmental factors. Interpolation maps were created using the inverse distance weighted (IDW) method and overlaid with the corresponding environmental variables.ResultsBased on the IDW analysis, high vector abundances were found in the southwestern part of Sarawak, the northern region of Pahang and the northwestern part of Sabah. However, most parts of Johor, Sabah, Perlis, Penang, Kelantan and Terengganu had low vector abundance. The accuracy test indicated that the model predicted sampling and non-sampling areas with 75.3% overall accuracy. The selected environmental variables were entered into the regression model based on their significant values. In addition to the presence of water bodies, elevation, temperature, forest loss and forest cover were included in the final model since these were significantly correlated. Anopheles mosquitoes were mainly distributed in Peninsular Malaysia (Titiwangsa range, central and northern parts), Sabah (Kudat, West Coast, Interior and Tawau division) and Sarawak (Kapit, Miri, and Limbang). The predicted Anopheles mosquito density was lower in the southern part of Peninsular Malaysia, the Sandakan Division of Sabah and the western region of Sarawak.ConclusionThe study offers insight into the distribution of the Leucosphyrus Group of Anopheles mosquitoes in Malaysia. Additionally, the accompanying predictive vector map correlates well with cases of P. knowlesi malaria. This research is crucial in informing and supporting future efforts by healthcare professionals to develop effective malaria control interventions.Graphical Abstract【 授权许可】
CC BY
© BioMed Central Ltd., part of Springer Nature 2023
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202311101288747ZK.pdf | 3744KB | ![]() |
|
MediaObjects/12888_2023_5278_MOESM2_ESM.docx | 20KB | Other | ![]() |
1165KB | Image | ![]() |
|
MediaObjects/13046_2023_2846_MOESM6_ESM.pdf | 313KB | ![]() |
|
MediaObjects/13046_2023_2846_MOESM8_ESM.pdf | 161KB | ![]() |
|
Fig. 3 | 393KB | Image | ![]() |
Fig. 1 | 3144KB | Image | ![]() |
Fig. 4 | 1271KB | Image | ![]() |
MediaObjects/12974_2023_2896_MOESM2_ESM.tif | 1653KB | Other | ![]() |
Fig. 2 | 1482KB | Image | ![]() |
13100_2023_302_Article_IEq7.gif | 1KB | Image | ![]() |
Fig. 1 | 192KB | Image | ![]() |
12951_2015_111_Article_IEq4.gif | 1KB | Image | ![]() |
Fig. 1 | 50KB | Image | ![]() |
MediaObjects/42004_2023_1020_MOESM3_ESM.mov | 3708KB | Other | ![]() |
12951_2017_270_Article_IEq8.gif | 1KB | Image | ![]() |
12951_2017_270_Article_IEq9.gif | 1KB | Image | ![]() |
【 图 表 】
12951_2017_270_Article_IEq9.gif
12951_2017_270_Article_IEq8.gif
Fig. 1
12951_2015_111_Article_IEq4.gif
Fig. 1
13100_2023_302_Article_IEq7.gif
Fig. 2
Fig. 4
Fig. 1
Fig. 3
【 参考文献 】
- [1]
- [2]
- [3]
- [4]
- [5]
- [6]
- [7]
- [8]
- [9]
- [10]
- [11]
- [12]
- [13]
- [14]
- [15]
- [16]
- [17]
- [18]
- [19]
- [20]
- [21]
- [22]
- [23]
- [24]
- [25]
- [26]
- [27]
- [28]
- [29]
- [30]
- [31]
- [32]
- [33]
- [34]
- [35]
- [36]
- [37]
- [38]
- [39]
- [40]
- [41]
- [42]
- [43]
- [44]
- [45]
- [46]
- [47]
- [48]
- [49]
- [50]
- [51]
- [52]
- [53]
- [54]
- [55]
- [56]
- [57]
- [58]
- [59]
- [60]
- [61]
- [62]
- [63]
- [64]
- [65]
- [66]
- [67]
- [68]
- [69]
- [70]
- [71]
- [72]
- [73]
- [74]
- [75]
- [76]
- [77]
- [78]
- [79]
- [80]
- [81]
- [82]
- [83]
- [84]
- [85]
- [86]
- [87]
- [88]
- [89]
- [90]
- [91]
- [92]
- [93]
- [94]
- [95]
- [96]
- [97]
- [98]
- [99]