Establishing and applying a schistosomiasis early warning index (SEWI) in the lower Yangtze River Region of Jiangsu Province, China.
BACKGROUND
China has made remarkable progress in schistosomiasis control over the past decades. Transmission control has replaced morbidity control as the country moves towards the goal of elimination and the current challenge is to find a sensitive measure capable of gauging transmission risk in low-prevalence areas. The study aims to develop a Schistosomiasis Early Warning Index (SEWI) and demonstrate its use in Jiangsu Province along the lower Yangtze River.


RESULTS
The Delphi approach, a structured communication technique, was used to develop the SEWI. Two rounds of interviews with 30 public health experts specialized in schistosomiasis control were conducted using 40 indicators that reflected different aspects of schistosomiasis transmission and control. The necessity, feasibility, and sensitivity of each indicator were assessed and the weight value of each indicator determined based on these experts' judgment. The system included 3 first-order indicators, 7 second-order indicators, and 30 third-order indicators. The 3 first-order indicators were endemic status, control measures, social and environmental factors, with the weight values 0.366, 0.343 and 0.291, respectively. For the 7 second-order indicators, the highest weight value was for control measures for snails (0.175) and the lowest for transmission route (0.110). We estimated and mapped the SEWI for endemic areas at the county scale in Jiangsu Province finding that the majority of the endemic areas were characterized as medium transmission risk (SEWI risk values between 0.3 and 0.6), while areas where transmission interruption had been officially declared showed SEWI values <0.30. A few isolated areas (e.g. endemic islands in the Yangtze River) produced SEWI values >0.60. These estimates are largely in agreement with the endemicity levels based on recent epidemiological surveys.


CONCLUSIONS
The SEWI should be useful for estimation of schistosomiasis transmission surveillance, particularly with reference to the elimination of the disease in China.
Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention (Ministry of Health), Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, Jiangsu Province, China.
Kun
K
Yang
Medicine school, Hubei University for Nationalities, Enshi, Hubei Province, China.
Jun-Fang
JF
Xu
Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention (Ministry of Health), Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, Jiangsu Province, China.
Jian-Feng
JF
Zhang
Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention (Ministry of Health), Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, Jiangsu Province, China.
Wei
W
Li
Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention (Ministry of Health), Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, Jiangsu Province, China.
Jian
J
He
Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America; Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.
Song
S
Liang
Ingerod 407, Brastad, Sweden.
Robert
R
Bergquist
D002681:China / Q000453:epidemiology; D005843:Geography; D006305:Health Status Indicators; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D062486:Public Health Surveillance; D015203:Reproducibility of Results; D045483:Rivers; D012552:Schistosomiasis / Q000453:epidemiology* / Q000517:prevention & control* / Q000635:transmission