Identifying high-risk regions for schistosomiasis in Guichi, China: a spatial analysis

A comparison of modelling the spatio-temporal pattern of disease: a case study of schistosomiasis japonica in Anhui Province, China

The construction of spatio-temporal models can be either descriptive or dynamic. In this study we aim to evaluate the differences in model fitting between a descriptive model and a dynamic model of the transmission for intestinal schistosomiasis caused by Schistosoma japonicum in Guichi, Anhui Province, China. The parasitological data at the village level from 1991 to 2014 were obtained by cross-sectional surveys. We used the fixed rank kriging (FRK) model, a descriptive model, and the integro-differential equation (IDE) model, a dynamic model, to explore the space-time changes of schistosomiasis japonica. In both models, the average daily precipitation and the normalized difference vegetation index are significantly positively associated with schistosomiasis japonica prevalence, while the distance to water bodies, the hours of daylight and the land surface temperature at daytime were significantly negatively associated. The overall root mean square prediction error of the IDE and FRK models was 0.0035 and 0.0054, respectively, and the correlation reflected by Pearson's correlation coefficient between the predicted and observed values for the IDE model (0.71; p<0.01) was larger than that for the FRK model (0.53; p=0.02). The IDE model fits better in capturing the geographic variation of schistosomiasis japonica. Dynamic spatio-temporal models have the advantage of quantifying the process of disease transmission and may provide more accurate predictions.

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.

Currently Available Monitoring and Surveillance Systems for Taenia spp., Echinococcus spp., Schistosoma spp., and Soil-Transmitted Helminths at the Control/Elimination Stage: A Systematic Review

An increasing global focus on neglected tropical diseases (NTDs) has resulted in the set up of numerous control and elimination activities worldwide. This is partly true for Taenia solium taeniasis/cysticercosis, the most important foodborne parasitic infection. Despite substantial progress, adequate monitoring and surveillance (M&S) are required to sustain a status of control/elimination. This is often lacking, especially for T. solium. Therefore, the objective was to conduct a systematic literature review of the currently available M&S systems at the control/elimination stage of the four top-ranked helminth NTDs. Specifically, Taenia spp., Echinococcus spp., Schistosoma spp., and soil-transmitted helminths (STHs) were considered to determine if there are any similarities between their M&S systems and whether certain approaches can be adopted from each other. The systematic review demonstrated that rigorous M&S systems have been designed for the control/elimination stage of both STHs and schistosomiasis, particularly in China. On the other hand, a concept of M&S for Taenia spp. and Echinococcus spp. has not been fully developed yet, due to a lack of epidemiological data and the fact that many endemic countries are far away from reaching control/elimination. Moreover, accurate diagnostic tools for all four diseases are still imperfect, which complicates proper M&S. Finally, there is an urgent need to develop and harmonize/standardize M&S activities in order to reliably determine and compare the epidemiological situation worldwide.

A Persistent Hotspot of Schistosoma mansoni Infection in a Five-Year Randomized Trial of Praziquantel Preventative Chemotherapy Strategies

Background

Persistent hotspots have been described after mass drug administration (MDA) for the control of schistosomiasis, but they have not been studied during the course of a multiyear MDA program.

Methods

In data from a 5-year study of school-based and village-wide preventive chemotherapy strategies for Schistosoma mansoni, spatial scan statistics were used to find infection hotspots in 3 populations: 5- to 8-year-olds, 9- to 12-year-olds, and adults. Negative binomial regression was used to analyze changes from baseline, and receiver operating characteristic analyses were used to predict which villages would reach prevalence and intensity endpoints.

Results

We identified a persistent hotspot, not associated with study arm, where S. mansoni infection prevalence and intensity did not decrease as much as in villages outside the hotspot. Significant differences from baseline were realized after 1 year of MDA: we did not identify factors that moderated this relationship. Villages meeting specified endpoints at year 5 were predicted from prior year data with moderately high sensitivity and specificity.

Conclusions

The MDA strategies were less effective at reducing prevalence and intensity in the hotspot compared with other villages. Villages that reached year 5 endpoints could be detected earlier, which may provide the opportunity to amend intervention strategies.

Assessment of the national schistosomiasis control program in a typical region along the Yangtze River, China

Schistosomiasis remains a major public health problem in eastern China, particularly along the Yangtze River Basin. The latest national schistosomiasis control program (NSCP) was implemented in 2005 with the main goal of reducing the rate of infection to less than 5% by 2008 and 1% by 2015. To assess the progress, we applied a Bayesian spatio-temporal model to describe dynamics of schistosomiasis in Guichi, Anhui Province, China, using annual parasitological and environmental data collected within 41 sample villages for the period 2005-2011. Predictive maps of schistosomiasis showed that the disease prevalence remains constant and low. Results of uncertainty analysis, in the form of probability contour maps (PCMs), indicated that the first goal of "infection rate less than 5% by 2008" was fully achieved in the study area. More longitudinal data for schistosomiasis are needed for the assessment of the second goal of "infection rate less than 1% by 2015". Compared with the traditional way of mapping uncertainty (e.g., variance or mean-square error), our PCMs provide more realistic information for schistosomiasis control.

China-Africa and China-Asia Collaboration on Schistosomiasis Control: A SWOT Analysis

Schistosomiasis, a disease caused by a trematode, parasitic worm, is a worldwide public health problem. In spite of great progress with regard to morbidity control, even elimination of this infection in recent decades, there are still challenges to overcome in sub-Saharan Africa and endemic areas in Southeast Asia. Regarded as one of the most successful countries with respect to schistosomiasis control, The People's Republic of China has accumulated considerable experience and learnt important lessons in various local settings that could benefit schistosomiasis control in other endemic countries. Based on an analysis of conceived strengths, weaknesses, opportunities and threats (SWOT) of potential collaborative activities with regard to schistosomiasis in Africa and Asia, this article addresses the importance of collaborative efforts and explores the priorities that would be expected to facilitate the transfer of Chinese experience to low- and middle-income countries in Africa and Asia.

Identifying Spatial Clusters of Schistosomiasis in Anhui Province of China: A Study from the Perspective of Application

With the strategy shifting from morbidity control to transmission interruption, the burden of schistosomiasis in China has been declining over the past decade. However, further controls of the epidemic in the lake and marshland regions remain a challenge. Prevalence data at county level were obtained from the provincial surveillance system in Anhui during 1997–2010. Spatial autocorrelation analysis and spatial scan statistics were combined to assess the spatial pattern of schistosomiasis. The spatial-temporal cluster analysis based on retrospective space-time scan statistics was further used to detect risk clusters. The Global Moran’s I coefficients were mostly statistically significant during 1997–2004 but not significant during 2005–2010. The clusters detected by two spatial cluster methods occurred in Nanling, Tongling, Qingyang and Wuhu during 1997–2004, and Guichi and Wuhu from 2005 to 2010, respectively. Spatial-temporal cluster analysis revealed 2 main clusters, namely Nanling (1999–2002) and Guichi (2005–2008). The clustering regions were significantly narrowed while the spatial extent became scattered during the study period. The high-risk areas shifted from the low reaches of the Yangtze River to the upper stream, suggesting the focus of schistosomiasis control should be shifted accordingly and priority should be given to the snail habitats within the high-risk areas of schistosomiasis.

Disease mapping for informing targeted health interventions: childhood pneumonia in Bohol, Philippines

BACKGROUND

Acute lower respiratory tract infections (ALRI) are the leading cause of childhood mortality worldwide. Currently, most developing countries assign resources at a district level, and yet District Medical Officers have few tools for directing targeted interventions to high mortality or morbidity areas. Mapping of ALRI at the local level can guide more efficient allocation of resources, coordination of efforts and targeted interventions, which are particularly relevant for health management in resource-scarce settings.

METHODS

An efficacy study of 11-valent pneumococcal vaccine was conducted in six municipalities in the Bohol Province of central Philippines from July 2000 to December 2004. Geocoded under-five pneumonia cases (using WHO classifications) were mapped to create spatial patterns of pneumonia at the local health unit (barangay) level.

RESULTS

There were 2951 children with WHO-defined clinical pneumonia, of whom 1074 were severe or very severely ill, 278 were radiographic, and 219 were hypoxaemic. While most children with pneumonia were from urban barangays, there was a disproportionately higher distribution of severe/very severe pneumonia in rural barangays and the most severe hypoxaemic children were concentrated in the northern barangays most distant from the regional hospital.

CONCLUSIONS

Mapping of ALRI at the local administrative health level can be performed relatively simply. If these principles are applied to routinely collected IMCI classification of disease at the district level in developing countries, such efforts can form the basis for directing public health and healthcare delivery efforts in a targeted manner.

Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology

Background

Monitoring spatial disease risk (e.g. identifying risk areas) is of great relevance in public health research, especially in cancer epidemiology. A common strategy uses case-control studies and estimates a spatial relative risk function (sRRF) via kernel density estimation (KDE). This study was set up to evaluate the sRRF estimation methods, comparing fixed with adaptive bandwidth-based KDE, and how they were able to detect ‘risk areas’ with case data from a population-based cancer registry.

Methods

The sRRF were estimated within a defined area, using locational information on incident cancer cases and on a spatial sample of controls, drawn from a high-resolution population grid recognized as underestimating the resident population in urban centers. The spatial extensions of these areas with underestimated resident population were quantified with population reference data and used in this study as ‘true risk areas’. Sensitivity and specificity analyses were conducted by spatial overlay of the ‘true risk areas’ and the significant (α=.05) p-contour lines obtained from the sRRF.

Results

We observed that the fixed bandwidth-based sRRF was distinguished by a conservative behavior in identifying these urban ‘risk areas’, that is, a reduced sensitivity but increased specificity due to oversmoothing as compared to the adaptive risk estimator. In contrast, the latter appeared more competitive through variance stabilization, resulting in a higher sensitivity, while the specificity was equal as compared to the fixed risk estimator. Halving the originally determined bandwidths led to a simultaneous improvement of sensitivity and specificity of the adaptive sRRF, while the specificity was reduced for the fixed estimator.

Conclusion

The fixed risk estimator contrasts with an oversmoothing tendency in urban areas, while overestimating the risk in rural areas. The use of an adaptive bandwidth regime attenuated this pattern, but led in general to a higher false positive rate, because, in our study design, the majority of true risk areas were located in urban areas. However, there is a strong need for further optimizing the bandwidth selection methods, especially for the adaptive sRRF.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-015-0005-9) contains supplementary material, which is available to authorized users.

Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats

The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future.

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

The 10-year (1992-2001) World Bank Loan Project (WBLP) contributed greatly to schistosomiasis control in China. However, the re-emergence of schistosomiasis in recent years challenged the long-term progress of the WBLP strategy. In order to gain insight in the long-term progress of the WBLP, the spatial pattern of the epidemic was investigated in the Yangtze River Valley between 1999-2001 and 2007-2008. Two spatial cluster methods were jointly used to identify spatial clusters of cases. The magnitude and number of clusters varied during 1999-2001. It was found that prevalence of schistosomiasis had been greatly reduced and maintained at a low level during 2007-2008, with little change. Besides, spatial clusters most frequently occurred within 16 counties in the Dongting Lake region and within 5 counties in the Poyang Lake region. These findings precisely pointed out the prior places for future public health planning and resource allocation of schistosomiasis.

Changing patterns of spatial clustering of schistosomiasis in Southwest China between 1999-2001 and 2007-2008: assessing progress toward eradication after the World Bank Loan Project

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999–2001 and again in 2007–2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin’s Local Moran’s I test and Kulldorff’s spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China.

Identification of parasite-host habitats in Anxiang county, Hunan Province, China based on multi-temporal China-Brazil earth resources satellite (CBERS) images

Remote sensing is a promising technique for monitoring the distribution and dynamics of various vector-borne diseases. In this study, we used the multi-temporal CBERS images, obtained free of charge, to predict the habitats of the snail Oncomelania hupensis, the sole intermediate host of schistosomiasis japonica, a snail-borne parasitic disease of considerable public health in China. Areas of suitable snail habitats were identified based on the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI), and the predictive model was tested against sites (snails present or absent) that were surveyed directly for O. hupensis. The model performed well (sensitivity and specificity were 63.64% and 78.09%, respectively), and with further development, we may provide an accurate, inexpensive tool for the broad-scale monitoring and control of schistosomiasis, and other similar vector-borne diseases.

Spatially explicit modeling of schistosomiasis risk in eastern China based on a synthesis of epidemiological, environmental and intermediate host genetic data

Schistosomiasis japonica is a major parasitic disease threatening millions of people in China. Though overall prevalence was greatly reduced during the second half of the past century, continued persistence in some areas and cases of re-emergence in others remain major concerns. As many regions in China are approaching disease elimination, obtaining quantitative data on Schistosoma japonicum parasites is increasingly difficult. This study examines the distribution of schistosomiasis in eastern China, taking advantage of the fact that the single intermediate host serves as a major transmission bottleneck. Epidemiological, population-genetic and high-resolution ecological data are combined to construct a predictive model capable of estimating the probability that schistosomiasis occurs in a target area (“spatially explicit schistosomiasis risk”). Results show that intermediate host genetic parameters are correlated with the distribution of endemic disease areas, and that five explanatory variables—altitude, minimum temperature, annual precipitation, genetic distance, and haplotype diversity—discriminate between endemic and non-endemic zones. Model predictions are correlated with human infection rates observed at the county level. Visualization of the model indicates that the highest risks of disease occur in the Dongting and Poyang lake regions, as expected, as well as in some floodplain areas of the Yangtze River. High risk areas are interconnected, suggesting the complex hydrological interplay of Dongting and Poyang lakes with the Yangtze River may be important for maintaining schistosomiasis in eastern China. Results demonstrate the value of genetic parameters for risk modeling, and particularly for reducing model prediction error. The findings have important consequences both for understanding the determinants of the current distribution of S. japonicum infections, and for designing future schistosomiasis surveillance and control strategies. The results also highlight how genetic information on taxa that constitute bottlenecks to disease transmission can be of value for risk modeling.

Schistosomiasis is considered the second most devastating parasitic disease after malaria. In China, it is transmitted to humans, cattle and other vertebrate hosts by a single intermediate snail host. It has long been suggested that the close co-evolutionary relationship between parasite and intermediate host makes the snail a major transmission bottleneck in the disease life cycle. Here, we use a novel approach to model the disease distribution in eastern China based on a combination of epidemiological, ecological, and genetic information. We found four major high risk areas for schistosomiasis occurrence in the large lakes and flood plain regions of the Yangtze River. These regions are interconnected, suggesting that the disease may be maintained in eastern China in part through the annual flooding of the Yangtze River, which drives snail transport and admixture of genotypes. The novel approach undertaken yielded improved prediction of schistosomiasis disease distribution in eastern China. Thus, it may also be of value for the predictive modeling of other host- or vector-borne diseases.

Spatial pattern of schistosomiasis in Xingzi, Jiangxi Province, China: the effects of environmental factors

Background

The recent rebounds of schistosomiasis in the middle and lower reaches of the Yangtze River pose a challenge to the current control strategies. In this study, identification of potential high risk snail habitats was proposed, as an alternative sustainable control strategy, in Xingzi County, China. Parasitological data from standardized surveys were available for 36,208 locals (aged between 6–65 years) from 42 sample villages across the county and used in combination with environmental data to investigate the spatial pattern of schistosomiasis risks.

Methods

Environmental factors measured at village level were examined as possible risk factors by fitting a logistic regression model to schsitosomiasis risk. The approach of ordinary kriging was then used to predict the prevalence of schistosomiasis over the whole county.

Results

Risk analysis indicated that distance to snail habitat and wetland, rainfall, land surface temperature, hours of daylight, and vegetation are significantly associated with infection and the residual spatial pattern of infection showed no spatial correlation. The predictive map illustrated that high risk regions were located close to Beng Lake, Liaohuachi Lake, and Shixia Lake.

Conclusions

Those significant environmental factors can perfectly explain spatial variation in infection and the high risk snail habitats delineated by the predicted map of schistosomiasis risks will help local decision-makers to develop a more sustainable control strategy.

Identification of high-risk regions for schistosomiasis in the Guichi region of China: an adaptive kernel density estimation-based approach

Identification of high-risk regions of schistosomiasis is important for rational resource allocation and effective control strategies. We conducted the first study to apply the newly developed method of adaptive kernel density estimation (KDE)-based spatial relative risk function (sRRF) to detect the high-risk regions of schistosomiasis in the Guichi region of China and compared it with the fixed KDE-based sRRF. We found that the adaptive KDE-based sRRF had a better ability to depict the heterogeneity of risk regions, but was more sensitive to altering the user-defined smoothing parameters. Specifically, the impact of bandwidths on the estimated risk value and risk significance (P value) was higher for the adaptive KDE-based sRRF, but lower on the estimated risk variation standard error (s.e.) compared with the fixed KDE-based sRRF. Based on this application the adaptive and fixed KDE-based sRRF have their respective advantages and disadvantages and the joint application of the two approaches can warrant the best possible identification of high-risk subregions of diseases.

Spatial patterns of malaria reported deaths in Yunnan Province, China

Malaria has been a heavy social and health burden in the remote and poor areas in southern China. Analyses of malaria epidemic patterns can uncover important features of malaria transmission. This study identified spatial clusters, seasonal patterns, and geographic variations of malaria deaths at a county level in Yunnan, China, during 1991-2010. A discrete Poisson model was used to identify purely spatial clusters of malaria deaths. Logistic regression analysis was performed to detect changes in geographic patterns. The results show that malaria mortality had declined in Yunnan over the study period and the most likely spatial clusters (relative risk [RR] = 23.03-32.06, P < 0.001) of malaria deaths were identified in western Yunnan along the China-Myanmar border. The highest risk of malaria deaths occurred in autumn (RR = 58.91, P < 0.001) and summer (RR = 31.91, P < 0.001). The results suggested that the geographic distribution of malaria deaths was significantly changed with longitude, which indicated there was decreased mortality of malaria in eastern areas over the last two decades, although there was no significant change in latitude during the same period. Public health interventions should target populations in western Yunnan along border areas, especially focusing on floating populations crossing international borders.

Long-term impact of the World Bank Loan Project for schistosomiasis control: a comparison of the spatial distribution of schistosomiasis risk in China

BACKGROUND

The World Bank Loan Project (WBLP) for controlling schistosomiasis in China was implemented during 1992-2001. Its short-term impact has been assessed from non-spatial perspective, but its long-term impact remains unclear and a spatial evaluation has not previously been conducted. Here we compared the spatial distribution of schistosomiasis risk using national datasets in the lake and marshland regions from 1999-2001 and 2007-2008 to evaluate the long-term impact of WBLP strategy on China's schistosomiasis burden.

METHODOLOGY/PRINCIPAL FINDINGS

A hierarchical Poisson regression model was developed in a Bayesian framework with spatially correlated and uncorrelated heterogeneities at the county-level, modeled using a conditional autoregressive prior structure and a spatially unstructured Gaussian distribution, respectively. There were two important findings from this study. The WBLP strategy was found to have a good short-term impact on schistosomiasis control, but its long-term impact was not ideal. It has successfully reduced the morbidity of schistosomiasis to a low level, but can not contribute further to China's schistosomiasis control because of the current low endemic level. A second finding is that the WBLP strategy could not effectively compress the spatial distribution of schistosomiasis risk. To achieve further reductions in schistosomiasis-affected areas, and for sustainable control, focusing on the intermediate host snail should become the next step to interrupt schistosomiasis transmission within the two most affected regions surrounding the Dongting and Poyang Lakes. Furthermore, in the lower reaches of the Yangtze River, the WBLP's morbidity control strategy may need to continue for some time until snails in the upriver provinces have been well controlled.

CONCLUSION

It is difficult to further reduce morbidity due to schistosomiasis using a chemotherapy-based control strategy in the lake and marshland regions of China because of the current low endemic levels of infection. The future control strategy for schistosomiasis should instead focus on a snail-based integrated control strategy to maintain the program achievements and sustainably reduce the burden of schistosomiasis in China.

Nonparametric evaluation of dynamic disease risk: a spatio-temporal kernel approach

Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the "average" spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled "spatio-temporal kernel density estimation (stKDE)" that employs hybrid kernel (i.e., weight) functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also "borrows" information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based) kernel density estimation (trKDE) which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.

Evaluation of mammalian and intermediate host surveillance methods for detecting schistosomiasis reemergence in southwest China

Background

Schistosomiasis has reemerged in China, threatening schistosomiasis elimination efforts. Surveillance methods that can identify locations where schistosomiasis has reemerged are needed to prevent the further spread of infections.

Methods and Principal Findings

We tested humans, cows, water buffalo and the intermediate host snail, Oncomelania hupensis, for Schistosoma japonicum infection, assessed snail densities and extracted regional surveillance records in areas where schistosomiasis reemerged in Sichuan province. We then evaluated the ability of surveillance methods to identify villages where human infections were present. Human infections were detected in 35 of the 53 villages surveyed (infection prevalence: 0 to 43%), including 17 of 28 villages with no prior evidence of reemergence. Bovine infections were detected in 23 villages (infection prevalence: 0 to 65%) and snail infections in one village. Two common surveillance methods, acute schistosomiasis case reports and surveys for S. japonicum-infected snails, grossly underestimated the number of villages where human infections were present (sensitivity 1% and 3%, respectively). Screening bovines for S. japonicum and surveys for the presence of O. hupensis had modest sensitivity (59% and 69% respectively) and specificity (67% and 44%, respectively). Older adults and bovine owners were at elevated risk of infection. Testing only these high-risk human populations yielded sensitivities of 77% and 71%, respectively.

Conclusions

Human and bovine schistosomiasis were widespread in regions where schistosomiasis had reemerged but acute schistosomiasis and S. japonicum-infected snails were rare and, therefore, poor surveillance targets. Until more efficient, sensitive surveillance strategies are developed, direct, targeted parasitological testing of high-risk human populations should be considered to monitor for schistosomiasis reemergence.

Schistosomiasis has reemerged in China in regions where it was previously controlled. As reductions in schistosomiasis, a water-born parasitic infection, prompt consideration of schistosomiasis elimination, surveillance strategies that can signal reemergence and prevent further lapses in control are needed. We examined the distribution of Schistosoma japonicum, the species that causes schistosomiasis in China, in 53 villages. The villages were located in regions of Sichuan province where schistosomiasis reemergence had been documented by public health authorities. We tested three key reservoirs, humans, cows and water buffalo, and freshwater snails for S. japonicum infection in an effort to identify high-risk populations and evaluate their ability to signal reemergence. Human and bovine infections were common, detected in 35 villages and 23 villages, respectively, but infected snails were rare, found in only one village. Two commonly used surveillance methods, hospital reports of acute schistosomiasis and surveys for S. japonicum-infected snails, grossly underestimated the number of villages where human infections were present. Schistosomiasis was widespread in the region we studied, highlighting the danger reemergence poses to disease elimination programs. Surveillance systems that monitor high-risk populations such as older adults or bovine owners should be considered to promote detection of reemergence.

Identifying high-risk areas of schistosomiasis and associated risk factors in the Poyang Lake region, China

The epidemiology of schistosomiasis japonicum over small areas remains poorly understood, and this is particularly true in China. We aimed to identify high-risk areas for schistosomiasis and associated risk factors in the Poyang Lake region, China. A cross-sectional study was conducted and 60 of 920 persons (6.5%) were found to be infected with Schistosoma japonicum. Locations of households and snail habitats were determined using a hand-held global positioning system. We mapped the data in a geographical information system and used spatial scan statistics to explore clustering of infection, logistic regression and Bayesian geostatistical models to identify risk factors for each individual's infection status and multinomial logistic regression to identify risk factors for living in a cluster area. The risk of schistosomiasis was spatially clustered and higher in fishermen and males, not in persons who lived in close proximity to snail habitats and infected water sources. This study has demonstrated significant spatial variation in the prevalence of schistosomiasis at a small spatial scale. The results suggest that demographic factors (gender, occupation) rather than the distance to infected water are driving human transmission at small-scale spatial levels. Such information can be used to plan locally targeted interventions based on anthelminthic drug administration, snail control and sanitation improvement.

Location of active transmission sites of Schistosoma japonicum in lake and marshland regions in China

Schistosomiasis control in China has, in general, been very successful during the past several decades. However, the rebounding of the epidemic situation in some areas in recent years raises concerns about a sustainable control strategy of which locating active transmission sites (ATS) is a necessary first step. This study presents a systematic approach for locating schistosomiasis ATS by combining the approaches of identifying high risk regions for schisotosmiasis and extracting snail habitats. Environmental, topographical, and human behavioural factors were included in the model. Four significant high-risk regions were detected and 6 ATS were located. We used the normalized difference water index (NDWI) combined with the normalized difference vegetation index (NDVI) to extract snail habitats, and the pointwise 'P-value surface' approach to test statistical significance of predicted disease risk. We found complicated non-linear relationships between predictors and schistosomiasis risk, which might result in serious biases if data were not properly treated. We also found that the associations were related to spatial scales, indicating that a well-designed series of studies were needed to relate the disease risk with predictors across various study scales. Our approach provides a useful tool, especially in the field of vector-borne or environment-related diseases.

Nonparametric spatial analysis to detect high-risk regions for schistosomiasis in Guichi, China

Schistosomiasis control in China is facing a new challenge due to the rebound of epidemics in many areas and the unsustainable effects of the chemotherapy-based control strategy. Identifying high-risk regions for schistosomiasis is an important first step for an effective and sustainable strategy. Direct surveillance of snail habitats to detect high-risk regions is costly and no longer a desirable approach, while indirect monitoring of acute schistosomiasis may be a satisfactory alternative. To identify high-risk regions for schistosomiasis, we jointly used multiplicative and additive models with the kernel smoothing technique as the main approach to estimate the relative risk (RR) and excess risk (ER) surfaces by analyzing surveillance data for acute schistosomiasis. The feasibility of detecting high-risk regions for schistosomiasis through nonparametric spatial analysis was explored and confirmed in this study, and two significant high-risk regions were identified. The results provide useful hints for improving the national surveillance network for acute schistosomiasis and possible approaches to utilizing surveillance data more efficiently. In addition, the commonly used epidemiological indices, RR and ER, are examined and emphasized from the spatial point of view, which will be helpful for exploring many other epidemiological indices.