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

Influence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year's longitudinal surveillance data: a spatio-temporal modelling study

BACKGROUND

Urbanization greatly affects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases. Schistosomiasis, a common parasitic disease transmitted by the snail Oncomelania hupensis, is mainly found in areas with population aggregations along rivers and lakes where snails live. Previous studies have suggested that factors related to urbanization may influence the infection risk of schistosomiasis, but this association remains unclear. This study aimed to analyse the effect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.

METHODS

County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected. The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the National Polar-Orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The geographically and temporally weighted regression model (GTWR) was used to quantify the influence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled. The regression coefficient of urbanization was tested for significance (α = 0.05), and the influence of urbanization on schistosomiasis infection risk was analysed over time and across space based on significant regression coefficients. Variables studied included climate, soil, vegetation, hydrology and topography.

RESULTS

The mean regression coefficient for urbanization (0.167) is second only to the leached soil area (0.300), which shows that the urbanization is the most important influence factors for schistosomiasis infection risk besides leached soil area. The other important variables are distance to the nearest water source (0.165), mean minimum temperature (0.130), broadleaf forest area (0.105), amount of precipitation (0.073), surface temperature (0.066), soil bulk density (0.037) and grassland area (0.031). The influence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year. During the study period, the significant coefficient of urbanization level increased from - 0.205 to - 0.131.

CONCLUSIONS

The influence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous. The urbanization does reduce the risk of schistosomiasis infection to some extend, but the strength of this influence decreases with increasing urbanization. Additionally, the effect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors. This study provides scientific basis for understanding the influence of urbanization on schistosomiasis, and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.

Impact of the National Wetland Park in the Poyang Lake Area on Oncomelania hupensis, the Intermediate Host of Schistoma japonicum

In this study, we aimed to understand the influence of ecotourism on the distribution of Oncomelania hupensis and to provide a scientific basis for formulating effective snail control methods in tourism development areas. Poyang Lake National Wetland Park was selected as the pilot area, and sampling surveys were conducted based on comprehensive and detailed investigations of all historical and suspected snail environments according to map data to determine the snail distribution and analyze the impact of tourism development. The results showed that from 2011 to 2021, the positive rates of blood tests and fecal tests tended to decrease among residents of the Poyang Lake area. The positive rates of blood tests and fecal tests in livestock also tended to decrease. The average density of O. hupensis snails decreased, and no schistosomes were detected during infection monitoring in Poyang Lake. The local economy rapidly grew after the development of tourism. The development of ecotourism projects in Poyang Lake National Wetland Park increased the transfer frequency of boats, recreational equipment, and people, but it did not increase the risk of schistosomiasis transmission or the spread of O. hupensis snails. Prevention and monitoring only need to be strengthened in low-endemic schistosomiasis areas to effectively promote economic development due to tourism activities without affecting the health of residents.

Spatial cluster analysis of Plasmodium vivax and P. malariae exposure using serological data among Haitian school children sampled between 2014 and 2016

BACKGROUND

Estimation of malaria prevalence in very low transmission settings is difficult by even the most advanced diagnostic tests. Antibodies against malaria antigens provide an indicator of active or past exposure to these parasites. The prominent malaria species within Haiti is Plasmodium falciparum, but P. vivax and P. malariae infections are also known to be endemic.

METHODOLOGY/PRINCIPAL FINDINGS

From 2014-2016, 28,681 Haitian children were enrolled in school-based serosurveys and were asked to provide a blood sample for detection of antibodies against multiple infectious diseases. IgG against the P. falciparum, P. vivax, and P. malariae merozoite surface protein 19kD subunit (MSP119) antigens was detected by a multiplex bead assay (MBA). A subset of samples was also tested for Plasmodium DNA by PCR assays, and for Plasmodium antigens by a multiplex antigen detection assay. Geospatial clustering of high seroprevalence areas for P. vivax and P. malariae antigens was assessed by both Ripley's K-function and Kulldorff's spatial scan statistic. Of 21,719 children enrolled in 680 schools in Haiti who provided samples to assay for IgG against PmMSP119, 278 (1.27%) were seropositive. Of 24,559 children enrolled in 788 schools providing samples for PvMSP119 serology, 113 (0.46%) were seropositive. Two significant clusters of seropositivity were identified throughout the country for P. malariae exposure, and two identified for P. vivax. No samples were found to be positive for Plasmodium DNA or antigens.

CONCLUSIONS/SIGNIFICANCE

From school-based surveys conducted from 2014 to 2016, very few Haitian children had evidence of exposure to P. vivax or P. malariae, with no children testing positive for active infection. Spatial scan statistics identified non-overlapping areas of the country with higher seroprevalence for these two malarias. Serological data provides useful information of exposure to very low endemic malaria species in a population that is unlikely to present to clinics with symptomatic infections.

Schistosoma japonicum-infected sentinel mice: Surveillance and spatial point pattern analysis in Hubei province, China, 2010-2018

OBJECTIVES

Progress in national schistosomiasis control in China has successfully reduced disease transmission in many districts. However, a low transmission rate hinders conventional snail surveys in identifying areas at risk. In this study, Schistosoma japonicum-infected sentinel mice surveillance was conducted to identify high-risk areas of schistosomiasis transmission in Hubei province, China.

METHODS

The risk of schistosomiasis transmission was assessed using sentinel mice monitoring in Hubei province from 2010 to 2018. Field detections were undertaken in June and September, and the sentinel mice were kept for approximately 35 days in a laboratory. They were then dissected to determine whether schistosome infection was present. Ripley's K-function and kernel density estimation were applied to analyze the spatial distribution and positive point pattern of schistosomiasis transmission.

RESULTS

In total, 190 sentinel mice surveillance sites were selected to detect areas of schistosomiasis infection from 2010 to 2018, with 29 (15.26%) sites showing infected mice. Of 4723 dissected mice, 256 adult worms were detected in 112 infected mice. The infection rate was 2.37%, with an average of 2.28 worms detected per infected mouse. Significantly more infected mice were detected in the June samples than in the September samples (χ²=12.11, p<0.01). Ripley's L(d) index analysis showed that, when the distance was ≤34.52km, the sentinel mice infection pattern showed aggregation, with the strongest aggregation occurring at 7.86km. Three hotspots were detected using kernel density estimation: at the junction of Jingzhou District, Gong'an County, and Shashi District in Jingzhou City; in Wuhan City at the border of the Huangpi and Dongxihu Districts, and in the Hannan and Caidian Districts.

CONCLUSION

The results showed that sentinel mice surveillance is useful in identifying high-risk areas, and could provide valuable information for schistosomiasis prevention and control, especially concerning areas along the Yangtze River, such as the Fu-Lun, Dongjing-Tongshun, and Juzhang River basins.

Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis

Schistosomiasis is a snail-borne parasitic disease endemic to the tropics and subtropics, whose distribution depends on snail prevalence as determined by climatic and environmental factors. Here, dynamic spatial and temporal patterns of Oncomelania hupensis distributions were quantified using general statistics, global Moran’s I, and standard deviation ellipses, with Maxent modeling used to predict the distribution of habitat areas suitable for this snail in Gong’an County, a severely affected region of Jianghan Plain, China, based on annual average temperature, humidity of the climate, soil type, normalized difference vegetation index, land use, ditch density, land surface temperature, and digital elevation model variables; each variable’s contribution was tested using the jackknife method. Several key results emerged. First, coverage area of O. hupensis had changed little from 2007 to 2012, with some cities, counties, and districts alternately increasing and decreasing, with ditch and bottomland being the main habitat types. Second, although it showed a weak spatial autocorrelation, changing negligibly, there was a significant east–west gradient in the O. hupensis habitat area. Third, 21.9% of Gong’an County’s area was at high risk of snail presence; and ditch density, temperature, elevation, and wetting index contributed most to their occurrence. Our findings and methods provide valuable and timely insight for the control, monitoring, and management of schistosomiasis in China.

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.

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.

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.

Exploring spatial patterns of cardiovascular disease in Sweden between 2000 and 2010

AIMS

Cardiovascular disease (CVD) is one of the leading causes of mortality and morbidity worldwide, including in Sweden. The main aim of this study was to explore the temporal trends and spatial patterns of CVD in Sweden using spatial autocorrelation analyses.

METHODS

The CVD admission rates between 2000 and 2010 throughout Sweden were entered as the input disease data for the analytic processes performed for the Swedish capital, Stockholm, and also for the whole of Sweden. Age-adjusted admission rates were calculated using a direct standardisation approach for men and women, and temporal trends analysis were performed on the standardised rates. Global Moran's I was used to explore the structure of patterns and Anselin's local Moran's I, together with Kulldorff's scan statistic were applied to explore the geographical patterns of admission rates.

RESULTS

The rates followed a spatially clustered pattern in Sweden with differences occurring between sexes. Accordingly, hot spots were identified in northern Sweden, with higher intensity identified for men, together with clusters in central Sweden. Cold spots were identified in the adjacency of the three major Swedish cities of Stockholm, Gothenburg and Malmö.

CONCLUSIONS

The findings of this study can serve as a basis for distribution of health-care resources, preventive measures and exploration of aetiological factors.

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.