Predictive determinants of scorpion stings in a tropical zone of south Iran: use of mixed seasonal autoregressive moving average model

Abstract

BackgroundMore 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.MethodsA 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.ResultsOf 853 victims, 384 (45%) patients were female and 30.2% of them lived in urban areas. The mean (± SD) age of patients was 30.1 (± 19.6) years and the most affected age group was 20-29 years (21.8%). Most victims were unemployed people and farmers (54.7%) followed by housewives (30.2%). The majority of the stings occurred indoors (53.7%), between midnight and 6 a.m. (29.2%), in the summer (44.2%), and the most affected limbs were hands and legs (81.2%). Patient genders and occasions of being stung by scorpions were significantly different between outdoors and indoors (p < 0.001). Scorpion stings due to Odontobuthus doriae were significantly higher than due to other species in urban and rural patients (p = 0.04). Mixed seasonal ARMA at lag 12, ARMA (1, 1) × (0, 1), was selected as the best process for monthly trend of data. Regression results indicated that significant climate factors associated with scorpion stings are temperature (p < 0.001) and relative humidity (p = 0.002).ConclusionsScorpion stings have a noticeable effect on tropical rural populations, mainly farmers. Two effective climate factors associated positively and negatively with scorpion sting cases are temperature and relative humidity, respectively. The results of time series and regression models to predict the trends and determinants of scorpion stings are almost the same.