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Objective Based on data related to arsenic contents in paddy rice,as part of the food safety monitoring programs in 2017,to discuss and explore the application of spatial analysis used for food safety risk assessment.Methods One province was chosen to study the spatial visualization,spatial point model estimation,and kernel density estimation.Moran's I statistic of spatial autocorrelation methods was used to analyze the spatial distribution at the county level.Results Data concerning the spatial point model estimation showed that the spatial distribution of pollution appeared relatively dispersive.From the kernel density estimation,we found that the hot spots of pollution were mainly located in the central and eastern regions.The global Moran's I values appeared as 0.11 which presented low spatial aggregation to the rice arsenic contamination and with statistically significant differences.One "high-high" and two typical "low-low" clustering were seen in this study.Conclusion Results from our study provided good visual demonstration,identification of pollution distribution rules,hot spots and aggregation areas for research on the distribution of food pollutants.Spatial statistics can provide technical support for the implementation of issue-based monitoring programs.
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Objective Based on data related to arsenic contents in paddy rice,as part of the food safety monitoring programs in 2017,to discuss and explore the application of spatial analysis used for food safety risk assessment.Methods One province was chosen to study the spatial visualization,spatial point model estimation,and kernel density estimation.Moran's I statistic of spatial autocorrelation methods was used to analyze the spatial distribution at the county level.Results Data concerning the spatial point model estimation showed that the spatial distribution of pollution appeared relatively dispersive.From the kernel density estimation,we found that the hot spots of pollution were mainly located in the central and eastern regions.The global Moran's I values appeared as 0.11 which presented low spatial aggregation to the rice arsenic contamination and with statistically significant differences.One "high-high" and two typical "low-low" clustering were seen in this study.Conclusion Results from our study provided good visual demonstration,identification of pollution distribution rules,hot spots and aggregation areas for research on the distribution of food pollutants.Spatial statistics can provide technical support for the implementation of issue-based monitoring programs.
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Objective To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources.Methods The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected.Downscaling interpolation was conducted by using area-to-area Poisson Kriging method.The interpolation results were visualized by using geographic information system (GIS).The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township.Results In the downscaling interpolation,the range of the fitting semi-variance equation was 20.38 km.Within the range,the incidence had correlation with each other.The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y=1.053 1x,R2=0.99.The incidences at different scale were consistent.Conclusions The incidence of HFMD had spatial autocorrelation within 20.38 km.When HFMD occurs in one place,it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km.Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.
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Objective To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources.Methods The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected.Downscaling interpolation was conducted by using area-to-area Poisson Kriging method.The interpolation results were visualized by using geographic information system (GIS).The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township.Results In the downscaling interpolation,the range of the fitting semi-variance equation was 20.38 km.Within the range,the incidence had correlation with each other.The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y=1.053 1x,R2=0.99.The incidences at different scale were consistent.Conclusions The incidence of HFMD had spatial autocorrelation within 20.38 km.When HFMD occurs in one place,it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km.Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.
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Objective The purpose of this study was to analyze the distribution,temporal and spatial clustering characteristics and changes of severe hand,foot,and mouth disease (HFMD) in order to provide evidence-based decision making strategy for control and prevention of severe HFMD cases.Methods Severe HFMD cares were extracted from the National Diseases Reporting System of Chinese Center for Disease Control and Prevention (CDC) between 2008 and 2013.Definition and clinical diagnostic criteria of severe HFMD cases were set up by China CDC in the Hand,Foot,and Mouth Disease Control and Prevention Guideline,version 2010.Spatial scan unit was under the district/county of 2 900 in mainland China with temporal scan unit as month and time span as from May 2008 to August 2013.Kulldorff scan statistics was applied and analyses were conducted by SaTScanTM 9.1.Mapping and visualizing the results were carried out with ArcGIS 10.0.Results Data related to the monitoring program on severe HFMD from 2008 to 2013 demonstrated that above 96％ of the severe HFMD cases occurred under 5 years old,mostly males,with the ratio of males to females as 1.73-1.80 and over 84％ of the children were ‘scattered'.Results from SaTScan illustrated that the temporal and spatial clustering existed among severe HFMD cases.The temporal dimension of severe HFMD was from May to July each year.Spatial dimension was located in south-east coastal area and middle-east area.With respect to the changes of temporal and spatial clustering phenomena,Class 1 clustering area was located in south-east coastal region in 2008 and in middle-east region in 2009 and was shifting to the west from middle-east region in 2010.It moved to the north-east from middle-east region in 2011 and to the north-west and south-west from middle-east region in 2012.Class 1 clustering area covered districts/countries from 18 provinces in 2012.The same pattem of Class 1 clustering area was observed as in the previous year-2013,but with less districts/countries from the 13 provinces.Conclusion Temporal and spatial clustering areas of severe HFMD were presented in this report,and the yearly changing pattern of the clustering areas was noted.Findings from this study provided evidence-based data to the decision-making authorities so as to prevent deaths from severe HFMD cases under reasonable prevention and control strategies.
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The history of life sciences has displayed that Interdisciplinary contributes to the development of life sciences.It also causes people to think dialectically,what is regarded as the development of Interdisciplinary,what is its drive causes,what is the rule of its development.By exploring the developing trend of scientific and interdisciplinary science,we have fully discussed how to train the Cross-talents.