Dynamics of spatial clustering of schistosomiasis in the Yangtze River Valley at the end of and following the World Bank Loan Project

Unraveling trends in schistosomiasis: deep learning insights into national control programs in China

OBJECTIVES

To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China.

METHODS

We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS).

RESULTS

The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1,000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1,000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease.

CONCLUSIONS

The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

BACKGROUND

Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence.

METHODS

In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data.

RESULTS

The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen's kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways.

CONCLUSION

Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

Background: Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence. Methods: In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data. Results: The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen’s kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (NDWI) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways. Conclusion: Our results suggest that in low-transmission environments, investing in training geographic information systems professionals to leverage open-source environmental data could yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds-A Case Study of Dongting Lake Area

Spatio-temporal epidemic simulation, assessment, and risk monitoring serve as the core to establishing and improving the national public health emergency management system. In this study, we investigated Oncomelania hupensis breeding grounds and analyzed the locational and environmental preferences of snail breeding in Dongting Lake (DTL), Hunan, China. Using geographic information systems and remote sensing technology, we identified schistosomiasis risk areas and explored the factors affecting the occurrence and transmission of the disease. Several key conclusions were drawn. (1) From 2006 to 2016, the spatial change of potential O. hupensis breeding risk showed a diminishing trend from the eastern and northern regions to southwest DTL. Environmental changes in the eastern DTL region resulted in the lakeside and hydrophilic agglomerations of the O. hupensis populations. The shift in snail breeding grounds from a fragmented to centralized distribution indicates the weakening mobility of the O. hupensis population, the increasing independence of solitary groups, and the growing dependence of the snail population to the local environment. (2) The spatial risk distribution showed a descending gradient from west Dongting area to the east and an overall pattern of high in the periphery of large lakes and low in other areas. The cold-spot areas had their cores in Huarong County and Anxiang County and were scattered throughout the peripheral areas. The hot-spot areas had their center at Jinshi City, Nanxian County, and the southern part of Huarong County. The areas with increased comprehensive risks changed from centralized and large-scale development to fragmented shrinkage with increased partialization in the core area. The risk distribution's center shifted to the northwest. The spatial risk distribution exhibited enhanced concentricity along the major axis and increased dispersion along the minor axis.

Dynamic evolution of schistosomiasis distribution under different control strategies: Results from surveillance covering 1991-2014 in Guichi, China

Background

Since the founding of the China, the Chinese government, depending on the changing epidemiological situations over time, adopted different strategies to continue the progress towards elimination of schistosomiasis in the country. Although the changing pattern of schistosomiasis distribution in both time and space is well known and has been confirmed by numerous studies, the problem of how these patterns evolve under different control strategies is far from being understood. The purpose of this study is, therefore, to investigate the spatio-temporal change of the distribution of schistosomiasis with special reference to how these patterns evolve under different control strategies.

Methodology / Principal findings

Parasitological data at the village level were obtained through access to repeated cross-sectional surveys carried out during 1991–2014 in Guichi, a rural district along the Yangtze River in Anhui Province, China. A hierarchical dynamic spatio-temporal model was used to evaluate the evolving pattern of schistosomiasis prevalence, which accounted for mechanism of dynamics of the disease. Descriptive analysis indicates that schistosomiasis prevalence displayed fluctuating high-risk foci during implementation of the chemotherapy-based strategy (1991–2005), while it took on a homogenous pattern of decreasing magnitude in the following period when the integrated strategy was implemented (2006–2014). The dynamic model analysis showed that regularly global propagation of the disease was not present after the effect of proximity to river was taken into account but local pattern transition existed. Maps of predicted prevalence shows that relatively high prevalence (>4%) occasionally occurred before 2006 and prevalence presents a homogenous and decreasing trend over the study area afterwards.

Conclusions

Proximity to river is still an important determinant for schistosomiasis infection regardless of different types of implemented prevention and control strategies. Between the transition from the chemotherapy-based strategy to the integrated one, we noticed a decreased prevalence. However, schistosomiasis would remain an endemic challenge in these study areas. Further prevention and control countermeasures are warranted.

Schistosomiasis japonica is one of the most serious parasitic diseases in China. The Chinese government has launched three different rounds of national schistosomiasis control programs since 1950s. The latest two are the World Bank Loan Project (WBLP) that ushered in chemotherapy as the main control approach, active from 1992 to 2001, and the integrated control strategy that took its place in 2005. In this study, we investigated changes in the dynamics of schistosomiasis transmission over space and time under these different control strategies. Based on spatio-temporal analyses of the schistosomiasis prevalence data at the village level during 1991–2014 in Guichi, Anhui Province, we built a dynamic model to evaluate the evolving pattern of prevalence. We found that the schistosomiasis prevalence generally showed a north-western shift over the study area during 1991–2005, while there was no such trend during 2006–2014. This global shifting trend disappeared after the effect of proximity to river was taken into account, but local change still existed which was possibly due to the transition between the two latest national control strategies. We conclude that proximity to River is still an important determinant for schistosomiasis prevalence and that although the integrated control strategy is more effective than the WBPL in reducing schistosomiasis prevalence, the disease would remain endemic for the long term without further improvements of the control program.

Impact of continuous low water stage on the breeding environment of Oncomelania hupensis: a case study of Poyang Lake area in China

BACKGROUND

Oncomelania hupensis is the only intermediate host of Schistosoma japonicum and plays a decisive role in its transmission. The variation of water level greatly affects the reproduction and growth of snails. Therefore, in this paper, we analyze the variations of water level in the Poyang Lake region from 1993 to 2016 combined with satellite imagery to elucidate the evolution of the snail breeding environment.

METHODS

By employing remote sensing data from 1993 to 2016 (April-June and September-November), the vegetation area of Poyang Lake and the vegetation area at different elevations were extracted and calculated. Moreover, the average daily water level data from the four hydrological stations (Hukou station, Xingzi station, Tangyin station and Kangshan station) which represent the typical state of Poyang Lake were collected from 1993 to 2016. The variance of the monthly mean water level, inundation time and the average area were analyzed by variance to find a significance level of α = 0.05.

RESULTS

According to hydrological data before and after 2003, the average water level after 2003 is significantly lower than that before 2003 in Poyang Lake. After 2003, the time of inundateing the snail breeding period was later in April to June than that before 2003, while the time of wate-falling stage in September to November moved forward after 2003 than before 2003. Of them, the lowest water level affecting the breeding and growing period of O. hupensis in the northern part of Poyang Lake decreased from 11 m to 9 m. After 2003, the expansion of meadow area in the north part of Poyang Lake was mainly concentrated in the elevation of 9-11 m, and the newly increased infested-meadow in the lake area was mainly concentrated in the north part of Poyang Lake.

CONCLUSIONS

By comparing the change of water level characteristics in different parts of the Poyang Lake area as well as changes in meadow area before and after 2003, it is found that the water level changes mainly affect the snail breeding area in the northern part of Poyang Lake. The results are helpful for improving scientific measures for snail control in Jiangxi Province. This approach could also be applicible to Dongting Lake area and other lake areas affected by water level changes and can bring significant guidance for snail control in lake areas.

Spatiotemporal Heterogeneity in Human Schistosoma japonicum Infection at Village Level in Hubei Province, China

The spatiotemporal dynamics of Schistosoma japonicum, combined with temporal heterogeneity among regions of different epidemic areal-types from a microscale viewpoint might capture the local change dynamics and thus aid in optimizing the combinations of precise schistosomiasis control measures. The prevalence data on schistosomiasis infection from 2007 to 2012 in the 30 most endemic counties of Hubei Province, Central China, were appended to the village-level administrative division polygon layer. Anselin local Moran's I, a retrospective space-time scan statistic and a multilevel-growth model analysis framework, was used to investigate the spatiotemporal pattern of schistosomiasis resident infection rate (RIR) at the village level and how natural geographical environment influence the schistosomiasis RIR over time. Two spatiotemporal high-risk clusters and continuous high-rate clusters were identified mainly in the embankment region across flooding areas of lakes connected with the Yangze and Hanjiang Rivers. Moreover, 12 other clusters and outlier evolution modes were detected to be scattered across the continuous high-rate clusters. Villages located in embankment region had the highest initial values and most rapidly reduced RIRs over time, followed by villages located in marshland-and-lake regions and finally by villages located in hilly region. Moreover, initial RIR values and rates of change did significantly vary (p < 0.001 and p < 0.001, respectively) irrespective of their epidemic areal-type. These local spatiotemporal heterogeneities could contribute to the formulation of distinct control strategies based on local transmission dynamics and be applied in other endemic areas of schistosomiasis.

Identification of high-risk habitats of Oncomelania hupensis, the intermediate host of schistosoma japonium in the Poyang Lake region, China: A spatial and ecological analysis

BACKGROUND

Identifying and eliminating snail habitats is the key measure for schistosomiasis control, critical for the nationwide strategy of eliminating schistosomiasis in China. Here, our aim was to construct a new analytical framework to predict high-risk snail habitats based on a large sample field survey for Oncomelania hupensis, providing guidance for schistosomiasis control and prevention.

METHODOLOGY/PRINCIPAL FINDINGS

Ten ecological models were constructed based on the occurrence data of Oncomelania hupensis and a range of variables in the Poyang Lake region of China, including four presence-only models (Maximum Entropy Models, Genetic Algorithm for rule-set Production, Bioclim and Domain) and six presence-absence models (Generalized Linear Models, Multivariate Adaptive Regression Splines, Flexible Discriminant Analysis, as well as machine algorithmic models-Random Forest, Classification Tree Analysis, Generalized Boosted Model), to predict high-risk snail habitats. Based on overall predictive performance, we found Presence-absence models outperformed the presence-only models and the models based on machine learning algorithms of classification trees showed the highest accuracy. The highest risk was located in the watershed of the River Fu in Yugan County, as well as the watershed of the River Gan and the River Xiu in Xingzi County, covering an area of 52.3 km2. The other high-risk areas for both snail habitats and schistosomiasis were mainly concentrated at the confluence of Poyang Lake and its five main tributaries.

CONCLUSIONS/SIGNIFICANCE

This study developed a new distribution map of snail habitats in the Poyang Lake region, and demonstrated the critical role of ecological models in risk assessment to directing local field investigation of Oncomelania hupensis. Moreover, this study could also contribute to the development of effective strategies to prevent further spread of schistosomiasis from endemic areas to non-endemic areas.

Distribution pattern of the snail intermediate host of schistosomiasis japonica in the Poyang Lake region of China

BACKGROUND

With the closure of the Three Gorges Dam in 2003 the hydrology of Poyang Lake was altered dramatically leading to significant changes in the environment. In order to assess the impact on schistosomiasis this study assessed the spatial and temporal patterns of the snail intermediate host, Oncomelania hupensis in the Poyang Lake tributaries. The results of the study have important implications for future snail control strategies leading to disease elimination.

METHODS

The marshland area surrounding Poyang Lake was divided randomly into 200 × 200 m vector grids using ArcGIS software, and the surveyed grids were randomly selected by the software. The snail survey was conducted in each selected grid using a survey frame of 50 × 50 m with one sideline of each grid serving as the starting line. No less than ten frames were used in each surveyed grid with Global Positioning System (GPS) recordings for each. All snails in each frame were collected to determine infection status by microscopy. Altitude data for all frames were extracted from a lake bottom topographic map in order to analyze the average altitude. All snail survey data were collected and statistically analyzed with SPSS 20.0 software in order to determine the difference of the percentage of frames with living snails and mean density of living snails in different regions of Poyang Lake. The altitude of the snail-infested marshlands and snail dens were subsequently identified.

RESULTS

A total of 1159 potential snail sampling grids were surveyed, of which 15 231 frames (0.1 m2/frame) were investigated. 1241 frames had live Oncomelania snails corresponding to 8.15% of the total number of frames. The mean density of living snails was 0.463/0.1 m2 with a maximum of 57 snails per frame. The percent of frames with snails in the southern sector (8.13%) of Poyang Lake did not differ statistically from the north (8.21%). However, the mean density of live snails in the northern sector (0.164/0.1 m2) of the lake was statistically higher (F = 6.727; P = 0.010) than the south (0.141/0.1 m2). In the south of the lake, the elevation of snail-inhabited marshland ranged between 11 - 16 m, and could be further subdivided into two snail-concentrated belts at 12-13 m of elevation and 15-16 m of elevation respectively. In the north of the lake, the elevation of snail-inhabited marshland ranged between 9- 16 m with the elevation of 12-14 m being the snail-concentrated zone.

CONCLUSIONS

The elevation of snail-infested marshlands in the Poyang Lake region ranged from 9 to 16 m. The snail distribution and habitat has moved north of the lake and to a lower altitude due to changes in the water level post dam closure. Based on the current geological features of the snail habitant focused mollusciciding should occur in snail dense northern regions with frequent bovine and human traffic. Targeting these identified 'hotspots' of transmission will assist in elimination efforts.

A Spatiotemporal Analysis of Schistosomiasis in Hunan Province, China

Based on annual parasitological data recently collected at county and village levels, this article presents a multiscale spatiotemporal analysis of transmission risk of schistosomiasis japonica in Hunan Province during 2001 to 2015 in a geographic information system environment. The study shows that the incidence and prevalence rate of human Schistosoma japonicum infection in Hunan Province decreased after 2001. A spatial autocorrelation analysis reveals the existence of spatial clusters of human Schistosoma japonicum infection and a growing tendency of spatial clustering over time. The identification of high-risk areas (hot spots) helps find areas of priority for future implementation of control strategies. The research demonstrates the importance of spatial scale in public health studies.

Analysis of risk factors and changing trends the infection rate of intestinal schistosomiasis caused by S. japonicum from 2005 to 2014 in Lushan city

Intestinal schistosomiasis caused by S. japonicum has long been a threat to the health of residents within endemic areas, especially along the mid-tier of the Yangtze River basin as well as the Dongting and Poyang lakes. Therefore, we collected monitoring data from 2005 to 2014 in Lushan City, Jiujiang City, Jiangxi Province, which is located downstream of Poyang Lake. We conducted a logistic regression analysis in 2005 and in 2008 and then conducted a time series analysis from 2005 to 2014 in Lushan city. The results of the logistic regression analysis showed that after integrated measures were implemented in Lushan city in 2004, the infection rate of intestinal schistosomiasis decreased sharply in different populations, but fishermen had a greater risk of contracting intestinal schistosomiasis in both 2005 and 2008. From the time series analysis, we found that the infection rate decreased sharply from 2005 to 2009 and then increased slowly from 2009 to 2011 before finally becoming relatively stable and the predicated infection rates in HES, SM2, and SM3 are -1.14%, 0.35%, 0.29%, respectively, compared with 0.41% of schistosomiasis infection in 2014, showing a downward trend. Our study indicated that the integrated measures initiated in 2004 in Lushan city had a positive effect on controlling intestinal schistosomiasis, but we should still emphasize special treatment of particular populations, such as fishermen, and should consider environmental changes, such as changes in the water level of Poyang Lake, in the future.

Spatio-temporal pattern of schistosomiasis in Anhui Province, East China: Potential effect of the Yangtze River - Huaihe River Water Transfer Project

Anhui Province has been one of typical epidemic areas of schistosomiasis in East China as a wide range of large lake and marshland regions provide an ideal environment for growth and reproduction of the intermediate snail host. With the completion of the Yangtze River-Huaihe River Water Transfer Project (YHWTP), launched by the end of 2016, the epidemic areas are expected to expand and controlling schistosomiasis remains a challenge. Based on annual surveillance data at the county level in Anhui for the period 2006-2015, spatial and temporal cluster analyses were conducted to assess the pattern of risk through spatial (Local Moran's I and flexible scan statistic) and space-time scan statistic (Kulldorff). It was found that schistosomiasis sero-prevalence was dramatically reduced and maintained at a low level. Cluster results showed that spatial extent of schistosomiasis contracted, but snail distribution remained geographically stable across the study area. Clusters, both for schistosomiasis and snail presence, were common along the Yangtze River. Considering the effect of the ongoing YHWTP on the potential spread of schistosomiasis, Zongyang County and Anqing, which will be transected by the new water-transfer route, should be given a priority for strengthened surveillance and control. Attention should also be paid to Guichi since it is close to one of the planned inlets of the YHWTP.

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.

The Spatial-Temporal Trend Analysis of Schistosomiasis from 1997 to 2010 in Anhui Province, Eastern China

Schistosomiasis is still prevalent in some parts of China. A shift in strategy from morbidity control to elimination has led to great strides in the past several decades. The objective of this study was to explore the spatial and temporal characteristics of schistosomiasis in Anhui, an eastern province of China. In this study, township-based parasitological data were collected from annual cross-sectional surveys during 1997-2010. The kernel k-means method was used to identify spatial clusters of schistosomiasis, and an empirical mode decomposition technique was used to analyze the temporal trend for Schistosoma japonicum in each clustered region. Overall, the prevalence of schistosomiasis remained at a low level except for the resurgence in 2005. According to the Caliński-Harabas index, all the townships were classified into three different clusters (median prevalence: 3.6 per 10,100, 1.8 per 10,000 and 1.7 per 10,000), respectively representing high-, median-, and low-risk clusters. There was an increasing tendency observed for the disease over time. The prevalence increased rapidly from 2003 to 2005, peaked in 2006, and then decreased afterward in the high-risk cluster. A moderate increase was observed in the median-risk cluster from 1998 to 2006, but there was an obvious decreasing tendency in the low-risk cluster after the year 2000. The spatial and temporal patterns of schistosomiasis were nonsynchronous across the three clusters. Disease interventions may be adjusted according to the risk levels of the clusters.

Approaches being used in the national schistosomiasis elimination programme in China: a review

Schistosomiasis japonica, caused by the human blood fluke Schistosoma japonicum, remains a major public health problem in China, although great success has been achieved. The control efforts during the past half-decade, notably the wide implementation of the new integrated strategy with emphasis on control of the source of S. japonicum infection across the country since 2004, has greatly reduced S. japonicum in humans, livestock, and intermediate host Oncomelania hupensis snails, and transmission control of schistosomiasis was achieved in China in 2015. A two-stage roadmap was therefore proposed for schistosomiasis elimination in 2015, with aims to achieve transmission interruption by 2020 and achieve disease elimination by 2025 in the country. During the last two decades, a variety of approaches, which target the epidemiological factors of schistosomiasis japonica have been developed, in order to block the transmission cycle of the parasite. These approaches have been employed in the national or local schistosomiasis control activities, and facilitated, at least in part, the progress of the schistosomiasis elimination programs. Here, we present an approach to control the source of S. japonicum infection, three new tools for snail control, three approaches for detecting and monitoring S. japonicum infection, and a novel model for health education. These approaches are considered to play a great role in the stage moving towards transmission interruption and elimination of schistosomiasis in China.

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.

Spatial measurement errors in the field of spatial epidemiology

Background

Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological analysis of spatial data.

Methods

Google Scholar, Medline, and Scopus databases were searched using a broad set of terms for papers indexed by a term indicating location (space or geography or location or position) and measurement error (measurement error or measurement inaccuracy or misclassification or uncertainty): we reviewed all papers appearing before December 20, 2014. These papers and their citations were reviewed to identify the relevance to our review.

Results

We were able to define and classify spatial measurement errors into four groups: (1) pure spatial location measurement errors, including both non-instrumental errors (multiple addresses, geocoding errors, outcome aggregations, and covariate aggregation) and instrumental errors; (2) location-based outcome measurement error (purely outcome measurement errors and missing outcome measurements); (3) location-based covariate measurement errors (address proxies); and (4) Covariate-Outcome spatial misaligned measurement errors. We propose how these four classes of errors can be unified within an integrated theoretical model and possible solutions were discussed.

Conclusion

Spatial measurement errors are ubiquitous threat to the validity of spatial epidemiological studies. We propose a systematic framework for understanding the various mechanisms which generate spatial measurement errors and present practical examples of such errors.

Shifts in the spatiotemporal dynamics of schistosomiasis: a case study in Anhui Province, China

Background

The Chinese national surveillance system showed that the risk of Schistosoma japonicum infection fluctuated temporally. This dynamical change might indicate periodicity of the disease, and its understanding could significantly improve targeted interventions to reduce the burden of schistosomiasis. The goal of this study was to investigate how the schistosomiasis risk varied temporally and spatially in recent years.

Methodology/Principal Findings

Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997-2010 in Anhui Province, East China. A multivariate autoregressive model, combined with principal oscillation pattern (POP) analysis, was used to evaluate the spatio-temporal variation of schistosomiasis risk. Results showed that the temporal changes of schistosomiasis risk in the study area could be decomposed into two sustained damped oscillatory modes with estimated period of approximately 2.5 years. The POPs associated with these oscillatory components showed that the pattern near the Yangtze River varied markedly and that the disease risk appeared to evolve in a Southwest/Northeast orientation. The POP coefficients showed decreasing tendency until 2001, then increasing during 2002-2005 and decaying afterwards.

Conclusion

The POP analysis characterized the variations of schistosomiasis risk over space and time and demonstrated that the disease mainly varied temporally along the Yangtze River. The schistosomiasis risk declined periodically with a temporal fluctuation. Whether it resulted from previous national control strategies on schistosomiasis needs further investigations.

We investigated changes in dynamics of schistosomiasis transmission over space and time in Anhui Province of East China. Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997–2010. A multivariate autoregressive model, combined with principal oscillation pattern (POP) analysis, was used to evaluate the spatio-temporal variation of schistosomiasis risk. The schistosomiasis risk changed temporally as a damped oscillatory mode with a fluctuation, indicating that the disease risk declined periodically but with a temporal ascent during the study period. This change might result from national control strategies on schistosomiasis. The POP analysis also demonstrated a shifting spatial pattern of schistosomiasis along the Yangtze River. The POP method is commonly used in geosciences but not in epidemiology. Our analysis based on the approach provided new insights into the research of schistosomiasis transmission. The utility of such methods for addressing epidemiological problems will grow as more large-scale datasets become readily available.

Spatial, temporal, and spatiotemporal analysis of malaria in Hubei Province, China from 2004-2011

Background

Malaria remains a public health concern in Hubei Province despite the significant decrease in malaria incidence over the past decades. Furthermore, history reveals that malaria transmission is unstable and prone to local outbreaks in Hubei Province. Thus, understanding spatial, temporal, and spatiotemporal distribution of malaria is needed for the effective control and elimination of this disease in Hubei Province.

Methods

Annual malaria incidence at the county level was calculated using the malaria cases reported from 2004 to 2011 in Hubei Province. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of malaria cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of malaria cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model.

Results

The overall malaria incidence decreased to a low level from 2004 to 2011. The purely spatial cluster of malaria cases from 2004 to 2011 showed that the disease was not randomly distributed in the study area. A total of 11 high-risk counties were determined through Local Moran’s I analysis from 2004 to 2011. The method of spatial scan statistics identified different 11 significant spatial clusters between 2004 and 2011. The space-time clustering analysis determined that the most likely cluster included 13 counties, and the time frame was from April 2004 to November 2007.

Conclusions

The GIS application and scan statistical technique can provide means to detect spatial, temporal, and spatiotemporal distribution of malaria, as well as to identify malaria high-risk areas. This study could be helpful in prioritizing resource assignment in high-risk areas for future malaria control and elimination.

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

BACKGROUND

Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions.

METHODS

In this study, spatial autocorrelation methodologies, including global Moran's I and local Getis-Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time.

RESULTS

The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran's I > 0, P < 0.01), which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties.

CONCLUSIONS

The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial-temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be continued, especially in the Yangtze River Basin of Jianghan Plain area.

New uses for old drugs: the tale of artemisinin derivatives in the elimination of schistosomiasis japonica in China

Artemisinin (qinghaosu), extracted from the Chinese herb Artemisia annua L. in 1972, and its three major derivatives--artemether, artesunate and dihydroartemisinin--were firstly identified as antimalarials and found active against all species of the malaria parasite. Since the early 1980s, artemisinin and its derivatives have been found efficacious against Schistosoma spp., notably larval parasites, and artemisinin derivatives have played a critical role in the prevention and treatment of human schistosomiasis in China. Currently, China is moving towards the progress of schistosomiasis elimination. However, the potential development of praziquantel resistance may pose a great threat to the progress of elimination of schistosomiasis japonica in China. Fortunately, these three major artemisinin derivatives also exhibit actions against adult parasites, and reduced sensitivity to artemether, artesunate and dihydroartemisinin has been detected in praziquantel-resistant S. japonicum. In this review, we describe the application of artemisinin derivatives in the prevention and treatment of schistosomiasis japonica in China, so as to provide tools for the global agenda of schistosomiasis elimination. In addition to antimalarial and antischistosomal actions, they also show activities against other parasites and multiple cancers. Artemisinin derivatives, as old drugs identified firstly as antimalarials, continue to create new stories.