Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013

Predicting Climate Change Impact on the Habitat Suitability of the Schistosoma Intermediate Host Oncomelania hupensis in the Yangtze River Economic Belt of China

Oncomelania hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of O. hupensis habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB) and the ecological stability of Yangtze River Basin. Therefore, it is crucial to analyze the influence of climate change on the distribution of O. hupensis in order to achieve accurate control over its population. This study utilized the MaxEnt model to forecast possible snail habitats by utilizing snail distribution data obtained from historical literature. The following outcomes were achieved: The primary ecological factors influencing the distribution of O. hupensis are elevation, minimum temperature of the coldest month, and precipitation of wettest month. Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution center for O. hupensis; specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest. These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, result in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

Measurement and characteristics of the temporal-spatial evolution of China's healthcare services efficiency

BACKGROUND

Healthcare services efficiency (HSE) is directly related to the healthcare demands of the general public and also plays an essential role in the country's coordinated economic and social development.

METHODS

In this study, the stochastic frontier approach (SFA)-Malmquist model was applied to measure the HSE of 31 Chinese provinces based on panel data from 2010-2020. Then, kernel density estimation, Markov chain, and exploratory spatial data analysis were adopted to study the temporal-spatial dynamic evolution characteristics of the HSE.

RESULTS

The study found that China's HSE showed an average value of approximately 0.841, indicating room for improvement. The HSE varied significantly across regions, presenting an "East > Central > West" distribution layout. The TFP of healthcare services in China grew by 1.6% per year, driven mainly by technological progress of 1.8% per year. The trend of the HSE shifting to a high level in China was significant, but its evolution exhibited stability of maintaining the original state, and it was harder to achieve leapfrog transfer. The temporal-spatial evolution of the HSE was also significantly affected by geospatial factors, with a clear spatial spillover effect and spatial agglomeration characteristics. Provinces with high-level HSE exhibited positive spatial spillover effects, while provinces with low-level HSE had negative spatial spillover effects. Thus, the "club convergence" phenomenon of "high efficiency concentration, low efficiency agglomeration, high levels of radiation, and low levels of suppression" was formed in the spatial distribution.

CONCLUSIONS

The results indicate that countermeasures should be taken to improve the HSE in China. Theoretical support for the improvement of HSE is provided in this paper.

A study of primary health care service efficiency and its spatial correlation in China

BACKGROUND

China's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China's primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution.

METHODS

Based on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions.

RESULTS

The number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China.

CONCLUSION

The service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.

Spatial Distribution of Dicrocoelium in the Himalayan Ranges: Potential Impacts of Ecological Niches and Climatic Variables

PURPOSE

Dicrocoeliosis can be an important cause of production loss in ruminants due to the cost of liver condemnation at slaughter. The aim of the present study was to determine the prevalence of Dicrocoelium infection and to predict the ecological niches and climatic variables that support dicrocoeliosis in the Himalayan ranges of Pakistan.

METHODS AND RESULTS

Dicrocoelium was detected in 33 of 381 liver samples and 238 of 6060 blood samples taken from sheep and goat herds in the area. The prevalence of dicrocoeliosis was higher in sheep than in goats and highest in females aged more than 3 years. An environmental risk map was created to predict active zones of transmission and showed the highest probability values in central parts of the Chitral district in the northwest of Pakistan. Climatic variables of the mean monthly diurnal temperature range (Bio2), annual precipitation (Bio12), and normalised difference vegetation index (NDVI) were found to be significantly (p < 0.05) associated with the presence of Dicrocoelium infection.

CONCLUSION

Together, the findings of this study demonstrate the most suitable ecological niches and climatic variables influencing the risk of dicrocoeliosis in the Himalayan ranges of Pakistan. The methods and results could be used as a reference to inform the control of dicrocoeliosis in the region.

Spatial Analysis of Schistosomiasis in Hunan and Jiangxi Provinces in the People's Republic of China

Understanding the spatial distribution of schistosome infection is critical for tailoring preventive measures to control and eliminate schistosomiasis. This study used spatial analysis to determine risk factors that may impact Schistosoma japonicum infection and predict risk in Hunan and Jiangxi Provinces in the People's Republic of China. The study employed survey data collected in Hunan and Jiangxi in 2016. Independent variable data were obtained from publicly available sources. Bayesian-based geostatistics was used to build models with covariate fixed effects and spatial random effects to identify factors associated with the spatial distribution of infection. Prevalence of schistosomiasis was higher in Hunan (12.8%) than Jiangxi (2.6%). Spatial distribution of schistosomiasis varied at pixel level (0.1 × 0.1 km), and was significantly associated with distance to nearest waterbody (km, β = -1.158; 95% credible interval [CrI]: -2.104, -0.116) in Hunan and temperature (°C, β = -4.359; 95% CrI: -9.641, -0.055) in Jiangxi. The spatial distribution of schistosomiasis in Hunan and Jiangxi varied substantially and was significantly associated with distance to nearest waterbody. Prevalence of schistosomiasis decreased with increasing distance to nearest waterbody in Hunan, indicating that schistosomiasis control should target individuals in close proximity to open water sources as they are at highest risk of infection.

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to be produced to guide national control programs. This study used an ecological niche modeling (ENM) and precision mapping approach to estimate environmental suitability and disease transmission risk. The results show that suitability for schistosomiasis is widespread and covers 264,781 km2 (102,232 sq miles). Covariates of significance to the model were the accessibility to cities, distance to water, enhanced vegetation index (EVI), annual mean temperature, land surface temperature (LST), clay content, and annual precipitation. Disease transmission risk is greatest in the central highlands, tropical east coast, arid-southwest, and northwest. An estimated 14.9 million people could be at risk of schistosomiasis; 11.4 million reside in rural areas, while 3.5 million are in urban areas. This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations. Because of the focal nature of the disease, these maps can inform national surveillance programs while improving understanding of areas in need of medical interventions.

Research on Urban Medical and Health Services Efficiency and Its Spatial Correlation in China: Based on Panel Data of 13 Cities in Jiangsu Province

The improvement of the efficiency of medical and health services is of great significance for improving the high-quality and efficient medical and health services system and meeting the increasingly diverse health needs of residents. Based on the panel data of 13 cities in Jiangsu Province, this research analyzed the relative effectiveness of medical and health services from 2015 to 2019 using the super efficiency slack-based measure-data envelopment analysis model, and the Malmquist index method was used to explore the changes in the efficiency of medical and health services from a dynamic perspective. Furthermore, the spatial autocorrelation analysis method was used to verify the spatial correlation of medical and health services efficiency. In general, there is room for improvement in the efficiency of medical and health services in 13 cities in Jiangsu Province. There are obvious differences in regional efficiency, and there is a certain spatial correlation. In the future, the medical and health services efficiency of China’s cities should be improved by increasing the investment in high-quality medical and health resources, optimizing their layout and making full use of the spatial spillover effects between neighboring cities to strengthen inter-regional cooperation and exchanges.

Use of geographic information system as a tool for schistosomiasis surveillance in an endemic Municipality in Eastern Samar, The Philippines

This study aimed to demonstrate the use of geographic information systems (GIS) in identifying factors contributing to schistosomiasis endemicity and identifying high-risk areas in a schistosomiasis- endemic municipality in the Philippines, which was devastated by Typhoon Haiyan in 2013. Data on schistosomiasis determinants, obtained through literature review, the Philippine Department of Health, and concerned local government units, were standardized and incorporated into a GIS map using ArcGIS. Data gathered included modifiable [agriculture, poverty, sanitation, presence of intermediate and reservoir hosts, disease prevalence and mass drug administration (MDA) coverage] and nonmodifiable (geography and climate) determinants for schistosomiasis. Results showed that most barangays (villages) are characterized by favourable conditions for schistosomiasis transmission which include being located in flood-prone areas, presence of vegetation, low sanitary toilet coverage, presence of snail intermediate host, high carabao (water buffalo) population density, previously reported ≥1% prevalence using Kato-Katz technique, and low MDA coverage. Similarly, barangays not known to be endemic for schistosomiasis but also characterized by the same favourable conditions for schistosomiasis as listed above and may therefore be considered as potentially endemic, even if not being high-risk areas. This study demonstrated the importance of GIS technology in characterizing schistosomiasis transmission. Maps generated through application of GIS technology are useful in guiding program policy and planning at the local level for an effective and sustainable schistosomiasis control and prevention.

Changes in geographic clustering of post-traumatic stress disorder and post-traumatic growth seven years after an earthquake in Cauquenes, Chile

Recent findings indicate that both disruptive Post-Traumatic Stress Disorder (PTSD) and healthy Post-Traumatic Growth (PTG) responses have some spatial distribution depending on where they are measured and the different degrees of exposure that people may have to a critical event (e.g., earthquake). Less is known about how these responses change as a function of space and time after these events. The objective of this study was to enter deeper into this relationship analysing how PTSD and PTG responses vary in their spatial distribution 6 and 7 years after an earthquake (such as the one that occurred on 27 February, 2010 in Cauquenes City, Chile). Spatial analyses based on Geographic Information Systems (GIS) were performed to detect global and local geographic clustering. Investigating 171 (2016) and 106 (2017) randomly selected adults from Cauquenes, we demonstrated that 7 years after the event only 4 variables were spatially clustered, i.e. personal mental strength, interpersonal relations, new possibilities and appreciation of life), all of them PTG dimensions; This result contrasted with the situation the previous year (2016), when 7 variables were clustered (total PTG, spiritual change, new possibilities, appreciation of life, PTSD symptoms, PTSD reactions and PTSD in total). The spatial identifications found could facilitate the comparison of mental health conditions in populations and the impact of recovery programmes in communities exposed to disasters.

Application of GIS Spatial Analysis and Scanning Statistics in the Gynecological Cancer Clustering Pattern and Risk Screening: A Case Study in Northern Jiangxi Province, China

OBJECTIVE

The incidence of gynecological cancer is high in China, and the effects of related treatments and preventive measures need to be improved.

METHODS

This study uses GIS spatial analysis methods and a scanning statistical analysis to study the major gynecological cancers in northern Jiangxi Province from 2016 to 2018.

RESULTS

The incidence and spatial pattern of cervical cancer, ovarian cancer, and uterine cancer had agglomeration characteristics and changes during the study period. The gynecological cancer had a spatial autocorrelation and agglomeration in its spatial pattern. The Moran's Index of the overall gynecological cancer incidence rate was 0.289 (p = 0.005). Ripley's L(d) function showed that the agglomeration radius was between 51.40 and 52.82 km. The results of the kernel density estimation showed that the cases of gynecological cancer were concentrated in the central and northeastern areas of the study area. The overall county-level incidence of gynecological cancer varied from 0.26 to 11.14 per 100,000. The results of the gravity center analysis showed that the spatial distribution of the gravity center point of gynecological cancer had moved toward the east during the past three years. The results of a hotspot analysis showed that there were five hotspot areas that had gynecological cancers. The most likely clusters of gynecological cancer at the county level in northern Jiangxi Province were distributed in the adjacent areas of Jiujiang, Yichun, and Nanchang, with a relative risk of 1.85.

CONCLUSION

The research shows that GIS can display the distribution of cancer cases and can use spatial analysis methods and scanning statistical techniques to obtain key areas of cancer incidence. These results can provide data and key areas for the formulation of regional public health policies and provide recommendations for cancer screening and the rational allocation of health resources.

Impacts of Physical Environment Perception on the Frailty Condition in Older People

Frailty increases the vulnerability of older people who commonly develop a syndrome leading to growing dependence and finally often death. Physical environment conditions may affect the severity of the syndrome positive or negatively. The main objective of this study was to analyse the conditions of different urban physical environments and their relationship with the frailty syndrome in older people. Geographic Information Systems (GIS) analyses were performed to detect global and local geographic clustering. Investigating 284 adults with ages from 60 to 74 years old from Talca City, Chile, we found spatial clustering of frailty conditions registered for older people, with hotspots of high and low values associated with areas of different urban infrastructures and socioeconomic levels into the city. The spatial identifications found should facilitate exploring the impact of mental health programmes in communities exposed to disasters like earthquakes, thereby improving their quality of life as well as reducing overall costs. Spatial correlation has a great potential for studying frailty conditions in older people with regard to better understanding the impact of environmental conditions on health.

Predicting environmental suitability and geographical distribution of Dicrocoelium dendriticum at littoral of Caspian Sea: An ecological niche-based modeling

Dicrocoeliasisis caused by the small liver fluke (Dicrocoelium spp.), mainly Dicrocoelium dendriticum in domestic and wild ruminants. The small liver fluke is the probable predisposing cause of economic burden. The impact of geographic and climatic factors on the incidence of dicrocoeliasis has been severely ignored in different geographical areas. Due to the lack of data regarding dicrocoeliasis in Iran, this study was aimed to investigate the prevalence and intensity of ovine and bovine Dicrocoelium infection in the coastal strip south of the Caspian Sea. Fecal samples were obtained from the cattle and sheep in three provinces of Guilan, Mazandaran and Golestan at the littoral of the Caspian Sea. All collected samples were then tested by flotation methods for determining the number of eggs per gram of feces (EPG). Moreover, we applied maximum entropy niche-based modeling (MaxEnt), coupled with remote sensing and the Geographical Information System (GIS) to visualize the spatial distribution and risk factors of Dicrocoelium dendriticum at the littoral of Caspian Sea. A total of 2688 stool samples were collected from cattle (n = 1344) and sheep (n = 1344) in coastal provinces of the Caspian Sea including Guilan (n = 1280), Mazandaran (n = 768) and Golestan (n = 640) provinces. Based on the data presented here, the highest rate of infection was observed in Guilan and Mazandaran provinces. The results revealed the prevalence rates of 36.72% and 6.09% for sheep and cattle in Guilan province, respectively. This rate was 22.4% for sheep and 3.91% for cattle in Mazandaran province. However, the rate of sheep infection was 90% in some point locations. Dicrocoelium infection was found to be significantly different between three provinces in sheep (P < 0.00001, Chi = 111.633). Our findings exhibited a high reliability of the MaxEnt model, and area under the curve (AUC) values of the training and test data sets were determined to be 0.852 and 0.818, respectively. Jackknife analysis showed the relative variable contribution to the model performance, where four variables were found as key influential factors that highly affected the habitat suitability of the presence of the lancet fluke including the precipitation of driest quarter (Bio17), altitude, temperature seasonality (Bio4), and precipitation of driest month (Bio14). The findings of this study demonstrated a high presence rate of Dicrocoelium infection at the littoral of Caspian Sea, Iran. Moreover, climatic variables can be considered as important predictive factors affecting the distribution of infection in the studied areas. Further studies based on the findings of the GIS are also very important in the country for planning control programs.

Epidemiological Trend of Typhoid and Paratyphoid Fevers in Zhejiang Province, China from 1953 to 2014

Background: The incidences of typhoid and paratyphoid remain high and these diseases still pose a public health problem in China and in Zhejiang Province in particular. This study aimed to investigate the trend of typhoid and paratyphoid in Zhejiang Province from 1953 to 2014 and to provide a theoretical basis for the prevention and control of these diseases. Methods: Included in this study were compiled epidemiological data of typhoid and paratyphoid cases in Zhejiang from 1953 to 2003 and epidemiological data of those from 2004 to 2014 registered in the China Information System for Diseases Control and Prevention. Description methods were employed to explore the epidemiological characteristics, including long-term trend, gender distribution, age distribution, and occupation distribution. Incidence maps were made to represent the annual average incidences for each municipality. Spearman’s rank correlation was performed to detect the correlation between incidence and average elevation, and circular distribution was calculated to identify the seasonality and peak days of the diseases. A p-value of <0.05 was considered statistically significant. Results: A total of 182,602 typhoid and paratyphoid cases were reported in Zhejiang Province from 1953 to 2014, and the average annual incidence was 7.89 per 100,000 population. The incidence in 2014 decreased by 93.82% compared with that in 1953 and by 95.00% compared with the highest incidence rate. The average incidence before 2003 was negatively correlated with the average elevation of each region in Zhejiang province (r < 0, p < 0.05), but there was no statistically significant correlation from 2003. The peak period of diseases fell in the months from April to October every year. The incidence among the population group aged over 35 rose gradually but declined sharply among those between 20 and 34. Conclusions: The incidence of typhoid and paratyphoid decreased in Zhejiang Province from 1953 to 2014 but remained high in some regions. Proper measures for prevention and control are warranted in the southeast coast areas and for high-risk populations.

Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China

This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff's spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial cluster in 2007 covered the north-central part of Jianghan Plain, whereas those observed from 2008 to 2012 were toward the south, with extended coverage in generally the same areas across various periods, and some variation nevertheless in precise locations. Furthermore, the 2007 period was more likely to be clustered than any other period. We found that temperature, land use, and soil type were the most critical factors associated with infection rates in humans. In addition, land use and soil type had the greatest impact on the prevalence of schistosomiasis in 2009, whereas this effect was minimal in 2007. The effect of temperature on schistosomiasis prevalence reached its maximum in 2010, whereas in 2008, this effect was minimal. Differences observed in the effects of those two factors on the spatial distribution of human schistosomiasis were inconsistent, showing statistical significance in some years and a lack thereof in others. Moreover, when two factors operated simultaneously, a trend of enhanced interaction was consistently observed. High-risk areas with strong interactions of affected factors should be targeted for disease control interventions.

Spatial distribution of 12 class B notifiable infectious diseases in China: A retrospective study

BACKGROUND

China is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China.

METHODS

Global and local Moran's I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps.

RESULTS

Of the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high-low (unit with high incidence surrounded by units with high incidence, the same below) and high-high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low-low and low-high spatial cluster areas abound in provincial units in north and east China.

CONCLUSION

Despite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high-high/high-low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders.

Dynamics of spatiotemporal distribution of schistosomiasis in Hubei Province, China

Schistosomiasis caused by parasitic flatworms of blood flukes, remains a major public health concern in China. The significant progress in controlling schistosomiasis in China over the past decades has resulted in the remarkable reduction in the prevalence and intensity of Schistosoma japonicum infection to an extremely low level. Therefore, the elimination of schistosomiasis has been promoted by the Chinese national government. Hubei Province is the major endemic area, that is, along the middle and low reaches of the Yangtze River in the lake and marshland regions of southern China. Eliminating the transmission of schistosomiasis in Hubei Province is challenging. The current issue is to determine the distributions and clusters of schistosomiasis transmission. In this study, we assessed the spatial distribution of schistosomiasis and the risk at the county level in Hubei Province from 2011 to 2015 to provide guidance on the elimination of schistosomiasis transmission in lake and marshland regions. Spatial database of human S.japonicum infection from 2011 to 2015 at the county level in the study area was built based on the annual schistosomias is surveillance data. Moran's I, the global spatial autocorrelation statistics, was utilized to describe the spatial autocorrelation of human S. japonicum infection. In addition, purely spatial scan statistics combined with space-time scan statistics were used to determine the epidemic clusters. Infection rates of S. japonicum decreased in each endemic county in Hubei from 2011 to 2015. Human S. japonicum infection rate showed statistical significance by global autocorrelation analysis during the study period (Moran's I > 0, P < 0.01). This result suggested that there were spatial clusters present in the distribution of S. japonicum infection for the five years. Purely spatial analysis of human S. japonicum infection showed one most likely cluster and one secondary cluster from 2011 to 2015, which covered four and one counties, respectively. Spatiotemporal clustering analysis determined one most likely cluster and one secondary cluster both in 2011-2012, which appeared in 4 and 5 counties, respectively. However, the number of clustering foci decreased with time, and no cluster was detected after 2013.The clustering foci were both located at the Jianghan Plain, along the middle reaches of the Yangtze River and its connecting branch Hanbei River. Spatial distribution of human S. japonicum infections did not change temporally at the county level in Hubei Province. A declining trend in spatiotemporal clustering was observed between 2011 and 2015. However, effective control strategies and integrated prevention should be continuously performed, especially at the Jianghan Plain area along the Yangtze and Hanbei River Basin. Multivariate statistical analysis was carried out to investigate the risk of missing examinations, missing treatment, and unstandardized treatment events. The results showed that age, education level and Sanitary latrines are risk factors for missing examinations (b > 0, OR >1), and treatment times in past and feeding cattle in village group are protective factors (b < 0, OR <1). We also found that age and education level are risk factors for missing treatment (b > 0, OR >1). Study of the risk for un-standardized treatment revealed that occupation is risk factors (b > 0, OR >1), though, education level is protective factors (b < 0, OR <1). Therefore, precise prevention and control should be mainly targeted at these special populations.

Village-based spatio-temporal cluster analysis of the schistosomiasis risk in the Poyang Lake Region, China

Background

The Poyang Lake Region, one of the major epidemic sites of schistosomiasis in China, remains a severe challenge. To improve our understanding of the current endemic status of schistosomiasis and to better control the transmission of the disease in the Poyang Lake Region, it is important to analyse the clustering pattern of schistosomiasis and detect the hotspots of transmission risk.

Results

Based on annual surveillance data, at the village level in this region from 2009 to 2014, spatial and temporal cluster analyses were conducted to assess the pattern of schistosomiasis infection risk among humans through purely spatial (Local Moran’s I, Kulldorff and Flexible scan statistic) and space-time scan statistics (Kulldorff). A dramatic decline was found in the infection rate during the study period, which was shown to be maintained at a low level. The number of spatial clusters declined over time and were concentrated in counties around Poyang Lake, including Yugan, Yongxiu, Nanchang, Xingzi, Xinjian, De’an as well as Pengze, situated along the Yangtze River and the most serious area found in this study. Space-time analysis revealed that the clustering time frame appeared between 2009 and 2011 and the most likely cluster with the widest range was particularly concentrated in Pengze County.

Conclusions

This study detected areas at high risk for schistosomiasis both in space and time at the village level from 2009 to 2014 in Poyang Lake Region. The high-risk areas are now more concentrated and mainly distributed at the river inflows Poyang Lake and along Yangtze River in Pengze County. It was assumed that the water projects including reservoirs and a recently breached dyke in this area were partly to blame. This study points out that attempts to reduce the negative effects of water projects in China should focus on the Poyang Lake Region.

Relative importance of meteorological and geographical factors in the distribution of Fasciola hepatica infestation in farmed sheep in Qinghai province, China

Fasciola hepatica is an important trematode parasite of economic importance that infests sheep and cattle worldwide. We conducted a detailed investigation into the spatial distribution of F. hepatica infestation in farmed sheep in Qinghai (Wutumeiren) province, Mainland China. Mathematical modelling was used to assess the inter-relationships between meteorological and geographical factors and the risk of F. hepatica infestation across the province. A capture enzyme-linked immunosorbent assay (ELISA) test (MM3-SERO) was used to detect F. hepatica infestation. A niche model based on the maximum entropy method (MaxEnt) was used to estimate the influence of meteorological and geographical factors on the observed spatial distribution of F. hepatica infestation. Results of jackknife analysis indicated that temperature, precipitation, solar radiation, digital elevation and slope were associated with the occurrence of F. hepatica infestation, and that infestation rates were significantly higher among animals from districts with a high percentage of grassland habitat. The findings indicate that meteorological and geographical factors may be important variables affecting the distribution of F. hepatica infestation and should be taken into account in the development of future surveillance and control programmes for fascioliasis.

A spatial analysis of human Schistosoma japonicum infections in Hubei, China, during 2009-2014

BACKGROUND

The province of Hubei is located in the middle of China, near the middle and lower reaches of the River Yangtze, and is an area where schistosomiasis is endemic. It is challenging to control this disease in this environment, and it would be useful to identify clusters of infection and transmission, as well as their distributions during recent years. Therefore, this study aimed to analyze the spatial distribution of schistosomiasis in Hubei, in order to facilitate the effective control and elimination of this disease.

METHODS

We collected schistosomiasis surveillance data from all endemic counties in Hubei during 2009-2014. A geographical information system (ArcGIS, version 10.1) was used to link the counties' geographical data with the epidemiological data, and the spatial scanning method (FleXScan v3.1.2) was used to identify spatial clusters of human infections with Schistosoma japonicum.

RESULTS

In Hubei, patients who exhibited stool test results that were positive for S. japonicum accounted for > 50 % of all cases in China during 2009-2014. However, each endemic county in Hubei exhibited a declining trend in the number of human S. japonicum infections during the study period. The ArcGIS analyses revealed that the middle reaches of the River Yangtze were highly endemic for S. japonicum infections. Spatial scan analyses revealed the following infection clusters: two clusters in ten counties during 2009, two clusters in nine counties during 2010, three clusters in 12 counties during 2011, two clusters in 12 counties during both 2012 and 2013 and two clusters in ten counties during 2014. Most of the cluster regions were located in the lake and marshland regions along the basins of the River Yangtze.

CONCLUSION

We successfully identified schistosomiasis clusters at the county level in Hubei during 2009-2014, and our results revealed that the clusters were typically located in lake and marshland regions. These data may be useful for controlling and eliminating schistosomiasis in other high-risk areas.