RESUMEN
OBJECTIVE: To explore the spatial pattern of the distribution of Oncomelania hupensis population in marshland and lake region. METHODS: Four bottomlands were selected randomly for the investigation along the Qiupu River in Guichi District, Anhui Province. The quadrats were placed randomly for snail survey, and the mean crowding, mean density, aggregation indices (diffusion coefficient (C), morisita index (Idelta), index of patchiness (m*/m) ), Taylor's power law and Iwao's m*-m regression index were analyzed. RESULTS: For 4 bottomlands in different time, the diffusion coefficients, Morisita indices, and m*/m indices were all more than one. There was a close linear relationship between the logarithm of the snail density and its variance (P < 0.01), and the correlation coefficient was 0.972. In Taylor's power law, the lg a was 0.602 and b was 1.427. There was a close linear relationship between the mean crowding (m*) and the snail density (m) (P < 0.01), and the correlation coefficient, alpha and beta was 0.984, 2.367 and 1.617 respectively. CONCLUSION: The spatial pattern of Oncomelania hupensis population shows an aggregation distribution in marshland and lake region, and the basic components of snail distribution are in colonies.
Asunto(s)
Ecosistema , Caracoles/crecimiento & desarrollo , Animales , China , Monitoreo del Ambiente , Agua Dulce/parasitología , Densidad de Población , Dinámica Poblacional , HumedalesRESUMEN
Acute schistosomiasis cases from 2001 to 2006 in Guichi District, Chizhou City, Anhui Province, were collected and analyzed by scan statistic method with moving window, central degree approach and circular distribution method in order to detect the temporal clustering of schistosomiasis. The analyzed data provided by the method showed that the temporal clustering of acute schistosomiasis from 2001 to 2003 in Guichi District became more concentrative, and then disperse, resulting in a final disappearance of the clustering in 2006 (LLR = 4.14, P > 0.05). The temporal clustering for all cases in the six years detected by scan statistic method was between August to September in 2002 (LLR = 18.5, P < 0.01), which was consistent with the real condition. Whereas the results from the central degree and the circular distribution methods could only provide limited information and were biased in the analysis in 2002, indicating that the scan statistic method with moving window can provide ample information with more robust and credible results.