Time series analysis of cutaneous leishmaniasis incidence in Shahroud based on ARIMA model

BackgroundLeishmaniasis is a zoonotic disease and Iran is one of the ten countries with has the highest estimated cases of leishmaniasis. This study aimed to determine the time trend of cutaneous leishmaniasis (CL) incidence using the ARIMA model in Shahroud County, Semnan, Iran.MethodsIn this study, 725 patients with leishmaniasis were selected in the Health Centers of Shahroud during 2009-2020. Demographic characteristics including; history of traveling, history of leishmaniasis, co-morbidity of other family members, history of treatment, underlying disease, and diagnostic measures were collected using the patients' information listed in the Health Ministry portal. The Box-Jenkins approach was applied to fit the SARIMA model for CL incidence from 2009 to 2020. All statistical analyses were done by using Minitab software version 14.ResultsThe mean age of patients was 28.2 & PLUSMN; 21.3 years. The highest and lowest annual incidence of leishmaniasis were in 2018 and 2017, respectively. The average ten-year incidence was 132 per 100,000 population. The highest and lowest incidence of the disease were 592 and 195 for 100,000 population in the years 2011 and 2017, respectively. The best model was SARIMA (3,1,1) (0,1,2)(4) (AIC: 324.3, BIC: 317.7 and RMSE: 0.167).ConclusionsThis study suggested that time series models would be useful tools for predicting cutaneous leishmaniasis incidence trends; therefore, the SARIMA model could be used in planning public health programs. It will predict the course of the disease in the coming years and run the solutions to reduce the cases of the disease.

Automated summary

This study aimed to determine the time trend of cutaneous leishmaniasis (CL) incidence in Shahroud County, Iran using the ARIMA model. The findings suggest that time series models, particularly the SARIMA model, can be useful in predicting the incidence trends of CL and planning public health programs to reduce the cases of the disease in the coming years.