[Spatial and temporal characteristics of reported schistosomiasis cases in China based on a Bayesian interrupted time-series model].

OBJECTIVE

To investigate the spatial-temporal characteristics of reported schistosomiasis cases in China from 2004 to 2017, so as to provide insights into the development of different schistosomiasis control strategies at various stages.

METHODS

The monthly data of reported schistosomiasis cases at a provincial level of China from 2004 to 2017 were collected from the Public Health Science Data Center, and the spatial-temporal distribution of reported schistosomiasis cases was preliminarily identified using a descriptive statistical method. According to the goals at different stages proposed by , a Bayesian interrupted time-series model was established to analyze the provincial reported incidence, time trend and seasonal variations of schistosomiasis in China at different stages.

RESULTS

The reported schistosomiasis cases were mainly concentrated in 5 provinces of Anhui, Jiangsu, Jiangxi, Hubei and Hunan and 2 provinces of Sichuan and Yunnan in China from 2004 to 2017, and the number of reported cases in endemic areas decreased gradually. The incidence of reported schistosomiasis cases predominantly peaked during the period from May to September in the marshland and lake regions, while no regular seasonality was seen in hilly regions. Bayesian interrupted time-series analysis showed the peak incidence of reported schistosomiasis cases in 4 provinces of Anhui, Hubei, Hunan and Jiangxi between May and September and in Jiangsu Province from July to November; however, no regular seasonal cycle was identified in hilly regions. The number of reported schistosomiasis cases showed a tendency towards an increase in 2 provinces of Hubei and Hunan from 2008 to 2014, with a minor peak during the period between March and April, and since 2015, the seasonality was not remarkable any longer in 3 provinces of Anhui, Jiangsu and Jiangxi with a decline in the incidence of reported schistosomiasis cases, while the seasonality remained in Hubei Province.

CONCLUSIONS

The spatial-temporal characteristics of schistosomiasis in China, notably seasonality, vary at different control stages. Bayesian interrupted time-series model is effective to identify the spatial-temporal changes of schistosomiasis, and the schistosomiasis control strategy may be adjusted according to the spatial-temporal changes to improve the schistosomiasis control efficiency.