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The Establishment of Integrated Model of Schistosomiasis Japonica Based on Landscape Pattern Analysis and Bayesian Modeling

Author: YangKun
Tutor: ZhouXiaoNong
School: Disease Control and Prevention Center
Course: Epidemiology and Biostatistics,
Keywords: Landscape Pattern Bayesian model Schistosomiasis japonica Snails Spatial and temporal distribution Scale Geographic Information Systems Remote sensing
CLC: R184
Type: PhD thesis
Year: 2008
Downloads: 262
Quote: 1
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Abstract

With the change of climate warming, returning farmland, human migration activities ecological environmental factors, snails their geographic environment, biomes, population density and its distribution area and so the changes. Schistosomiasis occurrence, development and trends change, the scientific model to predict the development trend of schistosomiasis is an important one in the Disease Control and Prevention. In this study, the geographic information system (GIS) and remote sensing (RS) technology support to major natural environmental factors (water, vegetation, temperature, etc.), landscape factors (land use, land type, etc.), and social factors as indicators in endemic areas were constructed based on snails and schistosomiasis distribution landscape pattern and Bayesian model composite model, clarify and predict the same environment at different scales, different type of environment in the same scale of snails and schistosomiasis distribution and temporal variations of as schistosomiasis monitoring and control strategies to provide a reference. First use of a GPS device in Yunnan Eryuan County records ditches shape the spatial location of the village boundary, and collect the 2000-2006 investigation Lo, the use of remote sensing images extracted vegetation index (NDVI), humidity (Wetness), surface temperature (LST) and land use / type of information, further extraction of landscape indices. Village Scale build the snail distribution of non-space-time and space-time Bayesian composite model point data Bayes composite model to predict the distribution of snail snail distribution data for 2006 and SPOT5 remote sensing images to build a smaller scale (snail Environment). Display a hilly snail distribution in the village level, no significant sexual temporal and spatial correlation; small scale snail distribution some space. Snail density and NDVI, humidity, ditches slope in the village level was some correlation. Small scale snail density above factors without significant with correlation, while the landscape index of the MSI (Mean shape index, the average shape indicators) and SEI (Shannon'sevenness index, Shannon uniformity indicators) was significant with positive correlation, infectious snails density the neighborhoods area ratio is positively correlated. Heterogeneity prompted to change the landscape of the endemic areas can play a role in reducing snail density; hilly snails with schistosomiasis Distribution of appropriate small-scale studies using high-resolution remote sensing images. Secondly, we have carried out in the Eryuan County schistosomiasis in Yunnan popular village household survey, to carry out the schistosomiasis checks (simple serological examination, simple pathogenic examination and blood tests positive pathogenic examination) ≥ 5-year-old resident of age, of blood tests positive rate and infection rate, to build Bayesian multi-level model (individual, household level and village-level). The results show that the rate and infection rate of the crowd blood tests positive spatial correlation occurs mainly in village-level internal, the crowd blood tests positive rate of different age group and gender, and the infection rate was no significant difference. Village level, the crowd blood tests positive rate and Landscape index SEI and LPI (Largest patches index, plaque index) was positively correlated with average density around the village of snails; schistosome infection risk factors. The level of the household level, the the the crowd blood tests positive risk factors for more shuiyang area, no digesters; the schistosome infection risk factors for family health livestock pens. Prompted the region to control schistosomiasis infection measures for the transformation of livestock pens with snail density reduce popular around the village. Third, we take advantage of Hunan Hanshou County 1995-2006 investigation the snail data and the corresponding Year of remote sensing images extracted NDVI Wetness, LST and landscape indices, build snail distribution in the composite Bayesian model for snail distribution forecast. Results show that the snails with infectious snails distribution showed a significant negative correlation; space the inside embankment snails distribution correlation with the distance increase and reduce the speed significantly faster on the embankment outside the snails; within the embankment of snail density and NDVI was negatively correlated within the embankment snails The density and Landscape index the SEI and LPl respectively showed a positive correlation and negative correlation. Annual embankment outside the snails and infectious snails distribution of space structure basically similar, varied greatly; embankment outside the snails and NDVI was positively correlated, embankment outside of snail density, respectively, with the LST and Wetness was negative related and positively correlated; embankment outside infection of snail density and landscape Index MSI, SDI (Shannon's diversity index, Shannon diversity index) was positively correlated, negatively correlated with the SEI, LPI and LSI. Returning Land to policy implementation, the snail distribution forecast figure shows Returning Land to implementation, the snail density within the embankment is still at a high level, and its spatial distribution centralized distribution over the embankment outside the snails, snails are mainly distributed in the embankment outside Hanshou County the northwest embankment outside bottomland. Finally, we take advantage of Hunan Hanshou County the schistosomiasis check the disease in 10 years, more than 3 times (3) data, consider checking method sensitivity and specificity of uncertainty based on to build Bayesian composite model. Indicating that the infection rate in the county no significant correlation annually schistosome infection rate spatial correlation structure quite different, showed a significant negative correlation with the NDVI. The forecast figure shows the 2002 infection rate at a low level, the rate of infection is greater than 1% of the area along the main river systems mesh Pinghu and Yuanshui distribution; county average infection rate in 2005 was 2.22%, high-prevalence areas are mainly along the major river systems distribution; similar to the rate of infection by serology alone or pathogenic examination predictive value of the spatial pattern of the prediction error distribution; infection rate forecast the change figure shows Hanshou County Yuanshui most areas south of schistosomiasis infection rate did not change significantly, Yuanshui The area north of schistosomiasis infection rates increased significantly, the prompt single regressive return farmland to the infection rate of schistosomiasis strong double regressive. Comparative analysis of the hilly lake type of snail distribution schistosomiasis Bayesian composite model, you can see the hills and limnology snails and schistosomiasis distribution factors, spatial and temporal patterns, modeling methods, there are differences between , determine the types of schistosomiasis control measures should be different. The limnology endemic areas can take relatively consistent or similar control measures should be taken to human and animal concurrent chemotherapy, livestock in captivity and susceptible areas molluscicidal based comprehensive prevention and control measures, to maximize the control of the disease, long-term monitoring of the level embankment flood discharge District dynamically change to take timely and effective control measures to prevent the spread of the epidemic. In the hills schistosomiasis endemic areas, prevention measures should be adapted to local conditions, implementation of targeted and operable in different range of technical measures, if we insist on the environmental transformation based schistosomiasis comprehensive management, the implementation of key projects molluscicidal the same time, people and livestock should be taken to concurrent chemotherapy, change water and sanitation, health education, livestock captive comprehensive prevention and control measures to minimize the area of ??snails to control schistosomiasis transmission. Suitable scale landscape pattern and Bayesian model-based composite snails and schistosomiasis distribution model, analyze and predict the hills and Limnological snails and schistosomiasis distribution will play an important role to determine the control measures to improve the control effect an important tool.

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