[Study on patients with Creutzfeldt-Jakob disease in Shanghai, 2006-2012].

OBJECTIVE: To describe the epidemiological characteristics of patients with Creutzfeldt-Jakob disease (CJD) in Shanghai from 2006 to 2012. METHODS: Clinical and epidemiological information on CJD patients from Shanghai CJD Surveillance Network was analyzed. Cerebral spinal fluid (CSF)and blood specimens from patients were collected and used for detecting the 14-3-3 protein, and polymorphism of 129 amino acid and mutation of PRNP genes. Data was processed by EpiData(V3.0)and analyzed by SPSS(V17.0). RESULTS: In totally, one definite CJD patient together with 56 probable and 17 possible sporadic CJD patients were identified. One E200K genetic CJD case was diagnosed and another one was clinically diagnosed. No period- or geographic-related events were observed for these cases, but the houses of the two genetic CJD cases were close to each other. The mean age of onset of the probable CJD patients was 62 years old which was significantly older than that of those possible CJD patients. CONCLUSION: Most of the CJD patients identified in Shanghai were sporadic and the number was stable from 2006 to 2012. The mean age of onset of those probable CJD patients was older than that of the possible CJD patients.

[Prediction of influenza-like illness in Shanghai based on the generalized additive method].

The aim of the current research topic was to test the generalized additive method (GAM), using data from the analysis and prediction on influenza-like illness (ILI) in Shanghai. Through collecting the meteorological data as well as the ILI from 2006 to 2010, we established several nonlinear regression candidate models based on the GAM. These models considered factors as: the nonlinear dependence on the meteorological data, i.e. weekly average temperature and weekly average (maximum) temperature differences and the ILI. The AIC (Akaike information criterion) involved two simplified models which were implemented for further analysis and prediction. Finally, numerical examples showed that the proposed models could shed light on the connection between the meteorological data and the ILI. GAM could be used to fit the frequencies of ILI and meteorological factors in Shanghai. The proposed models were able to accurately analyze the onset of ILI, implying that GAM might be suitable for the prediction and analysis of those meteorological correlative diseases.