Seasonality and geographical occurrence of West Nile fever and distribution of Asian tiger mosquito

The importance and risk of emerging mosquito borne diseases is going to increase in the European temperate areas due to climate change. The present and upcoming climates of Transdanubia seem to be suitable for the main vector of Chikungunya virus, the Asian tiger mosquito, Aedes albopictus Skuse (syn. Stegomyia albopicta). West Nile fever is recently endemic in Hungary. We used climate envelope modeling to predict the recent and future potential distribution/occurrence areas of the vector and the disease. We found that climate can be sufficient to explain the recently observed area of A. albopictus, while in the case of West Nile fever, the migration routes of reservoir birds, the run of the floodplains, and the position of lakes are also important determinants of the observed occurrence.

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).