Background: More than 1.2 million scorpion stings occur annually worldwide, particularly in tropical regions. In the absence of proper medical care, mortality due to venomous scorpion stings is an important public health issue. The aim of the present study is to explore the temporal trend of scorpionism with time series models and determine the effective factors on this event using regression models. Methods: A retrospective cross sectional study was conducted on 853 scorpion stung patients. They were referred to Haji-Abad Hospital of Hormozgan University of Medical Sciences (HUMS), south Iran, from May 2012 to July 2016. A linear model to describe and predict the monthly trend of scorpion sting cases is fit with autoregressive moving average (ARMA) model.

Background: Snakebite envenomation is a vital status necessitating immediate treatment following case detection. Many cases of snakebites are recorded every year due to the suitable climatic conditions for the existence and survival of snakes in south Iran. Methods: In the present retrospective cross-sectional study, 195 snake (Reptilia: Squamata: Viperidae; Echis carinatus sochureki) bite cases referred to 10 rural health centers, two health care stations and the Haji-Abad Central Hospital of Hormozgan University of Medical Sciences (HUMS) were surveyed during 2012-2016. Seasonal time series models were applied to fit a linear model to describe and predict the monthly trend of snakebite cases. Results: Among these patients, males (70%, 136) from rural areas (79.5%, 155) were mostly recorded. The mean (± SD) age of victims was 33 (± 17.0) years old and the most common age group was 20-29 years (32%). Most snakebites took place outdoors (80%), on hands and legs (97%), and among unemployed people and farmers (61.0%). Snakebites often happened between midnight and 6 am (32%); also 51% of them occurred during summer. Most (70%) patients had pain at the bite sites. The location of being bitten (indoors or outdoors) had a significant difference with patient's sex (χ 2 = 7.764, P = 0.021). Conclusions: Time series analysis proposed a mixed seasonal autoregressive moving average, ARMA × (1, 0) (1, 1) 12 as the best process for the monthly trend of snakebite and to predict the incidence of snakebites. Local residents should be more cautious on snakebites during warm seasons.

No abstract