Identifying determinants for the seropositive rate of schistosomiasis in Hunan province, China: A multi-scale geographically weighted regression model.

BACKGROUND: Schistosomiasis is of great public health concern with a wide distribution and multiple determinants. Due to the advances in schistosomiasis elimination and the need for precision prevention and control, identifying determinants at a fine scale is urgent and necessary, especially for resource deployment in practice. Our study aimed to identify the determinants for the seropositive rate of schistosomiasis at the village level and to explore their spatial variations in local space. METHODOLOGY: The seropositive rates of schistosomiasis were collected from 1714 villages or communities in Human Province, and six spatial regression models including ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), robust GWR (RGWR) and multiscale GWR (MGWR) were used to fit the data. PRINCIPAL/FINDINGS: MGWR was the best-fitting model (R2: 0.821, AICc:2727.092). Overall, the nearest distance from the river had the highest mean negative correlation, followed by proportion of households using well water and the annual average daytime surface temperature. The proportions of unmodified toilets showed the highest mean positive correlation, followed by the snail infested area, and the number of cattle. In spatial variability, the regression coefficients for the nearest distance from the river, annual average daytime surface temperature and the proportion of unmodified toilets were significant in all villages or communities and varied little in local space. The other significant determinants differed substantially in local space and had significance ratios ranging from 41% to 70%, including the number of cattle, the snail infested area and the proportion of households using well water. CONCLUSIONS/SIGNIFICANCE: Our study shows that MGWR was well performed for the spatial variability of schistosomiasis in Hunan province. The spatial variability was different for different determinants. The findings for the determinants for the seropositive rate and mapped variability for some key determinants at the village level can be used for developing precision intervention measure for schistosomiasis control.

Environmental Determinants for Snail Density in Dongting Lake Region: An Ecological Study Incorporating Spatial Regression.

This study explored the environmental determinants of different months on snail density measured in April at different types of snail habitats (marshlands, inner embankments, and hills) by considering spatial effects. Data were gathered from surveys on snails that were conducted in Hunan Province in April 2016, and information was collected on environmental variables. To investigate the environmental factors influencing snail density in various types of snail habitats, the ordinary least square model, spatial lag model, and spatial error model were all used. The environmental determinants for snail density showed different effects in the three types of snail habitats. In marshlands, snail density measured in April was associated positively with the normalized difference vegetation index (NDVI) and was associated negatively with flooding duration and annual hours of sunshine. Extreme temperatures correlated strongly to snail density measured in April (P < 0.05). In areas inside embankments, snail density measured in April increased with a decreased distance between snail habitat and the nearest river (P < 0.05). In hills, extreme heat, annual hours of sunshine, NDVI in September, and annual average land surface temperature (LST) were associated negatively with snail density measured in April, whereas index of moisture (IM) was associated positively with snail density measured in April (P < 0.05). The effects of LST and hours of sunshine on snail density measured in April varied with months of the year in the three different types of snail habitats (P < 0.05). Our study might provide a theoretical foundation for preventing snail transmission and subsequent spread of schistosomiasis.

Machine learning algorithms to predict the 1 year unfavourable prognosis for advanced schistosomiasis.

Short-term prognosis of advanced schistosomiasis has not been well studied. We aimed to construct prognostic models using machine learning algorithms and to identify the most important predictors by utilising routinely available data under the government medical assistance programme. An established database of advanced schistosomiasis in Hunan, China was utilised for analysis. A total of 9541 patients for the period from January 2008 to December 2018 were enrolled in this study. Candidate predictors were selected from demographics, clinical features, medical examinations and test results. We applied five machine learning algorithms to construct 1 year prognostic models: logistic regression (LR), decision tree (DT), random forest (RF), artificial neural network (ANN) and extreme gradient boosting (XGBoost). An area under the receiver operating characteristic curve (AUC) was used to evaluate the model performance. The important predictors of the optimal model for unfavourable prognosis within 1 year were identified and ranked. There were 1249 (13.1%) cases having unfavourable prognoses within 1 year of discharge. The mean age of all participants was 61.94 years, of whom 70.9% were male. In general, XGBoost showed the best predictive performance with the highest AUC (0.846; 95% confidence interval (CI): 0.821, 0.871), compared with LR (0.798; 95% CI: 0.770, 0.827), DT (0.766; 95% CI: 0.733, 0.800), RF (0.823; 95% CI: 0.796, 0.851), and ANN (0.806; 95% CI: 0.778, 0.835). Five most important predictors identified by XGBoost were ascitic fluid volume, haemoglobin (HB), total bilirubin (TB), albumin (ALB), and platelets (PT). We proposed XGBoost as the best algorithm for the evaluation of a 1 year prognosis of advanced schistosomiasis. It is considered to be a simple and useful tool for the short-term prediction of an unfavourable prognosis for advanced schistosomiasis in clinical settings.

Prevalence and incidence of advanced schistosomiasis and risk factors for case fatality in Hunan Province, China.

Advanced schistosomiasis has become a major public health problem in areas with a heavy burden of schistosomiasis infection. Our objective was to determine the incidence and prevalence of advanced schistosomiasis and risk factors associated with case fatality of advanced schistosomiasis. Data were abstracted from hospitalization records of patients with advanced schistosomiasis from Hunan Province, China. The incidence and prevalence of advanced schistosomiasis were determined and the risk factors for death in advanced patients were assessed using logistic regression analysis. A total of 10,362 patients with advanced schistosomiasis were recruited into our study and 65% of them were categorized as the ascites type. There were 1249 deaths between 2005 and 2018 and the case fatality was 12.05%. The incidence of advanced schistosomiasis increased from 2002 to 2010, peaked in 2010 and then leveled off. The prevalence of advanced schistosomiasis increased from 2005 to 2014, and was stable afterwards. HBV was a risk factor for death in advanced patients (adjusted odds ratio (aOR=1.93, 95% confidence interval (CI: 1.55 to 2.41). Patients without splenectomy had a higher risk of death (aOR=1.29, 95%CI: 1.08 to 1.56). Upper gastrointestinal bleeding was positively associated with the risk of death (aOR=1.42, 95% CI: 1.15 to 1.76). Besides, abnormal ALT, ascites and anemia were also significantly associated with the risk of death in advanced patients. Advanced schistosomiasis was effectively controlled in recent years. Splenectomy could reduce the case fatality of advanced patients. HBV infection, abnormal ALT, upper gastrointestinal bleeding and anemia also predicted the risk of death for advanced patients.

Spatio-temporal variations of emerging sites infested with schistosome-transmitting Oncomelania hupensis in Hunan Province, China, 1949-2016.

BACKGROUND: Constant emerging sites infested with Oncomelania hupensis (O. hupensis) impede the goal realization of eliminating schistosomiasis. The study assessed the spatial and temporal distributions of new Oncomelania snail habitats in Hunan Province from 1949 to 2016. METHODS: We used the data from annual snail surveys throughout Hunan Province for the period from 1949 to 2016. Global Moran's I, Anselin local Moran's I statistics (LISA) and a retrospective space-time permutation model were applied to determine the spatial and temporal distributions of emerging snail-infested sites. RESULTS: There were newly discovered snail-infested sites almost every year in 1949-2016, except for the years of 1993, 2009 and 2012. The number of emerging sites varied significantly in the five time periods (1949-1954, 1955-1976, 1977-1986, 1986-2003 and 2004-2016) (H = 25.35, p < 0.05). The emerging sites lasted 37.52 years in marshlands, 30.04 years in hills and 24.63 at inner embankments on average, with the values of Global Moran's I being 0.52, 0.49 and 0.44, respectively. High-value spatial clusters (HH) were mainly concentrated along the Lishui River and in Xiangyin County. There were four marshland clusters, two hill clusters and three inner embankment clusters after 1976. CONCLUSIONS: Lower reaches of the Lishui River and the Dongting Lake estuary were the high-risk regions for new Oncomelania snail habitats with long durations. Snail surveillance should be strengthened at stubborn snail-infested sites at the inner embankments. Grazing prohibition in snail-infested grasslands should be a focus in marshlands. The management of bovines in Xiangyin County is of great importance.

[Analysis of epidemiological characteristics of advanced schistosomiasis in Hu-nan province, 2012].

OBJECTIVE: To understand the epidemiological characteristics of patients with advanced schistosomiasis in Hunan Province, so as to provide the evidence for formulating the advanced schistosomiasis prevention strategies and measures. METHODS: The data of advanced schistosomiasis patients were collected and analyzed retrospectively with the cross section research method and description method in Hunan Province, 2012. RESULTS: There were 5 722 advanced schistosomiasis patients in Hunan Province, and among them, 4 112 patients were male (71.86%), and 1610 were female (28.14%). Totally 5311 patients came from the schistosomiasis endemic areas (92.82%) and 411 patients from non-schistosomiasis endemic areas (7.18%). The prevalence rate of advanced schistosomiasis was 8.46/10,000. The mean age of advanced schistosomiasis patients was 60.30 +/- 11.63 years, and the youngest was 17 years old and the oldest 92 years old. In the age composition of advanced schistosomiasis patients, the greatest number of cases was in the 60-70 years age group (32.72%). There were 3 595 cases of ascites type (62.83%), 2107 cases of splenomegaly type (36.82%), 11 cases of dwarf type (0.16%), and 11 cases of colon proliferation type (0.35%). CONCLUSION: The prevalence rate of advanced schistosomiasis is relatively stable in Hunan Province, and the age of the patients showed an old aging trend. The salvation of advanced schistosomiasis patients in non-endemic areas should be strengthened.

[Retrospective investigation of schistosomiasis endemic situation in Hunan Province].

OBJECTIVE: To understand the dynamic rules of schistosomiasis endemic situation before and after reaching the criteria of schistosomiasis transmission controlled or transmission interrupted, so as to provide the evidence for improving schistosomiasis control. METHODS: Wuling District, Xihu District and Linli County were selected and investigated retrospectively to collect the schistosomiasis epidemiological information 10 years before they reached the criteria of transmission controlled and the subsequent years until 2008. A database of retrospective investigation was established for analyzing the trends and rules of changes of the Oncomelania hupensis snail status and infection status of cattle and human. RESULTS: In Wuling District, the endemic situation was declining, and no schistosome infection persons, animals and snails were found after 1974. There was no rebound until 2008. In Xihu District, the endemic situation reached the criteria of transmission controlled in 1997, and the endemic situation was stable. The human infection rate was positively correlated with the area of infection snails (r = 0.584, P < 0.05). In Linli County, there were no snails, no infected persons and cattle twice, but 2 endemic rebounds, and there were positive correlations between the densities of living snails and the infection rates of human and animal during the endemic rebound period. CONCLUSION: The snail status is an important indicator of schistosomiasis endemic rebound. Therefore, the snail control is one of the most important schistosomiasis control measures.

[Short-term effect of black film covering on Oncomelania hupensis snail control in marshland and lake regions].

OBJECTIVE: To evaluate the short-term effect of the black film covering combined with niclosamide on Oncomelania hupensis snail control in marshland and lake regions. METHODS: A ditch with snails in Anxiang County was selected as the experimental sites. The ditch was divided into 3 groups: a film group, a niclosamide group, and a niclosamide and film group. The snails were surveyed before the test and 1, 3, 5, 7 days after the experiment. RESULTS: After the film covering, the highest temperature of the surface of soil was 63.7 degrees C on the first day, and the temperature higher than 40 degrees C lasted 4.34 hours. On the second day, the highest temperature was 52.3 degrees C, and the temperature higher than 40 degrees C lasted 4.96 hours. On the fourth day and fifth day, the temperature was lower than 30 degrees C, while the temperature was lower than 34 degrees C on the sixth day. On the seventh day of the experiment, the snail death rates of the film group, the niclosamide group, and the niclosamide and film group on the soil surface were 16.36%, 58.40% and 53.57%, respectively. On the seventh day, the snail death rates of the film group, and the niclosamide and film group under the soil were 20.00% and 40.00%, respectively, while no snails were found under the soil in the niclosamide group 3 days after the experiment. In mesh bags, the snail death rates of the film group, the niclosamide group, and the niclosamide and film group were 84.00%, 95.33% and 95.33%, respectively. CONCLUSION: The short-term effect of the black film covering on snail control is not obvious, and the black film covering does no promote the molluscicidal effect of niclosamide.

[Distribution of susceptible areas of schistosomiasis outside embankment in Hunan Province, 2011].

OBJECTIVE: To investigate the current distribution of susceptible areas of schistosomiasis outside embankment, so as to provide the evidence for making comprehensive measures in Hunan Province. METHODS: The outside embankment areas where Oncomelania snails possibly or historically distributed and people and animals had activities were surveyed. The schistosomiasis information of the susceptible areas was collected, a database was set up, the positions were marked with GPS, an E-map was drawn with Google Earth, and the distribution was analyzed. RESULT: The number of marshlands with schistosomiasis susceptible areas outside embankment was 787, the length was 1,429.64 km, and the area was 6,2017.17 hm(2). The average density of living snails was 0.37 snails/0.1 m(2), and the average density of infected snails was 0.0019 snails/0.1 m(2). The infected snails were found in 180 marshlands, and the area was 688.07 hm(2). Sixteen rivers had the susceptible areas, and the main vegetation was weeds. CONCLUSIONS: The susceptible area of schistosomiasis outside embankment is wide and complex. Therefore, the comprehensive control measures should be strengthened.

[Study on spatial-temporal variation of infected snail in bottomland areas after an integrated control strategy at village level in the marshland and lake regions based on geographic information system].

OBJECTIVE: To evaluate the effect of an integrated control strategy and to quantify the spatial-temporal variation of infected snails in the bottomland areas after the strategy was implemented. METHODS: Based on the geographic database of infected snail distribution at the village level during 2004 - 2010 in Anxiang county, Hunan province, spatial autocorrelation analysis and spatial scan statistics were applied to analyze the spatial-temporal characteristics on the distribution of infected snails. RESULTS: The number of embankments with infected snails in Anxiang county decreased from 23 in 2004 to 10 in 2010, while the rate of frame with infected snail in embankments decreased from 4.32‰ in 2004 to 0.12‰ in 2010. The spatial distribution of infected snails was nonrandom, only in 2004 and 2005 with Moran's I = 0.21 (P < 0.10) and Moran's I = 0.13 (P < 0.10) respectively. Data from the local spatial auto-correlation analysis showed that the number of villages with H-H types of auto-correlation model had been gradually decreasing. The results of SaTScan statistics appeared the same as from the local spatial auto-correlation analysis, showing that the number of areas with increased risk was decreasing. CONCLUSION: The comprehensive measures with emphasis on infectious source control seemed effective for schistosomiasis control program. The current distribution characteristics provided us with evidence that the resource assignment could be more reasonably implemented so as to control schistosomiasis in a more effective way.

[Application of multi-temporal China-Brazil Earth Recourses Satellite-02 data on surveillance of dynamic changes of water body of rivers and Oncomelania snail habitats in Anxiang County].

OBJECTIVE: To study the dynamic changes of the water body of rivers and Oncomelania snail habitats by using multi-temporal China-Brazil Earth Recourses Satellite-02 images taken in Anxiang County so as to establish the correct procedure for selecting images. METHODS: CBERS-02 images were collected on 20th December 2003, 10th February 2004, 10th April 2004, 19th June 2004, 10th August 2004 and 27th October 2004. Then the water body information from the study areas based on NDWI was extracted and the areas of water body were calculated to determine the images. RESULTS: The dynamic changes of the water body conformed to the rules of "water in summer and land in winter". Because of the rise of water, the water area in July was the biggest and the water area began to decline from August. The water area in April was the smallest. Then the wet season and the dry season should be June and April. CONCLUSION: The multi-temporal CBERS-02 images could be used to surveillance the dynamic changes of the water area and helpful in choosing the right images of the wet season and dry season.

[Study on spatial distribution of advanced schistosomiasis at village level in Anxiang County based on geographic information system].

OBJECTIVE: To explore the spatial distribution and pattern of advanced schistosomiasis in Anxiang County so as to provide the evidence for improving advanced schistosomiasis control. METHODS: Based on the geographic database of advanced schistosomiasis distribution at the village level in Anxiang County, Hunan Province, the spatial autocorrelation analysis and spatial scan statistics were applied to analyze the spatial characteristics of distribution of advanced schistosomiasis. RESULTS: The global Moran's I of prevalence rate of advanced schistosomiasis was 0.06 (P > 0.05) and there was no spatial auto-correlation as a whole. The local spatial auto-correlation analysis showed that there were 9 villages with statistically significant LISA value (P < 0.05), among which existed high-high, low-high and high-low types of auto-correlation model. The results of SaTScan statistics was the same as local spatial auto-correlation analysis and showed the existence of one cluster area. CONCLUSIONS: There are local spatial auto-correlation and spatial aggregation of advanced schistosomiasis in Anxiang County. According to the distribution characteristics, we can assign resource more reasonably and control schistosomiasis more effectively.