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OBJECTIVE@#To predict the trends for fine-scale spread of Oncomelania hupensis based on supervised machine learning models in Shanghai Municipality, so as to provide insights into precision O. hupensis snail control.@*METHODS@#Based on 2016 O. hupensis snail survey data in Shanghai Municipality and climatic, geographical, vegetation and socioeconomic data relating to O. hupensis snail distribution, seven supervised machine learning models were created to predict the risk of snail spread in Shanghai, including decision tree, random forest, generalized boosted model, support vector machine, naive Bayes, k-nearest neighbor and C5.0. The performance of seven models for predicting snail spread was evaluated with the area under the receiver operating characteristic curve (AUC), F1-score and accuracy, and optimal models were selected to identify the environmental variables affecting snail spread and predict the areas at risk of snail spread in Shanghai Municipality.@*RESULTS@#Seven supervised machine learning models were successfully created to predict the risk of snail spread in Shanghai Municipality, and random forest (AUC = 0.901, F1-score = 0.840, ACC = 0.797) and generalized boosted model (AUC= 0.889, F1-score = 0.869, ACC = 0.835) showed higher predictive performance than other models. Random forest analysis showed that the three most important climatic variables contributing to snail spread in Shanghai included aridity (11.87%), ≥ 0 °C annual accumulated temperature (10.19%), moisture index (10.18%) and average annual precipitation (9.86%), the two most important vegetation variables included the vegetation index of the first quarter (8.30%) and vegetation index of the second quarter (7.69%). Snails were more likely to spread at aridity of < 0.87, ≥ 0 °C annual accumulated temperature of 5 550 to 5 675 °C, moisture index of > 39% and average annual precipitation of > 1 180 mm, and with the vegetation index of the first quarter of > 0.4 and the vegetation index of the first quarter of > 0.6. According to the water resource developments and township administrative maps, the areas at risk of snail spread were mainly predicted in 10 townships/subdistricts, covering the Xipian, Dongpian and Tainan sections of southern Shanghai.@*CONCLUSIONS@#Supervised machine learning models are effective to predict the risk of fine-scale O. hupensis snail spread and identify the environmental determinants relating to snail spread. The areas at risk of O. hupensis snail spread are mainly located in southwestern Songjiang District, northwestern Jinshan District and southeastern Qingpu District of Shanghai Municipality.
Subject(s)
Animals , Bayes Theorem , China/epidemiology , Ecosystem , Gastropoda , Supervised Machine LearningABSTRACT
We aimed to assess the risks of
Subject(s)
Humans , China , Cryptosporidiosis/microbiology , Cryptosporidium/isolation & purification , Giardia/isolation & purification , Giardiasis/microbiology , Risk Assessment , Water Microbiology , Water Supply/statistics & numerical dataABSTRACT
Objective To investigate the epidemiological profiles of echinococcosis cases reported in non-endemic areas of China in the National Notifiable Disease Report System from 2004 to 2016, so as to provide insights into the development of effective surveillance and response measures. Methods The data pertaining to the echinococcosis cases reported in the National Notifiable Disease Report System in 22 non-endemic provinces of China from 2004 to 2016 were collected, and the epidemiological profiles of the reported echinococcosis cases were descriptively analyzed. Results A total of 462 echinococcosis cases were reported in the 22 non-endemic provinces of China from 2004 to 2016, and the number of reported cases increased with time (χ2 = 4.516, P = 0.034). During the 13-year period from 2004 to 2016, the highest number of echinococcosis cases was reported in central and eastern China (56.49%), followed by in northern and northeastern China (30.30%), and the highest number of echinococcosis cases was reported in Henan Province (99 cases). Among the 462 echinococcosis cases reported, there were 234 men and 228 women, and the mean age was (41.42 ± 16.03) years (range, 4 to 86 years), with the highest number of echinococcosis cases reported at ages of 20 to 50 years (63.20%). The highest proportion of occupations was farmers and herdsmen (36.15%), and the greatest source was from echinococcosis-endemic provinces (50.43%); in addition, 97.40% of the echinococcosis cases were reported by hospitals. Conclusions Echinococcosis cases were reported in all 22 non-endemic provinces of China in the National Notifiable Disease Report System from 2004 to 2016, and the number of reported cases appeared an overall tendency for sporadicity and local increase with time. Screening of echinococcosis is recommended among famers and herdsmen at ages of 20 to 50 years from endemic regions by medical institutions in non-endemic regions for timely identification and treatment of echinococcosis cases.
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Objective To investigate the spatiotemporal distribution of Oncomelania hupensis snails and infected snails in the endemic areas of schistosomiasis in Anhui Province. Methods Based on the snail survey data in Anhui Province in 2016, the distribution of snails and infected snails were analyzed, and the spatial distribution of snails and spatial cluster patterns of infected snails were investigated in snail habitats in Anhui Province from 1950 to 2016. Results A total of 22 757 snail habitats and 5 004 infected snail habitats were identified in Anhui Province from 1950 to 2016, which appeared single-peak and double-peak patterns, with an inflection point seen in 1970. There were 141 000 hm2 historically accumulative snail habitats, 88.08% of which were firstly identified from 1950 to 1979, and totally 114 500 hm2 snail habitats were eradicated, 77.17% of which were eradicated from 1970 to 1999. There were 4 830 snail habitats identified until 2016, in which 1 051 were once detected with infected snails. In addition, 78.12% of current snail habitats had been present for over 40 years, and infected snails had been eliminated in 65.75% of the infected snail habitats within 10 years. There was a spatial autocorrelation of the living snail density in current snail habitats in Anhui Province (Moran’s I = 0.196, Z = 139.63, P < 0.001), and local hotspot analysis showed spatial clusters of living snails density in snail habitats, with high-value clusters in south of the Yangtze River and low-value clusters in north of the Yangtze River. The 21 high-value clusters of living snail density with statistical significance were distributed along the Yangtze River basin and its branches. Spatiotemporal scan analysis revealed spatiotemporal clusters of infected snails in 4 current snail habitats. Conclusions The current snail habitats have been present for a long period of time, and snails are difficult to be eliminated by chemical treatment alone, which requires the combination of environment improvements. There are spatial clusters of living snail density in current snail habitats in Anhui Province. The epidemic factors and risk of human and animal infections still remain in some clusters of historical infected snail habitats revealed by spatiotemporal scan analysis, which should be consid- ered as the key target areas for snail control in Anhui Province.
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Objective To explore the spatial-temporal clustering distribution of schistosomiasis transmission risk in Yunnan Province from 2004 to 2015, so as to provide scientific evidence for the future schistosomiasis control and consolidation of the control achievements. Methods All data pertaining to endemic situation of human and bovine schistosomiasis and snail survey at a township level in Yunnan Province from 2004 to 2015 were collected. A descriptive epidemiological method and Joinpoint model were used to describe the changing trends of Schistosoma japonicum infections in humans, bovine and snails, and the hotspots and clusters of schistosomiasis transmission risk were identified using spatial autocorrelation analysis, hotspots analysis and retrospective space-time scan statistic in Yunnan Province from 2004 to 2015. Results The prevalence of S. japonicum infections appeared a continuous decline in humans, bovine and snails in Yunnan Province from 2004 to 2015, and the estimated number of schistosomiasis cases reduced from 43 056 in 2004 to 756 in 2015, with a decline rate of 98.24%. There were no acute cases since 2008 and no infected snails since 2014 in Yunnan Province. There were significant differences in the changing trends of human and bovine S. japonicum infections in Yunnan Province between 2012 and 2015 and between 2013 and 2015, respectively using the Joinpoint model (P < 0.05). In addition, there was a spatial autocorrelation in human S. japonicum infections in Yunnan Province from 2004 to 2013 (P < 0.01), and the hotspots areas for human S. japonicum infections were mainly distributed in some townships from Dali City, Weishan County and Eryuan County. Retrospective spatial-temporal scanning revealed that S. japonicum human, bovine and snail infections were clustered in 23, 15, 4 townships from Dali City, Weishan County, Eryuan County, Nanjian County and Heqing County, respectively, with relative risks of 6.25 to 28.75 (P < 0.01), which was almost consistent with the cluster areas detected by hotspots analysis. Conclusions The endemic situation of schistosomiasis significantly reduced in Yunnan Province from 2004 to 2015; however, there is still a risk of schistosomiasis transmission. The monitoring and control of schistosomiasis should be intensified in the future in Yunnan Province.
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Objective To explore the spatial-temporal clustering distribution of schistosomiasis transmission risk in Yunnan Province from 2004 to 2015, so as to provide scientific evidence for the future schistosomiasis control and consolidation of the control achievements. Methods All data pertaining to endemic situation of human and bovine schistosomiasis and snail survey at a township level in Yunnan Province from 2004 to 2015 were collected. A descriptive epidemiological method and Joinpoint model were used to describe the changing trends of Schistosoma japonicum infections in humans, bovine and snails, and the hotspots and clusters of schistosomiasis transmission risk were identified using spatial autocorrelation analysis, hotspots analysis and retrospective space-time scan statistic in Yunnan Province from 2004 to 2015. Results The prevalence of S. japonicum infections appeared a continuous decline in humans, bovine and snails in Yunnan Province from 2004 to 2015, and the estimated number of schistosomiasis cases reduced from 43 056 in 2004 to 756 in 2015, with a decline rate of 98.24%. There were no acute cases since 2008 and no infected snails since 2014 in Yunnan Province. There were significant differences in the changing trends of human and bovine S. japonicum infections in Yunnan Province between 2012 and 2015 and between 2013 and 2015, respectively using the Joinpoint model (P < 0.05). In addition, there was a spatial autocorrelation in human S. japonicum infections in Yunnan Province from 2004 to 2013 (P < 0.01), and the hotspots areas for human S. japonicum infections were mainly distributed in some townships from Dali City, Weishan County and Eryuan County. Retrospective spatial-temporal scanning revealed that S. japonicum human, bovine and snail infections were clustered in 23, 15, 4 townships from Dali City, Weishan County, Eryuan County, Nanjian County and Heqing County, respectively, with relative risks of 6.25 to 28.75 (P < 0.01), which was almost consistent with the cluster areas detected by hotspots analysis. Conclusions The endemic situation of schistosomiasis significantly reduced in Yunnan Province from 2004 to 2015; however, there is still a risk of schistosomiasis transmission. The monitoring and control of schistosomiasis should be intensified in the future in Yunnan Province.
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Babesiosis is an emerging parasitic disease, distributed globally in Europe, Asia, Africa, North and South America, and Australia, and the United States is still the country with the largest number of babesiosis cases reported. Babesiosis in China is mainly distributed in the northeast, followed by the southwest and other regions. As a new vector-borne infectious disease, babesiosis poses a serious threat to human health, and its research foundation is relatively weak, so it requires more attention and recognition. The research hot spots on babesiosis are screening of diagnostic antigens, and the mechanisms of Babesia and the hosts, co-infections between Babesia and other pathogens. The epidemic distribution, screening of diagnostic antigens, host immune response mechanism and co-infection of babesiosis in our country and abroad are reviewed in this paper.
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The study analyzes the strengths, weaknesses, opportunities and threats (SWOT) of the informatization of parasitic disease prevention and control in China, and puts forward the development strategies, in order to provide the reference for accelerating the informatization of parasitic disease prevention and control.
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Objective To investigate the status of Oncomelania hupensis snails in Anhui Province in 2016, so as to provide the evidence for formulating the 13th Five-Year Plans for Schistosomiasis Control. Methods In 2016, a snail survey was conducted in Anhui Province according to the National Programme of the Oncomelania Snail Survey, covering all snail habitats or historical snail habitats and suspected environments of snail breeding, and the results of the survey were analyzed. Results In 2016, 22 848 environments were surveyed, and no schistosome-infected snails were found. There were 17 927 historical snail habitats in whole province, among which, the environments without changes, changed partly and changed completely accounted for 71.2%, 19.3% and 9.5%, respectively. The area of historical snail habitats was 1.410 billion m2. There were 4 830 environments with snail habitats covering an area of 0.265 billion m2 in 38 counties of 7 cities, including newly emerging area of 1 287.65 hm2 and reemerging area of 1 375.32 hm2. The density of living snails was 0.392 0 snails/0.1 m2, and the rate of frame with living snails was 12.93%. The type of marshland and lake regions, and the type of hilly and mountainous regions accounted for 22.4% and 77.6% of number of snail habitats, and accounted for 86.7% and 13.3% of areas of snail habitats, respectively. Among the different types of vegetation in snail habitats, grass was superior owe to accounting for 82.2% of the number of snail habitats, 57.3% of the area with snail habitats, and the highest density of living snails (0.413 9 snails/0.1 m2). Among the different types of environments in snail habitats, the ditch was superior owe to accounting for 56.8% of the number of snail habitats, the highest density of living snails (0.570 3 snails/0.1m2) and the highest rate of frame with living snails (18.57%), and the beach was superior owe to accounting for 87.8% of the area with snail habitats. In Anhui Province, the first year of snails and schistosome-infected snails being found was 1950 and 1952, respectively, and the latest year of schistosome-infected snails being found was 2012. The map showed that the most environments with snail habitats were distributed along the Yangtze River in Anhui Province. Conclusion For the first time, the investigation has built the database and map of snail spatial distribution, which truly reflect the historic and current status of snail distribution in Anhui Province and can provide the evidence for formulating the 13th Five-Year Plans for Schistosomiasis Control and improving the schistosomiasis prevention and control work in the future.
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The study analyzes the strengths, weaknesses, opportunities and threats (SWOT) of the informatization of parasitic disease prevention and control in China, and puts forward the development strategies, in order to provide the reference for accelerating the informatization of parasitic disease prevention and control.
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Objective To investigate the status of Oncomelania hupensis snails in Anhui Province in 2016, so as to provide the evidence for formulating the 13th Five-Year Plans for Schistosomiasis Control. Methods In 2016, a snail survey was conducted in Anhui Province according to the National Programme of the Oncomelania Snail Survey, covering all snail habitats or historical snail habitats and suspected environments of snail breeding, and the results of the survey were analyzed. Results In 2016, 22 848 environments were surveyed, and no schistosome-infected snails were found. There were 17 927 historical snail habitats in whole province, among which, the environments without changes, changed partly and changed completely accounted for 71.2%, 19.3% and 9.5%, respectively. The area of historical snail habitats was 1.410 billion m2. There were 4 830 environments with snail habitats covering an area of 0.265 billion m2 in 38 counties of 7 cities, including newly emerging area of 1 287.65 hm2 and reemerging area of 1 375.32 hm2. The density of living snails was 0.392 0 snails/0.1 m2, and the rate of frame with living snails was 12.93%. The type of marshland and lake regions, and the type of hilly and mountainous regions accounted for 22.4% and 77.6% of number of snail habitats, and accounted for 86.7% and 13.3% of areas of snail habitats, respectively. Among the different types of vegetation in snail habitats, grass was superior owe to accounting for 82.2% of the number of snail habitats, 57.3% of the area with snail habitats, and the highest density of living snails (0.413 9 snails/0.1 m2). Among the different types of environments in snail habitats, the ditch was superior owe to accounting for 56.8% of the number of snail habitats, the highest density of living snails (0.570 3 snails/0.1m2) and the highest rate of frame with living snails (18.57%), and the beach was superior owe to accounting for 87.8% of the area with snail habitats. In Anhui Province, the first year of snails and schistosome-infected snails being found was 1950 and 1952, respectively, and the latest year of schistosome-infected snails being found was 2012. The map showed that the most environments with snail habitats were distributed along the Yangtze River in Anhui Province. Conclusion For the first time, the investigation has built the database and map of snail spatial distribution, which truly reflect the historic and current status of snail distribution in Anhui Province and can provide the evidence for formulating the 13th Five-Year Plans for Schistosomiasis Control and improving the schistosomiasis prevention and control work in the future.
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Objective To understand the endemic situation and distribution features of schistosomiasis in Xinjian District,Nanchang City,Jiangxi Province from 2009 to 2014,so as to provide a reference for the prevention and control of schistosomia-sis in the future.Methods The endemic data of schistosomiasis in Xinjian District were collected by taking the village as a unit from 2009 to 2014.An endemic database was established,and the SaTScan software was applied to analyze the spatiotemporal aggregation areas of Schistosoma japonicum infection in crowd,Oncomelania hupensis snails and cattle.Results The S.japoni-cum infection rate of crowd was decreased from 0.10％in 2009 to 0.000 68％in 2014.The infection rate of O.hupensis snails was greatly fluctuated from 2009 to 2014,the highest was 1.04％in 2012,but it fell to 0 in 2014.The highest infection rate of cattle was 1.98％in 2012,and it fell to 0 in 2014.The spatial temporal clustering detection showed that three areas of crowd infection were mainly concentrated in 20 villages of Changyi Township,Lianyu Township and Songhu Town;two areas of snail infection were mainly concentrated in five villages of Changyi Township and Nanji Township;one area of cattle infection was mainly con-centrated in three villages of Changyi Township.Conclusions The endemic situation of schistosomiasis presents a declining trend in Xinjian District from 2009 to 2014 as a whole.However,the potential risks of the rebound of the disease still exist,and the six clustering areas of infection are still the key areas for the prevention and control of schistosomiasis in the future.
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A taeniasis/cysticercosis information management system was designed to achieve the dynamic monitoring of the epidemic situation of taeniasis/cysticercosis and improve the intelligence level of disease information management.The system in-cludes three layer structures(application layer,technical core layer,and data storage layer)and designs a datum transmission and remote communication system of traffic information tube in Browser/Server architecture.The system is believed to promote disease datum collection.Additionally,the system may provide the standardized data for convenience of datum analysis.
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Cysticercosis refers to a parasitic infection caused by the larvae of pork tapeworm Taenia solium.It is a parasitic zoonosis and listed by the World Health Organization(WHO)as one of the neglected tropical diseases.Cysticercosis is spread-ing all over the world through globalization and it mainly epidemic in developing countries.In the southwest and minority nation-ality areas of China,as a result of the low level of medical and health care,and the unchangeable diet custom,there are still many cases of cysticercosis,which is manifested as a local high prevalence.Neuroimaging is the preferred method for cysticerco-sis diagnosis,and by using CT and MRI scans it is possible to visualise the infecting cysticerci and assess their number and loca-tion within the central nervous system(CNS).The immunological assay is also required in the diagnosis.At present,the preven-tion and control of cysticercosis is still relatively weak.In this paper,the current status and research progress of cysticercosis are reviewed,and further suggestions on the prevention and control of cysticercosis are put forward.