Abstract Background: Although scorpionism is recorded worldwide, some regions such as Iran present a higher incidence. Due to the great prevalence of scorpion stings in Khuzestan province, southwestern Iran, the present study examined the relationship between different climate parameters and the scorpion sting rate in this area from April 2010 to March 2015. Methods: In this cross-sectional descriptive-analytical study, we considered all scorpion sting cases recorded in the Department of Infectious Diseases, Ahvaz Jundishapur University of Medical Sciences. Data were analyzed using statistics, frequency distribution and Pearson’s correlation coefficient. Results: A total of 104,197 cases of scorpion stings was recorded from 2010 to 2015. The cumulative incidence of scorpion sting was 2.23%. The spatial distribution of scorpion stings showed that most cases occurred in the Dehdez district (4,504 scorpion stings/100,000 inhabitants) and the Masjed Soleyman county (4,069 scorpion stings/100,000 inhabitants). A significant association was found between climate factors (temperature, evaporation rate, sunshine duration, humidity, and precipitation) and the scorpion sting rate. An increase in rainfall and humidity coincided with a reduction in scorpion stings whereas an increase in temperature, evaporation, and sunshine duration was accompanied by a growth of scorpion stings. No significant correlation was found between wind velocity/direction and the incidence rate of stings. Moreover, the seasonal peak incidence of scorpion stings was recorded in summer (an average of 8,838 cases) and the lowest incidence was recorded during winter (an average of 1,286 cases). The annual trend of scorpion sting cases decreased during the period from 2010 to 2015. Conclusion: Climate variables can be a good index for predicting the incidence of scorpion stings in endemic regions. Since they occur mostly in the hot season, designing preventive measures in the counties and districts with a high incidence of scorpion stings such as Dehdez and Masjed Soleyman can minimize mortality and other burdens.

Este artículo se refiere al problema de discriminación entre dos clases de series de tiempo estacionarias locales basadas en información de discriminación mínima. Se consideran las señales observadas como realizaciones de procesos wavelet estacionarios locales (LSW, por sus siglas en inglés) gausianos. La información de discriminación Kullback - Leibler asintótica y la información de discriminación de Chernoff se desarrollan como criterios discriminantes para procesos LSW. El estudio de simulación mostró que el procedimiento propuesto se desempeña tan bien como otros procedimientos y en algunos casos mejor que otros métodos de clasificación. Aplicaciones a la clasificación de datos sísmicos muestran la utilidad de los criterios discriminantes propuestos.

This article is concerned with the problem of discrimination between two classes of locally stationary time series based on minimum discrimination information. We view the observed signals as realizations of Gaussian locally stationary wavelet (LSW) processes. The asymptotic Kullback - Leibler discrimination information and Chernoff discrimination information are developed as discriminant criteria for LSW processes. The simulation study showed that our procedure performs as well as other procedures and in some cases better than some other classification methods. Applications to classifying real data show the usefulness of our discriminant criteria.