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.

BackgroundThe trend in chemical insecticide development has focused on improving the efficacy against mosquitoes while reducing the environmental impact. Lethal lures apply an “attract-and-kill” strategy that draws the insect to the killing agent rather than bringing the killing agent to the insect.MethodsIn this study, the mosquito oviposition pheromone was extracted from the eggs of Aedes aegypti (L.) and further investigated with a combination of pheromone and granular temephos as a lethal lure.ResultsThe compound caproic acid attracted significantly more egg-laying mosquitos at 1 ppm (660.83 ± 91.61) than the control (343.83 ± 56.24), which consisted of solvent only (Oviposition Activity Index: 0.316). Further investigation of the combination of caproic acid with granular temephos as a lethal lure attracted significantly more gravid female Ae. aegypti to oviposit their eggs than the temephos treated water and control.ConclusionsThis indicated the ability of caproic acid in acting as an attractant and counters the repellency effect of temephos. Additionally, the presence of temephos in the lethal lure also restricted the hatching of the eggs and killed any larvae that hatched.

Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.