Time Series Model for Forecasting the Prevalence of Some Important Parasitic Infections in Slaughtered Sheep in North-Central Iran - Azizian, Mahdieh; Tavakoli Oliaee, Razieh; Karimazar, Mohammd Reza; Ebrahimipour, Mohammad; Afgar, Ali (Archives of Veterinary Science, 2023)
Uncontrolled parasitic infections in livestock can increase the potential risk of transmission between human societies. Owing to the socioeconomic challenges of these diseases in slaughtered sheep, the current study aimed to forecast the prevalence of these infections in a central slaughterhouse in Alborz Province, north-central Iran. Data from 2009 to 2018 on parasitic infections in slaughtered sheep presented at a slaughterhouse were compiled and the prevalence of these diseases was computed. The prevalence has been considered as a time series and afterward, RStudio software using the best-fitted ARIMA model was applied to forecast the monthly variation in prevalence rates. From 2009 to 2018, a total of 1,339,196 sheep were slaughtered in the studied slaughterhouse. The Iranian Afshari breed was the most slaughtered sheep and, a total of 77.6% of these animals were raised under traditional farming system. In addition to the Alborz province, slaughtered sheep were brought from five other provinces, including Zanjan, Qazvin, Qom, Kurdistan, and East Azerbaijan. The highest and lowest total prevalence of studied parasitic zoonoses in slaughtered livestock were cystic echinococcosis (12.76%) and Taenia ovis infection (0.01%), respectively. An approximate stationary trend for fascioliasis and CE and a mild decreasing trend for dicrocoeliasis and sarcocystosis has been forecasted for the next 10 years. Forecasting the prevalence of T. ovis infection showed that without implementing control strategies, this infection would be increased in the years ahead. The current study has demonstrated for the first time the predicting of some important parasitic infections in sheep in Iran. The results provide helpful data for authorities for controlling these diseases in the frontline of meat production. Vast and in-depth forecasting investigations is required to find evidence-based data about these infections for entire the country of Iran.