Hepatitis C virus (HCV) infection is an important public health problem that attracts worldwide attention. HCV infection can lead to liver cell damage and further development will lead to cirrhosis and liver cancer, a serious threat to people's health(Thrift et al., 2017; Zhu, and L, F., Z, A, 2018). In addition, infection with HCV not only has an impact on the liver but also has some extrahepatic manifestations such as insulin resistance and glomerulonephritis(Zignego et al., 2007). In early 2020, an estimated 56.8 million people worldwide were infected with the hepatitis C virus(Blach et al., 2022). As the global burden of disease has increased(L., M.C.J., Y., A.A, et al., 2020), the World Health Organization (WHO) advocated eliminating the threat of hepatitis C by 2030(Sun et al., 2021). China has the largest number of HCV infected patients in the world. It is estimated that at least 25 million people in China are infected with HCV(Bian et al., 2017). In addition, almost one-fifth of HCV related cirrhosis and chronic hepatitis C deaths occur in China(Li et al., 2019). Therefore, the high prevalence of hepatitis C in China is becoming increasingly serious, and China is bearing a huge burden of disease caused by hepatitis C.

Shandong Province, located on the east coast of China, is the second most populous province(Xu et al., 2020). Its large population and strong mobility are easy to cause the spread of the HCV virus. The wide distribution of HCV susceptible populations such as unsafe injections or blood transfusion and HIV-infected undoubtedly increases the difficulty of prevention and control of hepatitis C(Wang et al., 2020). A study showed that the incidence rate of hepatitis C in Shandong Province is on the rise, which seriously threatens the health of the provincial people(Gu et al., 2018). Since there is no vaccine against HCV, we mainly rely on screening and drug treatment to control the spread of hepatitis C(Gomaa et al., 2017). Multiple factors in the economic and social environment influence the spread of infectious diseases (Angulo et al., 2013; Piao et al., 2014). The trend analysis of hepatitis C in Shandong Province can provide a reference for the prevention and control of hepatitis C in populations that share similar characteristics as that in Shandong Province.

In recent years, many models have been used to predict the incidence rate(Ando et al., 2011; Zhang et al., 2013). A few studies use the Autoregressive Integrated Moving Average (ARIMA) model and the Long Short-Term Memory (LSTM) model to predict hepatitis C (Akhtar and Rozi, 2009; Zhang et al., 2023). ARIMA model is a commonly used time-series model for predicting the onset of infectious diseases. It is suitable for predicting infectious diseases with complex long-term trends and seasonality(Li et al., 2012). LSTM models can predict future trends in diseases by identifying and learning from existing data on the disease(Thakur et al., 2020). Combining the two models has higher prediction accuracy(Xu et al., 2021). Some previous studies have analyzed the epidemic trend and genotyping of hepatitis C in Shandong Province(Jin-hong, 2011; WanSu et al., 2010), but there are few studies on the spatial distribution and incidence rate prediction of hepatitis C in Shandong Province(Zhao et al., 2012). Our study aims to understand the overall epidemic trend of hepatitis C and the differences between regional incidence rates in Shandong Province, and use the ARIMA model and combined ARIMA-LSTM model to predict hepatitis C incidence rate from 2022 to 2030. It is beneficial to increase attention to less economically developed regions and promote rational allocation of healthcare resources. At the same time, it can strengthen the screening of hepatitis C in less economically developed areas, detect and treat it early, and reduce the regional incidence rate.