Data-driven exploration of 'spatial pattern-time process-driving forces' associations of SARS epidemic in Beijing, China.

BACKGROUND: Severe Acute Respiratory Syndrome (SARS) was first reported in November 2002 in China, and spreads to about 30 countries over the next few months. While the characteristics of epidemic transmission are individually assessed, there are also important implicit associations between them. METHODS: A novel methodological framework was developed to overcome barriers among separate epidemic statistics and identify distinctive SARS features. Individual statistics were pair-wise linked in terms of their common features, and an integrative epidemic network was formulated. RESULTS: The study of associations between important SARS characteristics considerably enhanced the mainstream epidemic analysis and improved the understanding of the relationships between the observed epidemic determinants. The response of SARS transmission to various epidemic control factors was simulated, target areas were detected, critical time and relevant factors were determined. CONCLUSION: It was shown that by properly accounting for links between different SARS statistics, a data-based analysis can efficiently reveal systematic associations between epidemic determinants. The analysis can predict the temporal trend of the epidemic given its spatial pattern, to estimate spatial exposure given temporal evolution, and to infer the driving forces of SARS transmission given the spatial exposure distribution.

[Analysis on the multi-distribution and the major influencing factors on severe acute respiratory syndrome in Beijing].

OBJECTIVE: To analyse the multi-dimension nature of severe acute respiratory syndrome (SARS) transmission. METHODS: Based on the data of SARS in 2003 and the geographic information system of Beijing, as well as under the broad range of the theorems and techniques of data-driven and model-driven knowledge mining, hierarchical techniques were used to test the hot spots. Wavelet technique was also used to decompose Moran's I frequency to survey the spatial clustering process of SARS. For factors analysis, BW test was used to distinguish factors which influencing SARS process. In temporal aspects, susceptive-infective-removal model (SIR) without Taylor expansion was solved by a genetic-simulated annealing algorithm, that directly provided a new approach to obtain epidemic parameters from the SIR model. RESULTS: Different order of spatial hot spots were noticed and the clustering were relevant with the means of transportation. Diffusion dynamics were changed along with the temporal process of SARS. Regarding factor analysis, geographic relationship, population density, the amount of doctors and hospitals appeared to be the key elements influencing the transmission of SARS. The predictable number of SARS cases evolving with time were also calculated. CONCLUSIONS: Cluster detection of close contacts of SARS infective in Beijing revealed the spatial characters of urban population flow and having important implications in the prevention and control of this communicable diseases. Some human and physical environment factors played statistical significant roles in different periods during SARS epidemics. An efficient algorithm was developed to solve SIR model directly, enabling the estimation of epidemic parameters from SIR and early forecast.

[Study on the animal model for severe acute respiratory syndrome].

To screen small animals susceptible to SARS-CoV, five species of animals, including guinea pig, hamster, albino hamster, chicken and rat, were experimentally infected with SARS-CoV strain BJ-01 by different routes. On the basis of this, further cynomolgus and rhesus macaques were selected and experimentally inoculated SARS-CoV, the quality they serve as animal model for SARS was evaluated. The results showed that, all five species of small animals chosed were not susceptible to SARS-CoV, no characterized changes in clinical sign and histopathology were observed after infection, but from the lung samples of large rat and pig guinea, the genomic RNA of SARS-CoV could be detected by RT-PCR at day 14 post infection, this suggested that SARS-CoV could replicate in these animals. After inoculated with SARS-CoV, all inoculated cynomolgus and rhesus macaques had developed interstitial pneumonia of differing severity. These changes on histopathology were similar to that seen in SARS patients, but the pathological lesions were less severe than that of human. Except interstitial pneumonia, no other characterized pathological changes were observed. This suggested cynomolgus and rhesus macaques were not the ideal animal model for SARS in fact, but they could serve as animal model for SARS when a more ideal animal model is absent.

[The application of indirect immuno-fluorescence assay in the diagnosis of severe acute respiratory syndrome].

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.

[Effects of A3243G point mutation on aminoacylation of human mitochondrial tRNALeu(UUR)].

The wild-type and mutant-type human mitochondrial tRNALeu(UUR) genes were synthesized and transcribed in vitro with T7 RNA polymerase. The kinetic parameters of human mitochondrial leucyl-tRNA synthetase(mtLeuRS) were determined with wild-type and mutant-type human mitochondrial tRNALeu(UUR) respectively. The results show that the value of Km/Kcat of mtLeuRS for the mutant-type tRNALeu(UUR) is 63.9% as compared with the wild-type. Human mitochondrial tRNALeu(UUR) gene A3243G point mutant can remarkably reduce it's aminoacylation activity, suggesting it would be one of the mechanisms that the mutation could produce such clinical phenotypes.