Bacterial community profiles within the water samples of leptospirosis outbreak areas

Background

Leptospirosis is a water-related zoonotic disease. The disease is primarily transmitted from animals to humans through pathogenic Leptospira bacteria in contaminated water and soil. Rivers have a critical role in Leptospira transmissions, while co-infection potentials with other waterborne bacteria might increase the severity and death risk of the disease.

Methods

The water samples evaluated in this study were collected from four recreational forest rivers, Sungai Congkak, Sungai Lopo, Hulu Perdik, and Gunung Nuang. The samples were subjected to next-generation sequencing (NGS) for the 16S rRNA and in-depth metagenomic analysis of the bacterial communities.

Results

The water samples recorded various bacterial diversity. The samples from the Hulu Perdik and Sungai Lopo downstream sampling sites had a more significant diversity, followed by Sungai Congkak. Conversely, the upstream samples from Gunung Nuang exhibited the lowest bacterial diversity. Proteobacteria, Firmicutes, and Acidobacteria were the dominant phyla detected in downstream areas. Potential pathogenic bacteria belonging to the genera Burkholderiales and Serratia were also identified, raising concerns about co-infection possibilities. Nevertheless, Leptospira pathogenic bacteria were absent from all sites, which is attributable to its limited persistence. The bacteria might also be washed to other locations, contributing to the reduced environmental bacterial load.

Conclusion

The present study established the presence of pathogenic bacteria in the river ecosystems assessed. The findings offer valuable insights for designing strategies for preventing pathogenic bacteria environmental contamination and managing leptospirosis co-infections with other human diseases. Furthermore, closely monitoring water sample compositions with diverse approaches, including sentinel programs, wastewater-based epidemiology, and clinical surveillance, enables disease transmission and outbreak early detections. The data also provides valuable information for suitable treatments and long-term strategies for combating infectious diseases.

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data

Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. In this study, we use vector indices and meteorological data as predictors to develop the ML models. We trained and validated seven ML algorithms, including an ensemble ML method, and compared their performance using the receiver operating characteristic (ROC) with the area under the curve (AUC), accuracy and F1 score. Our results show that an ensemble ML such as XG Boost, AdaBoost and Random Forest perform better than the logistics regression, Naïve Bayens, decision tree, and support vector machine (SVM), with XGBoost having the highest AUC, accuracy and F1 score. Analysis of the importance of the variables showed that the container index was the least important. By removing this variable, the ML models improved their performance by at least 6% in AUC and F1 score. Our result provides a framework for future studies on the use of predictive models in the development of an early warning system.

Evaluating the Potential of Pyriproxyfen Dissemination using Mosquito Home System against Aedes albopictus at a Dengue Hotspot Area

Aedes mosquitoes were found to lay their eggs in the cryptic breeding sites. Eliminating cryptic and open breeding sites is essential in reducing dengue virus transmission. However, it is often challenging for health officers to assess these breeding sites which are usually missed during larval surveillance. The autodissemination approach may produce a better outcome by manipulating female mosquitoes to disperse insecticide to other Aedes spp. mosquito habitats. Thus, the present study aims to evaluate the effectiveness of the pyriproxyfen autodissemination technique using Mosquito Home System against the population of mosquitoes. This study was conducted in Bandar Baru Bangi, Selangor, Malaysia. The Mosquito Home System was deployed to control Aedes spp. populations at treatment sites using before-after-control-impact (BACI) design. The presence of pyriproxyfen distribution was confirmed using the WHO larval bioassay which resulted in 10-35% larvae mortalities. Autodissemination of pyriproxyfen significantly reduced the population size of mosquito eggs (p<0.05), larvae (p<0.05), and ovitrap index (p<0.05) at the treatment areas compared to the control areas. Moreover, rainfall was correlated positively against ovitrap index (r = 0.247), larvae (r = 0.420), and eggs (r = 0.422). The study provides promising results for controlling Aedes spp. populations and also highlights the potentials of this technique as an alternative in vector control programmes. However, further studies on larger scale field trials are warranted.

Evaluation of a mosquito home system for controlling Aedes aegypti

BACKGROUND

Dengue is a significant public health issue that is caused by Aedes spp. mosquitoes. The current vector control methods are unable to effectively reduce Aedes populations and thus fail to decrease dengue transmission. Hence, there is an urgent need for new tools and strategies to reduce dengue transmission in a wide range of settings. In this study, the Mosquito Home System (MHS) and Mosquito Home Aqua (MHAQ) formulations were assessed as commercial autodissemination traps in laboratory and small-scale field trials.

METHOD

Multiple series of laboratory and small-scale field trials were performed to assess the efficacy of MHS and MHAQ exposed to Ae. aegypti. In the laboratory trials, various parameters such as fecundity, fertility, wing size, oviposition preferences, residual effects, and MHAQ transference to other containers through controlled experiments were tested. For small-scale field trials, the efficacy of the MHS and MHAQ approaches was determined to ascertain whether wild mosquitoes could transfer the MHAQ formulation from MHS stations to ovitraps.

RESULTS

The data revealed that Ae. aegypti was highly susceptible to low concentrations of MHAQ formulations and had a residual effect of up to 3 months, with MHAQ exposure affecting fecundity, fertility, and mosquito wing size. In the oviposition studies, gravid females strongly preferred the hay infusion compared to tap water and MHAQ during egg-laying in the laboratory. Nevertheless, the use of commercial MHAQ by MHS was highly attractive in field settings compared to conventional ovitraps among local Aedes spp. mosquitoes. In addition, MHAQ horizontal transfer activities in the laboratory and small-scale field trials were demonstrated through larval bioassays. These findings demonstrated the potential of MHAQ to be transferred to new containers in each study site.

CONCLUSION

This study provided proof of principle for the autodissemination of MHAQ. Through further refinement, this technique and device could become an effective oviposition trap and offer an alternative preventive tool for vector control management.

Implications of the COVID-19 Lockdown on Dengue Transmission in Malaysia

We aim to investigate the effect of large-scale human movement restrictions during the COVID-19 lockdown on both the dengue transmission and vector occurrences. This study compared the weekly dengue incidences during the period of lockdown to the previous years (2015 to 2019) and a Seasonal Autoregressive Integrated Moving Average (SARIMA) model that expected no movement restrictions. We found that the trend of dengue incidence during the first two weeks (stage 1) of lockdown decreased significantly with the incidences lower than the lower confidence level (LCL) of SARIMA. By comparing the magnitude of the gradient of decrease, the trend is 319% steeper than the trend observed in previous years and 650% steeper than the simulated model, indicating that the control of population movement did reduce dengue transmission. However, starting from stage 2 of lockdown, the dengue incidences demonstrated an elevation and earlier rebound by four weeks and grew with an exponential pattern. We revealed that Aedes albopictus is the predominant species and demonstrated a strong correlation with the locally reported dengue incidences, and therefore we proposed the possible diffusive effect of the vector that led to a higher acceleration of incidence rate.