METHODS: The YOLOv4 model is modified using direct layer pruning and backbone replacement. The primary objective of layer pruning is the removal and individual analysis of residual blocks within the C3, C4 and C5 (C3-C5) Res-block bodies of the backbone architecture's C3-C5 Res-block bodies. The CSP-DarkNet53 backbone is simultaneously replaced for enhanced feature extraction with a shallower ResNet50 network. The performance metrics of the models are compared and analysed.
RESULTS: The modified models outperform the original YOLOv4 model. The YOLOv4-RC3_4 model with residual blocks pruned from the C3 and C4 Res-block body achieves the highest mean accuracy precision (mAP) of 90.70%. This mAP is > 9% higher than that of the original model, saving approximately 22% of the billion floating point operations (B-FLOPS) and 23 MB in size. The findings indicate that the YOLOv4-RC3_4 model also performs better, with an increase of 9.27% in detecting the infected cells upon pruning the redundant layers from the C3 Res-block bodies of the CSP-DarkeNet53 backbone.
CONCLUSIONS: The results of this study highlight the use of the YOLOv4 model for detecting infected red blood cells. Pruning the residual blocks from the Res-block bodies helps to determine which Res-block bodies contribute the most and least, respectively, to the model's performance. Our method has the potential to revolutionise malaria diagnosis and pave the way for novel deep learning-based bioinformatics solutions. Developing an effective and automated process for diagnosing malaria will considerably contribute to global efforts to combat this debilitating disease. We have shown that removing undesirable residual blocks can reduce the size of the model and its computational complexity without compromising its precision.
METHODS: Vector 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.
RESULTS: Based 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.
CONCLUSION: The 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.
METHODOLOGY/PRINCIPAL FINDINGS: We assessed oral susceptibility of Malaysian Ae. aegypti and Ae. albopictus by real-time PCR to an Australian RRV strain SW2089. Replication kinetics in midgut, head and saliva were determined at 3 and 10 days post-infection (dpi). With a 3 log10 PFU/ml blood meal, infection rate was higher in Ae. albopictus (60%) than Ae. aegypti (15%; p<0.05). Despite similar infection rates at 5 and 7 log10 PFU/ml blood meals, Ae. albopictus had significantly higher viral loads and required a significantly lower median oral infectious dose (2.7 log10 PFU/ml) than Ae. aegypti (4.2 log10 PFU/ml). Ae. albopictus showed higher vector competence, with higher viral loads in heads and saliva, and higher transmission rate (RRV present in saliva) of 100% at 10 dpi, than Ae. aegypti (41%). Ae. aegypti demonstrated greater barriers at either midgut escape or salivary gland infection, and salivary gland escape. We then assessed seropositivity against RRV among 240 Kuala Lumpur inpatients using plaque reduction neutralization, and found a low rate of 0.8%.
CONCLUSIONS/SIGNIFICANCE: Both Ae. aegypti and Ae. albopictus are susceptible to RRV, but Ae. albopictus displays greater vector competence. Extensive travel links with Australia, abundant Aedes vectors, and low population immunity places Kuala Lumpur, Malaysia at risk of an imported RRV outbreak. Surveillance and increased diagnostic awareness and capacity are imperative to prevent establishment of new arboviruses in Malaysia.
METHODOLOGY/PRINCIPAL FINDINGS: We conducted longitudinal studies to investigate the entomological parameters of the simian malaria vectors and to examine the genetic diversity and evolutionary pattern of their simian Plasmodium. All the captured Anopheles mosquitoes were dissected to examine for the presence of oocysts, sporozoites and to determine the parous rate. Our study revealed that the Anopheles Leucosphyrus Group mosquitoes are highly potential competent vectors, as evidenced by their high rate of parity, survival and sporozoite infections in these mosquitoes. Thus, these mosquitoes represent a risk of human infection with zoonotic simian malaria in this region. Haplotype analysis on P. cynomolgi and P. inui, found in high prevalence in the Anopheles mosquitoes from this study, had shown close relationship between simian Plasmodium from the Anopheles mosquitoes with its vertebrate hosts. This directly signifies the ongoing transmission between the vector, macaques, and humans. Furthermore, population genetic analysis showed significant negative values which suggest that both Plasmodium species are undergoing population expansion.
CONCLUSIONS/SIGNIFICANCE: With constant microevolutionary processes, there are potential for both P. inui and P. cynomolgi to emerge and spread as a major public health problem, following the similar trend of P. knowlesi. Therefore, concerted vector studies in other parts of Southeast Asia are warranted to better comprehend the transmission dynamics of this zoonotic simian malaria which eventually would aid in the implementation of effective control measures in a rapidly changing environment.
METHODS: Anopheles mosquitoes were collected from the location where P. knowlesi cases were reported. Cases of knowlesi malaria from 2011 to 2019 in Johor were analyzed. Internal transcribed spacers 2 (ITS2) and cytochrome c oxidase subunit I (COI) genes were used to identify the Leucosphyrus Group of Anopheles mosquitoes. In addition, spatial analysis was carried out on the knowlesi cases and vectors in Johor.
RESULTS: One hundred and eighty-nine cases of P. knowlesi were reported in Johor over 10 years. Young adults between the ages of 20-39 years comprised 65% of the cases. Most infected individuals were involved in agriculture and army-related occupations (22% and 32%, respectively). Four hundred and eighteen Leucosphyrus Group Anopheles mosquitoes were captured during the study. Anopheles introlatus was the predominant species, followed by Anopheles latens. Spatial analysis by Kriging interpolation found that hotspot regions of P. knowlesi overlapped or were close to the areas where An. introlatus and An. latens were found. A significantly high number of vectors and P. knowlesi cases were found near the road within 0-5 km.
CONCLUSIONS: This study describes the distribution of P. knowlesi cases and Anopheles species in malaria-endemic transmission areas in Johor. Geospatial analysis is a valuable tool for studying the relationship between vectors and P. knowlesi cases. This study further supports that the Leucosphyrus Group of mosquitoes might be involved in transmitting knowlesi malaria cases in Johor. These findings may provide initial evidence to prioritize diseases and vector surveillance.
METHODS: A randomized 4 × 4 Latin square designed experiment was conducted to compare the efficiency of the Mosquito Magnet against three other common trapping methods: human landing catch (HLC), CDC light trap and human baited trap (HBT). The experiment was conducted over six replicates where sampling within each replicate was carried out for 4 consecutive nights. An additional 4 nights of sampling was used to further evaluate the Mosquito Magnet against the "gold standard" HLC. The abundance of Anopheles sampled by different methods was compared and evaluated with focus on the Anopheles from the Leucosphyrus group, the vectors of knowlesi malaria.
RESULTS: The Latin square designed experiment showed HLC caught the greatest number of Anopheles mosquitoes (n = 321) compared to the HBT (n = 87), Mosquito Magnet (n = 58) and CDC light trap (n = 13). The GLMM analysis showed that the HLC method caught significantly more Anopheles mosquitoes compared to Mosquito Magnet (P = 0.049). However, there was no significant difference in mean nightly catch of Anopheles mosquitoes between Mosquito Magnet and the other two trapping methods, HBT (P = 0.646) and CDC light traps (P = 0.197). The mean nightly catch for both An. introlatus (9.33 ± 4.341) and An. cracens (4.00 ± 2.273) caught using HLC was higher than that of Mosquito Magnet, though the differences were not statistically significant (P > 0.05). This is in contrast to the mean nightly catch of An. sinensis (15.75 ± 5.640) and An. maculatus (15.78 ± 3.479) where HLC showed significantly more mosquito catches compared to Mosquito Magnet (P