Tiger prowling: Distribution modelling for northward-expanding Aedes albopictus (Diptera: Culicidae) in Japan.

The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae. albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae. albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae. albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae. albopictus with a focus on Japan.

Correlation between the proportion of stained eggs and the number of mites (Dermanyssus gallinae) monitored using a 'non-parallel board trap'.

The poultry red mite (Dermanyssus gallinae) is a serious problem for the poultry industry worldwide. However, the relationship between the mite population and the damage that they cause is still unclear. In this study, the mite population in poultry houses was examined using an established trap method, and the risk of blood-stained eggs caused by the mites was assessed. Traps were placed once a week outside the egg channels and/or on the floor in two poultry farms in Fukuoka Prefecture, Japan, from April 2012 to July 2014. The numbers of blood-stained eggs and total eggs were counted at weekly intervals. The results showed that the number of mites increased from April to May, and reached a peak around the beginning of June when the average temperature and humidity were >24°C and 70-90%, respectively. In the segmented model, the correlation between the proportion of blood-stained eggs and the number of mites or temperature was positive over a threshold. In conclusion, our established trap method is useful for monitoring mites and can be used to predict when poultry farms should be treated to prevent appearance of blood-stained eggs.