Prevalence and spatial distribution characteristics of human echinococcosis in China

• Published in: PLoS neglected tropical diseases 2021-12, Vol.15 (12), p.e0009996-e0009996
• Main Authors: Wang, Li-Ying, Qin, Min, Liu, Ze-Hang, Wu, Wei-Ping, Xiao, Ning, Zhou, Xiao-Nong, Manguin, Sylvie, Gavotte, Laurent, Frutos, Roger
• Format: Article
• Language: English
• Subjects: Agglomeration; Aggregation; Animals; Autocorrelation; Biology and Life Sciences; Chi-square test; China - epidemiology; Clustering; Computer and Information Sciences; Data collection; Demographic aspects; Disease control; Disease hot spots; Disease prevention; Distribution; Earth Sciences; Echinococcosis; Echinococcosis - epidemiology; Echinococcosis - parasitology; Echinococcus - physiology; Humans; Infections; Larvae; Life Sciences; Medicine and Health Sciences; Parasitic diseases; Parasitoses; People and Places; Prevalence; Prevention; Probability theory; Provinces; Public Health; Risk factors; Safety; Spatial Analysis; Spatial distribution; Statistical analysis; Statistical methods; Statistical tests; Tibet - epidemiology; Tropical diseases; Zoonoses
• ISSN: 1935-2735; 1935-2727; 1935-2735
• DOI: 10.1371/journal.pntd.0009996

Echinococcosis is a zoonotic parasitic disease caused by larval stages of cestodes belonging to the genus Echinococcus. The infection affects people's health and safety as well as agropastoral sector. In China, human echinococcosis is a major public health burden, especially in western China. Echinococcosis affects people health as well as agricultural and pastoral economy. Therefore, it is important to understand the prevalence status and spatial distribution of human echinococcosis in order to advance our knowledge of basic information for prevention and control measures reinforcement. Report data on echinococcosis were collected in 370 counties in China in 2018 and were used to assess prevalence and spatial distribution. SPSS 21.0 was used to obtain the prevalence rate for CE and AE. For statistical analyses and mapping, all data were processed using SPSS 21.0 and ArcGIS 10.4, respectively. Chi-square test and Exact probability method were used to assess spatial autocorrelation and spatial clustering. A total of 47,278 cases of echinococcosis were recorded in 2018 in 370 endemic counties in China. The prevalence rate of human echinococcosis was 10.57 per 10,000. Analysis of the disease prevalence showed obvious spatial positive autocorrelation in globle spatial autocorrelation with two aggregation modes in local spatial autocorrelation, namely high-high and low-high aggregation areas. The high-high gathering areas were mainly concentrated in northern Tibet, western Qinghai, and Ganzi in the Tibetan Autonomous Region and in Sichuan. The low-high clusters were concentrated in Gamba, Kangma and Yadong counties of Tibet. In addition, spatial scanning analysis revealed two spatial clusters. One type of spatial clusters included 71 counties in Tibet Autonomous Region, 22 counties in Qinghai, 11 counties in Sichuan, three counties in Xinjiang Uygur Autonomous Region, two counties in Yunnan, and one county in Gansu. In the second category, six types of spatial clusters were observed in the counties of Xinjiang Uygur Autonomous Region, and the Qinghai, Gansu, and Sichuan Provinces. This study showed a serious prevalence of human echinococcosis with obvious spatial aggregation of the disease prevalence in China. The Qinghai-Tibet Plateau is the "hot spot" area of human echinococcosis in China. Findings from this study indicate that there is an urgent need of joint strategies to strengthen efforts for the prevention and control of echinococcosis in China, especial