Monitoring and analysis of endemic situation of schistosomiasis in Suzhou New District from 2004 to 2021
10.19428/j.cnki.sjpm.2023.22780
- VernacularTitle:2004—2021年苏州市高新区血吸虫病疫情监测分析
- Author:
Guoping GUI
1
;
Yuheng CHENG
2
;
Feng GUO
1
;
Yanhong HU
1
;
Dabing LYU
2
;
Wenhui SHI
3
Author Information
1. Suzhou New District (Huqiu District) Center for Disease Control and Prevention, Suzhou, Jiangsu 215011, China
2. Department of Epidemiology and Health Statistics, School of Public Health, Suzhou University, Suzhou, Jiangsu 215127, China
3. Adverse Reaction Monitoring Center for Family Planning Medicines and Utensils of National Health Commision/Jiangsu Health Development Research Center, Nanjing, Jiangsu 210036, China
- Publication Type:Journal Article
- Keywords:
schistosomiasis;
Oncomelania snail;
Mann-Kendall analysis;
Joinpoint regression model;
endemic prediction;
Suzhou New District
- From:
Shanghai Journal of Preventive Medicine
2023;35(9):857-862
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo analyze the monitoring data of schistosomiasis from 2004 to 2021 in Suzhou New District， Jiangsu Province， and to provide evidence for improving schistosomiasis elimination strategies. MethodsFollowing the Opinions on Prevention and Control of Schistosomiasis， Parasitic Diseases and Endemic Diseases in Suzhou and the Technical Plan for Prevention and Control of Schistosomiasis， Parasitic Diseases and Endemic Diseases in Suzhou， the monitoring of schistosomiasis in the population and snail habitats from 2004 to 2021 was conducted. The Mann-Kendall method and Joinpoint regression method were employed to analyze the trend of epidemic indicators （such as seropositive rate， prevalence of snail frames， etc.）. Time series analysis （exponential smoothing model） was conducted to predict snail occurrence. ResultsFrom 2004 to 2021， a total of 73 680 people were serologically tested for schistosomiasis， with a positive rate of 0.084%. The seropositivity rate showed statistically significant differences between different years （χ2=70.73， P<0.05）， but there was no significant trend over time. In addition， 3 053 fecal tests were conducted and no positive result was found. The snail habitats covered an area of 70.11 hm2 and showed a decreasing trend （Z=-1.97， P<0.05）. A total of 30 093 frames were surveyed， of which 19.038% contained snails. The difference in the prevalence of snail frames between different years was statistically significant （χ2=7 203.09， P<0.05）， with a decreasing trend in the prevalence of snail frames （Z=-2.05， P<0.05）. A total of 26 296 live snails were seized and density of live snails was 0.874 snails per frame， showing a decreasing trend in the density of live snails （Z=-2.35， P<0.05）. A total of 12 391 snails were dissected and no infected snail was found. The areas treated with molluscicides remained stable at 264.60 hm2. An area of 27.77 hm2 achieved the goal of snail eradication through environmental modification， with a decreasing trend （Z=-2.44， P<0.05）. It is estimated that the prevalence of snail frames and snail density will remain relatively stable from 2022 to 2026， but the snail habitat area will fluctuate significantly， showing an increasing trend. ConclusionNo indigenous cases of schistosomiasis and no infected snails are reported， indicating the successful consolidation of schistosomiasis prevention and control measures. However， the snail habitat area fluctuates greatly with an increasing trend， suggesting the need for long-term Oncomelania snail monitoring in local areas.
