Bayesian Spatial Modeling Of Echinococcosis Among Children In Guoluo Prefecture,Qinghai Province

Echinococcosis is a serious zoonotic parasitic disease caused by the metacestode Echinococcus. In western China, echinococcosis, both cystic and alveolar, has a great impact on the public health and social economy. Previous studies indicated that the degree of endemicity of echinococcosis is influenced by various factors including biological, environmental and social factors. In our study, RS and GIS methods, logistic regression analysis, Bayesian spatial model were complemented and analyzed based on the data collection of serological test on echinococcosis in Guoluo prefecture, in order to explore the risk factors and spatial pattern of echinococcosis. This study can be referenced for constituting the control strategies of echinococcosis.Firstly, a sampling survey were performed to understand the endemic situation of echinococcosis among children in Guoluo prefecture. A total of7445children aged from6to12were sampled from37towns through a stratified cluster sampling technique and all of them were examined by color ultrasound and serological test(ELISA). On town-level, the total prevalence is2.47%, the median of prevalence is2.11%, the highest and lowest prevalence were12.41%and0, respectively; the total seraprevalence is21.24%, the median of seraprevalence is21.21%, the highest and lowest seraprevalence were45.04%and4.82%, respectively.Secondly, raster map which collected from the study field was developed into digital map to extract environment variables (altitude, LST, NDVI) from remote sensing images. Meanwile, livestock variables related to echinococcosis were collected, including mean dog number per family, mean sheep number per dog and mean yak number per dog. The relation between children seraprevalence of echinococcosis on town-level and potential influencing factors including environment variables and livestock variables was analyzed with logistic regression analysis. It was shown that the seraprevalence of echinococcosis in children were positively correlated with altitude and the mean sheep number per dog (regression coefficient:0.485and0.062, respectively). While the seraprevalence of echinococcosis in children were negatively correlated with the mean of LST and the mean of NDVI(regression coefficient:-0.630and-0.607, respectively). We conclude that altitude, the mean sheep number per dog, the mean of LST and the mean of NDVI played important roles in the transmission of echinococcosis.Finally, Bayesian spatial models for area data were used to analyze the town-level data from serological tests, which was part of the field survey on echinococcosis in Guoluo prefecture, altitude, the mean sheep number per dog, the mean of LST and the mean of NDVI. It was shown that in the anlalysis of risk factors of echinococcus, we got the same conclusion as logistic regression analysis. The seraprevalence of echinococcosis in children were positively correlated with altitude and the mean sheep number per dog (regression coefficient:0.000159and0.043, respectively). While the seraprevalence of echinococcosis in children were negatively correlated with the mean of LST and the mean of NDVI(regression coefficient:-0.02214and-0.83935, respectively). The anlalysis of spatial pattern of echinococcosis showed that the spatial correlation coefficient is0.343, but the spatial correlation coefficients ranged from-0.047～0.640, that means there is no strong spatial correlation for the seraprevalence of echinococcosis in children on country-level.In conclusion, in this study, we used R.S and GIS methods, logistic regression analysis and Bayesian statistics to analyze the risk factors of echinococcosis and developed a spatial Bayesion model to analyze the spatial pattern of echinococcosis, which may help constituting and adjusting the control strategies of echinococcosis.