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Objective: To study the complete sequence of M segment of Amur virus in rodents and to explore their molecular characteristics., Methods: Complete M segment of Amur virus in rodent from China was amplified by RT-PCR. The purified PCR product was cloned into pGEM-T Easy vector and then sequenced. Phylogenetic analysis on multiple nucleotide sequences was performed with the Tree PUZZLE and DNAStar software., Results: The full-length of its M gene comprised of 3615 nucleotides with one open reading frame (ORF) including 3408 nucleotides and encoding a protein which comprised 1135 amino acids. The ORF was located at bases 41 to 3448. The phylogenetic analysis of JilinAP06 with other hantaviruses revealed that the complete sequence of M segment of JilinAP06 strain was closely related to those Amur viruses such as B78 strain, Liu strain and H5 strain were all from the patients. The complete sequence of M segment of JilinAP06 had only 79.5% identities with the nucleotide sequence of HTNV strain 76 - 118., Conclusion: The complete sequence on M segment of Amur virus in rodent was first time identified in this country.

Objective: To analyze the determinants of malaria in Anhui province during the year of 2004-2006., Methods: A GIS-based database of malaria at the township scale of Anhui province was established, using remote sensing and spatial analysis technologies. Methods on statistical analysis, principal component analysis combined with logistic regression analysis were synthetically used to analyze the association between malaria and environmental factors., Results: Malaria epidemics in Anhui province during 2004-2006 mainly occurred in the northern districts of Huai River, and the epidemics had become more serious yearly. The determinants of malaria at the township scale mainly included factors as temperature, rainfall, normalized difference vegetable index and elevation. If the lowest temperature in a year, which appeared the fourth principal component of the temperature index series, increased by one unit, the probability of incidence of malaria would decrease by 33%. If the total annual rainfall, which was ihe first principal component of the rainfall index series, increased by one unit, the probability would decrease by 27%. If the elevation increased by 10 meters, the probability would decrease by 2%. However, he relationship between Normalized Difference Vegetable Index (NDVI) and the probability of incidence of malaria was different. If the NDVI had a one unit increase, the probability would increase 3.28 times., Conclusion: The northern districts of Huai River during 2004-2006 appeared to be a new spatio-temporal cluster when reemergence of malaria epidemics had occurred in Auhui province since 2000. Terrain and physiognomy, nature and circumstances factors, such as temperature and rainfall had affected the incidence rates of malaria. Our research data from Anhui province would provide some important references to the discovery of main reasons on the reemergence of malaria epidemics since 2000, especially in the central geographic areas of China.

Objective: To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics., Methods: Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0., Results: The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST)., Conclusion: Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Objective: To analyze the spatial distribution of highly pathogenic avian influenza (HPAI) and to explore environmental factors associated with HPAI using geographic information system (GIS) techniques in Mainland China., Methods: Databases were set up using the information of HPAI during epidemics in 2004, and linked to digital maps at provincial and county administrative layers in the country through the ArcGIS 8.3 software. Spatial cluster analyses, spatial statistics analyses and tracking analyses on epidemic situation of HPAI were implemented. Environmental factors associated with HPAI were also analyzed on data related to weather, vegetation and migratory birds etc., Results: Findings from spatial cluster analyses showed that high incidence area was centralized in 113.261 degrees ordm; east longitude and 23. 119 degrees ordm; north latitude with a radius of 1090.52 kilometers (relative risk= 2.646, P value= 0.001). Spatial statistical analyses showed that HPAI took place mainly in capital cities of provinces and surrounding areas as well as in the circumference areas of arterial rivers, lakes and seacoasts. Results also showed that HPAI occurrences were associated with low air temperature, high relative humidity and high air pressure as well as with east & central migration routes of migratory birds. The average normalized difference vegetation index was 0.36 +/- 0.11 in epidemic areas of HPAI., Conclusion: HPAI was unrandomly distributed and geographically clustered in China.

Objective: To analyze the association between types of epidemic areas and proportion of main animal hosts of hemorrhagic fever with renal syndrome (HFRS) in China., Methods: Data on serotype of HFRS patients from 122 regions and species as well as number of animal hosts from 41 national surveillance sites were collected and managed. The map of the types of epidemic areas from 1991-1999 in China was produced using inverse distance weighted technique in the ArcGIS 8.1 software. The map of the proportion of host animals was then overlapped on it and the surveillance sites of HFRS were clustered in terms of the proportion of host animals., Results: Variance in spatial distribution of the types of epidemic areas was observed. Two epidemic area types, namely Hantaan-dominant mixed epidemic areas and Soul-dominant mixed epidemic areas seemed to have transferred from the north-east to south-west of China in turns. There were more species of HFRS animal hosts in fields than those of in residential areas. The diversity of rodent species in fields was higher than that of the residential areas which predominant harbored rodent species of 2-3 kinds. Types of surveillance sites classified by cluster analysis of proportion of main animal hosts were consistent with the serotypes of HFRS patients., Conclusion: Through employment of spatial analysis technique based on GIS databases, the HFRS types of main epidemic area in China could be well predicted by surveillance data.

Objective: To study the factors in relation to severe acute respiratory syndromes (SARS) among health care workers and to develop related protective measures., Methods: Case-control study was applied. A standardized questionnaire was used to collect SARS related information for health care workers who had contacted or treated SARS patients. Univariate analysis was conducted using SPSS 10.0 software package and multivariate logistic regression analysis was conducted using SAS 6.12., Results: Twenty-seven of the 49 factors under study were significantly associated with SARS infection, in which 22 factors were protective, and the other 5 were risk factors. 27 factors were included for multivariate logistic regression analysis. Results showed that six factors as wearing eye glasses, wearing protection gowns, exposure to secrets/mode of contact with SARS patients, types of mask and the working years atc, remained significant association with hospital infection of SARS., Conclusion: SARS infection in heath care workers was related to many factors during the process of diagnoses and/or treatment. It is recommended that adequate masks, eye-protection and protective gowns should be adopted for heath care workers during the process of clinical diagnoses and treatment of SARS patients.

Objectives: To study the correlation between positive rates of RNA in clinical confirmed severe acute respiratory syndrome (SARS) patients and its appearance in relation to the development of the disease in order to provide scientific basis for early diagnosis, effective prevention and treatment of the disease., Methods: One-step reverse transcription-polymerase chain reaction (RT-PCR) was used to amplify the SARS RNA in the clinical specimens from different courses of the disease. The representative amplicons were then sequenced. Chi-square for trend test was performed to study the correlation between positive rates of RT-PCR and at different periods after the onset of the disease., Results: The fragments amplified from the sputum specimens of SARS patients were shown to share 100% homology with the published SARS-associated coronavirus. Of the different clinical specimens, positive rate in the stools appeared to be the highest (21.55%). Chi-square for trend test revealed that the positive rates of stools and sputa of SARS patients decreased with the development of the disease (chi(2) for trend = 12.55 and 16.408, P = 0.0004 and P = 0.000 05 respectively)., Conclusion: One-step RT-PCR proved to be an effective method for the detection of SARS-associated coronavirus from clinical specimens. Data as indicated that the positive rates of SARS coronavirus were decreasing in SARS patients along with the disease progression.

Objective: To analyze the spatial distribution of hemorrhagic fever with renal syndrome (HFRS) in Haidian district, Beijing and to explore the geographical characteristics of HFRS in highly endemic areas., Methods: Administration boundary layer was established under the background of 1:100,000 map in the ArcInfo 8.1 software. The HFRS cases from 1997 to 2002 were positioned on the map. Highly endemic areas were identified by spatial cluster analysis using SaTScan 3.0 software. Distribution of HFRS cases was shown in different colors and contours by spatial analysis of geographic information system (GIS)., Results: Spatial Cluster Analysis of confirmed cases of HFRS identified in 1997 - 2002 in Haidian district showed that HFRS patients were not randomly distributed. The highly endemic areas were founded in Sujiatuo township, Yongfeng township, Shangzhuang township, Wenquan town and Bei'anhe township (relative risk = 4.43, P = 0.001). A thematic map of HFRS in haidian district was set up., Conclusion: HFRS infections were not randomly distributed, since the distribution was related to geographic-environmental factors.

Objective: To explore the temporal profile of serum antibody against coronavirus in patients with severe acute respiratory syndrome (SARS), and to evaluate the reliability of indirect immuno-fluorescence assay (IFA) in the diagnosis of SARS., Methods: Clinically confirmed SARS patients, suspected SARS patients, and controls were included in the study. IFA was used to detect the serum antibody against SARS coronavirus. General information about the subjects was collected using a standard questionnaire., Results: The positive rates of specific IgG and IgM against SARS virus within 10 days after onset of the disease were 55.1% and 16.3% respectively and then increased up to 89.8% for IgG and 65.3% for IgM. After 25 days of the onset of the disease, 90.9% patients became positive for both IgG and IgM. Results from chi-square for trend test revealed that the positive rates of both IgG and IgM increased with time (chi(2) for trend = 16.376, P = 0.00005 for IgG; chi(2) for trend = 28.736, P = 0.00000 for IgM). Sensitivity, specificity and agreement value of IFA regarding the diagnosis of SARS were all higher than 90%., Conclusion: IFA can be used to assist diagnosis of SARS after 10 days of the onset of disease.

Objective: To analyze the spatial distribution of hemorrhagic fever with renal syndrome (HFRS) in China by geographic information system, and to draw up a map on HRFS risk areas., Methods: A set of database was set up using the information collected and linked to electronic maps of China in a software ArcGIS 8.01 from 41 HFRS surveillance sites during 1995 - 1998. A HFRS spatial distribution model was developed using inverse distance weighted interpolation of ArcGIS's spatial analysis method. The normalized difference vegetation index (NDVI) in each HFRS surveillance site was extracted from SPOT4 satellite vegetation imagery. Correlation analysis was performed through SPSS 10.0 to analyze the association between NDVI and HFRS incidence, HFRS risk areas were mapped under different colors., Results: Spatial distribution model from HFRS surveillance sites showed that HFRS foci mainly presented in the Heilongjiang River drainage, the middle and lower reaches of the Yellow River, the middle and lower reaches of the Yangtze River, and the Jinghang grant Canal-Huaihe River drainage. It was consistent with HFRS distribution map derived from national infectious disease reporting system. Correlation analysis indicated that HFRS incidence rates were significantly associated with NDVI (r = 0.417, P < 0.01). The HFRS risk areas was mapped according to NDVI of each surveillance site., Conclusion: It is promising to apply GIS technology in predication of the distribution of HFRS by establishing this prediction model.