Animal model
Kunming strain mice weighing 25g±3g were purchased from the Hubei Provincial Centre for Disease Control and Prevention. (Wuhan, China). All procedures were designed by National Institute of parasitic diseases, Chinese Center for Disease Control and Prevention, and approved by the Committee on the Ethics of Chinese Center for Disease Control and Prevention.
Method and Procedures
Following the springtime O.hupensis snail survey, we implemented a schistosomiasis transmission surveillance method based on the use of sentinel mice in suspected high-risk water regions. Our main aim was to identify surveillance sites (i.e., areas used by both humans and livestock) that were positive for infected sentinel mice as quickly as possible while simultaneously recording data on local residents, livestock, snails, and wild animal fecal samples. Through this approach, we aimed to prevent both humans and livestock from becoming infected with schistosomiasis and supplement the routine schistosomiasis surveillance system.
Prior to initiating field work, on-site local staff at both the county and township levels participated in unified training courses conducted by the Hubei Institute of Schistosomiasis Prevention and Control (HISPC). This training aimed to ensure that the adopted plan, timing, approach, and norms were uniformly devised and implemented to ensure the accuracy and reliability of the experiment results. The trained field staff supervised the process of on-site surveillance to guarantee that as few sentinel mice as possible were unexpectedly lost. Mice were housed in a specific pathogen-free (SPF) laboratory and dissected in a medical morphological laboratory by a specialized team from the HISPC. Sentinel mouse monitoring was conducted as follows:
A). We selected the sentinel surveillance sites according to the following standards:
(1) an identification of O. hupensis within the last 5 years;
(2) frequent activity involving bovines or local residents in areas known to support O. hupensis;
(3) environments near neighborhoods or distribution centers used by boat fishermen (including the rivers connected to the Yangtze River that are areas known to support O. hupensis);
(4) large agricultural operation areas irrigated with reservoirs carrying O. hupensis;
(5) waters adjacent to national or provincial surveillance points.
B). Sentinel mice comprised males with body weights of 25g ± 3 g. Cylindroid wire-mesh cages were purchased from the HISPC. Each cage measured 51.3 cm in length, with a diameter of 11.1 cm, and was fitted with six spherical plastic foam balls tied to each side to float the cage on a water surface. Each cage was divided into five cells of equal size. Two cages were set at each site at a spacing interval of 10–20 m. Each cage contained two mice per cell (10 mice in total), and the cage position was adjusted to ensure that the tail and abdomen of each mouse would be exposed to the water. Sentinel surveillance was conducted from May to July and from September to October. The sentinel mice in the cages were exposed to the water surface from 10:00 a.m. to 14:00 p.m. on two consecutive days. The activities of the local residents and livestock, air and water temperatures, and flow velocity were recorded simultaneously.
C). The surviving mice were collected after exposure, marked, and returned to the animal facility, which was maintained at an appropriate ambient temperature (23–26ºC) and humidity (40–70%) for 35–40 days to allow the infective schistosomes to mature sufficiently. Subsequently, the mice were sacrificed and dissected, and the livers and portal/mesenteric veins were screened for S. japonicum eggs and adult worms, respectively. Mice that harbored eggs in the liver and/or adult worms in the portal and mesenteric veins were considered positive for schistosomiasis infection.
D). Data management, presentation, and electronic distribution were supported using Google Earth software (version 7.0), and photos of the sentinel surveillance field environments were recorded using Picasa (version 3.1). For each site, a database was established to include information about the location (latitude and longitude) and surveillance results. The field photographical images and sentinel mouse data from all sites were compiled via Google Earth Pro v7.1.8.3036 software and ArcGIS 10.5 software. The interval between dissection and data import was no longer than 7 days.
E). When positive results were found, a detailed plan for schistosomiasis control was established and set in motion as soon as possible. This implementation required the dispatch of professional teams to the positive sites within 24 hours to conduct a field survey and implement specific control measures. Required protection measures (e.g., extended chemotherapy) were applied in a timely manner to high-risk populations (e.g., humans and cattle). Finally, the efficacies of the response measures were evaluated.
Multi-distance spatial clustering analysis (Ripley’s K function)
Ripley’s K function is used to analyze whether spatial point data show statistically significant aggregation or dispersion within a certain scale. This analysis considers each case in the study area as a point on a plane, draws an epidemiological punctuation map based on its coordinates, and analyzes the spatial distribution pattern of cases in the study area based on the punctuation map. L(d) values are clustered outside the confidence interval and randomly distributed within the confidence interval. When the distribution is clustered, the deviation confidence interval value is used as the index of clustering intensity, where the maximum is the maximum clustering intensity and the clustering range is the circle whose distance is the radius. In this study, the Monte Carlo method was used to simulate 999 random simulations with a confidence interval of 95%. Ripley’s L(d) index analysis was performed using ArcGIS software.
Kernel density estimation
Kernel density estimation is a non-parametric method used to estimate the probability density function. This method assumes that the disease can occur at any point in space, but the probability differs at different locations. The probability of disease occurrence is high in densely populated areas, and low in sparsely populated areas. Kernel density analysis and visualization was implemented using AcrGIS software.
Statistical analysis
The changes over time at the positive sites, rates and worm burdens were first explored through visual inspection including calculation of the mean values and dispersions, then compared using a χ2 test. The analyses were performed using SPSS 22.0 (SPSS Inc. Chicago, USA). All spatially analyses were carried out using the spatial analyst module of ArcGIS 10.5 (ESRI; Redlands, USA), which has been widely applied in many fields of research.