Effects of a closed-loop system against SARS-CoV-2 at the Beijing 2022 Olympic Winter Games: a descriptive and modeling study.

BACKGROUND: To assess the efficacy of the epidemic prevention measures of the "closed-loop" system adopted by the Beijing 2022 Olympic Winter Games (BOWG). METHODS: We retrospectively collected and analyzed information, including age, sex, nationality, vaccination status, date of diagnosis, and date of entry, from 280 SARS-CoV-2-positive individuals identified during the BOWG. A susceptibility-exposed-infectious-remove model was employed to evaluate the effectiveness of epidemic prevention strategies on controlling the spread of SARS-CoV-2 under different scenarios during the BOWG. RESULTS: Regarding SARS-CoV-2-positive cases, 97.9% were imported, and 96.4% were asymptomatic. The median age was 37 years (range: 29-47 years), and 73.9% were male, with the majority of cases being broadcasters and European attendees. Regarding vaccination status, 93.5% were fully vaccinated, and six cases were considered to have been infected in the closed-loop system during the BOWG. Assuming that the BOWG adopted a semi-closed-loop management system, the cumulative number of confirmed cases would be 1,137 for quick quarantine measures (3 d later) implemented and 5,530 for delayed quarantine measures (9 d later) implemented. This modeling revealed that stringent pandemic prevention measures and closed-loop management effectively controlled the spread of SARS-CoV-2 during the BOWG. CONCLUSION: Imported cases are considered the main risk factor for SARS-CoV-2 transmission during mass gatherings, but a comprehensive closed-loop system could minimize transmission among attendees and general personnel.

A Chess and Card Room-Induced COVID-19 Outbreak and Its Agent-Based Simulation in Yangzhou, China.

Objective: To evaluate epidemiological characteristics of the COVID-19 outbreak that resurged in Yangzhou and to simulate the impact of different control measures at different regional scales. Methods: We collected personal information from 570 laboratory-confirmed cases in Yangzhou from 28 July to 26 August 2021, and built a modified susceptible-exposed-infected-removed (SEIR) model and an agent-based model. Results: The SEIR model showed that for passengers from medium-high risk areas, pre-travel nucleic acid testing within 3 days could limit the total number of infected people in Yangzhou to 50; among elderly persons, a 60% increase in vaccination rates could reduce the estimated infections by 253. The agent-based model showed that when the population density of the chess and card room dropped by 40%, the number of infected people would decrease by 54 within 7 days. A ventilation increase in the chess and card room from 25 to 50% could reduce the total number of infections by 33 within 7 days; increasing the ventilation from 25 to 75% could reduce the total number of infections by 63 within 7 days. Conclusions: The SEIR model and agent-based model were used to simulate the impact of different control measures at different regional scales successfully. It is possible to provide references for epidemic prevention and control work.

The Analysis of Patterns of Two COVID-19 Outbreak Clusters in China.

Since the emergence of COVID-19, there have been many local outbreaks with foci at shopping malls in China. We compared and analyzed the epidemiological and spatiotemporal characteristics of local COVID-19 outbreaks in two commercial locations, a department store building (DSB) in Baodi District, Tianjin, and the Xinfadi wholesale market (XFD) in Fengtai District, Beijing. The spread of the infection at different times was analyzed by the standard deviation elliptical method. The spatial transfer mode demonstrated that outbreaks started at the center of each commercial location and spread to the periphery. The number of cases and the distance from the central outbreak showed an inverse proportional logarithmic function shape. Most cases were distributed within a 10 km radius; infected individuals who lived far from the outbreak center were mainly infected by close-contact transmission at home or in the workplace. There was no efficient and rapid detection method at the time of the DSB outbreak; the main preventative measure was the timing of COVID-19 precautions. Emergency interventions (closing shopping malls and home isolation) were initiated five days before confirmation of the first case from the shopping center. In contrast, XFD closed after the first confirmed cases appeared, but those infected during this outbreak benefitted from efficient nucleic acid testing. Quick results and isolation of infected individuals were the main methods of epidemic control in this area. The difference in the COVID-19 epidemic patterns between the two shopping malls reflects the progress of Chinese technology in the prevention and control of COVID-19.

Clinical application and improvement of a CNN-based autosegmentation model for clinical target volumes in cervical cancer radiotherapy.

OBJECTIVE: Clinical target volume (CTV) autosegmentation for cervical cancer is desirable for radiation therapy. Data heterogeneity and interobserver variability (IOV) limit the clinical adaptability of such methods. The adaptive method is proposed to improve the adaptability of CNN-based autosegmentation of CTV contours in cervical cancer. METHODS: This study included 400 cervical cancer treatment planning cases with CTV delineated by radiation oncologists from three hospitals. The datasets were divided into five subdatasets (80 cases each). The cases in datasets 1, 2, and 3 were delineated by physicians A, B, and C, respectively. The cases in datasets 4 and 5 were delineated by multiple physicians. Dataset 1 was divided into training (50 cases), validation (10 cases), and testing (20 cases) cohorts, and they were used to construct the pretrained model. Datasets 2-5 were regarded as host datasets to evaluate the accuracy of the pretrained model. In the adaptive process, the pretrained model was fine-tuned to measure improvements by gradually adding more training cases selected from the host datasets. The accuracy of the autosegmentation model on each host dataset was evaluated using the corresponding test cases. The Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD_95) were used to evaluate the accuracy. RESULTS: Before and after adaptive improvements, the average DSC values on the host datasets were 0.818 versus 0.882, 0.763 versus 0.810, 0.727 versus 0.772, and 0.679 versus 0.789, which are improvements of 7.82%, 6.16%, 6.19%, and 16.05%, respectively. The average HD_95 values were 11.143 mm versus 6.853 mm, 22.402 mm versus 14.076 mm, 28.145 mm versus 16.437 mm, and 33.034 mm versus 16.441 mm, which are improvements of 37.94%, 37.17%, 41.60%, and 50.23%, respectively. CONCLUSION: The proposed method improved the adaptability of the CNN-based autosegmentation model when applied to host datasets.

An evaluation of COVID-19 transmission control in Wenzhou using a modified SEIR model.

In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.

Estimating hourly PM2.5 concentrations in Beijing with satellite aerosol optical depth and a random forest approach.

Assessing short-term exposure to PM2.5 requires the concentration distribution at a high spatiotemporal resolution. Abundant researches have derived the daily predictions of fine particles, but estimating hourly PM2.5 is still a challenge restrained by the input data. The recent aerosol optical depth (AOD) product from Himawari-8 provides hourly satellite observations informative to modelling. In this study, we developed separate random forest models with and without AOD and combined the estimates to obtain a full-coverage hourly PM2.5 distribution. 10-fold cross validation R2 ranged from 0.92 to 0.95 and root mean square errors from 14.1 to 16.9 µg/m3, indicating the good model performance. Spatial convolutional layers of PM2.5 measurements and temporal accumulation effects of meteorological features were added into the model. They turned out to be of the most important predictors and improved the performance significantly. Finally, we mapped hourly PM2.5 at a 1-km resolution in Beijing during a pollution episode in 2019 and studied the pollution pattern. The study proposed a method to obtain 24-h full-coverage hourly PM2.5 estimates which are useful for acute exposure assessment in epidemiological researches.

A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer.

PURPOSE: To develop and test a three-dimensional (3D) deep learning model for predicting 3D voxel-wise dose distributions for intensity-modulated radiotherapy (IMRT). METHODS: A total of 122 postoperative rectal cancer cases treated by IMRT were considered in the study, of which 100 cases were randomly selected as the training-validating set and the remaining as the testing set. A 3D deep learning model named 3D U-Res-Net_B was constructed to predict 3D dose distributions. Eight types of 3D matrices from CT images, contoured structures, and beam configurations were fed into the independent input channel, respectively, and the 3D matrix of dose distributions was taken as the output to train the 3D model. The obtained 3D model was used to predict new 3D dose distributions. The predicted accuracy was evaluated in two aspects: (a) The dice similarity coefficients (DSCs) of different isodose volumes, the average dose difference of all voxels within the body, and 3%/5 mm global gamma passing rates of organs at risks (OARs) and planned target volume (PTV) were used to address the spatial correspondence between predicted and clinical delivered 3D dose distributions; (b) The dosimetric index (DI) including homogeneity index, conformity index, V50 , V45 for PTV and OARs between predicted and clinical truth were statistically analyzed with the paired-samples t test. The model was also compared with 3D U-Net and the same architecture model without beam configurations input (named as 3D U-Res-Net_O). RESULTS: The 3D U-Res-Net_B model predicted 3D dose distributions accurately. For the 22 testing cases, the average prediction bias ranged from -1.94% to 1.58%, and the overall mean absolute errors (MAEs) was 3.92 ± 4.16%; there was no statistically significant difference for nearly all DIs. The model had a DSCs value above 0.9 for most isodose volumes, and global 3D gamma passing rates varying from 0.81 to 0.90 for PTV and OARs, clearly outperforming 3D U-Res-Net_O and being slightly superior to 3D U-Net. CONCLUSIONS: This study developed a more general deep learning model by considering beam configurations input and achieved an accurate 3D voxel-wise dose prediction for rectal cancer treated by IMRT, a potentially easier clinical implementation for more comprehensive automatic planning.

Deceleration of Liver Regeneration by Knockdown of Heme Oxygenase-1 is Associated With Impairment of Liver Injury Recovery After Reduced-Size Liver Transplantation in Rats.

AIM: It has been reported that heme oxygenase-1 (HO-1) is upregulated during hepatocyte proliferation. Herein, we used a half-size liver transplantation (HSLT) model to study the impact of HO-1 on liver grafts proliferation. To the best of our knowledge, this is the first time that HO-1 has been characterized as a regulator of liver graft regeneration. MATERIALS AND METHODS: Saline and tin protoporphyrin (SnPP, a HO-1 competitive inhibitor) were separately administered in vehicle and SnPP group before rats HSLT. Plasma samples were collected at 0, 1, 3, and 5 days after HSLT for liver function analysis. Liver tissues were obtained at 0, 1, 3, and 5 days after HSLT for analyses of histologic, apoptosis, and proliferation index by immunohistochemical, enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction, and Western blotting. RESULTS: HO-1 level was upregulated by the treatment of HSLT along with accelerated liver proliferation, which was reversed by SnPP. The reduced regeneration by SnPP lead to higher Suzuki's scores, alanine aminotransferase, and aspartate aminotransferase levels. The interleukin-6 levels, p-Stat3/t-Stat3, c-myc, and c-jun were decreased in the SnPP group than the vehicle group. CONCLUSIONS: Our findings suggest that inhibition of HO-1 mitigates liver regeneration in part by downregulation of an interleukin-6/Stat3 axis. Targeted specific pharmacologic induction of HO-1 may be applicable in clinical practice.

Landscape of emerging and re-emerging infectious diseases in China: impact of ecology, climate, and behavior.

For the past several decades, the infectious disease profile in China has been shifting with rapid developments in social and economic aspects, environment, quality of food, water, housing, and public health infrastructure. Notably, 5 notifiable infectious diseases have been almost eradicated, and the incidence of 18 additional notifiable infectious diseases has been significantly reduced. Unexpectedly, the incidence of over 10 notifiable infectious diseases, including HIV, brucellosis, syphilis, and dengue fever, has been increasing. Nevertheless, frequent infectious disease outbreaks/events have been reported almost every year, and imported infectious diseases have increased since 2015. New pathogens and over 100 new genotypes or serotypes of known pathogens have been identified. Some infectious diseases seem to be exacerbated by various factors, including rapid urbanization, large numbers of migrant workers, changes in climate, ecology, and policies, such as returning farmland to forests. This review summarizes the current experiences and lessons from China in managing emerging and re-emerging infectious diseases, especially the effects of ecology, climate, and behavior, which should have merits in helping other countries to control and prevent infectious diseases.

Detection of Multiple Parallel Transmission Outbreak of Streptococcus suis Human Infection by Use of Genome Epidemiology, China, 2005.

Streptococcus suis sequence type 7 emerged and caused 2 of the largest human infection outbreaks in China in 1998 and 2005. To determine the major risk factors and source of the infections, we analyzed whole genomes of 95 outbreak-associated isolates, identified 160 single nucleotide polymorphisms, and classified them into 6 clades. Molecular clock analysis revealed that clade 1 (responsible for the 1998 outbreak) emerged in October 1997. Clades 2-6 (responsible for the 2005 outbreak) emerged separately during February 2002-August 2004. A total of 41 lineages of S. suis emerged by the end of 2004 and rapidly expanded to 68 genome types through single base mutations when the outbreak occurred in June 2005. We identified 32 identical isolates and classified them into 8 groups, which were distributed in a large geographic area with no transmission link. These findings suggest that persons were infected in parallel in respective geographic sites.

A spatial, social and environmental study of tuberculosis in China using statistical and GIS technology.

Tuberculosis (TB) remains a major public health problem in China, and its incidence shows certain regional disparities. Systematic investigations of the social and environmental factors influencing TB are necessary for the prevention and control of the disease. Data on cases were obtained from the Chinese Center for Disease and Prevention. Social and environmental variables were tabulated to investigate the latent factor structure of the data using exploratory factor analysis (EFA). Partial least square path modeling (PLS-PM) was used to analyze the complex causal relationship and hysteresis effects between the factors and TB prevalence. A geographically weighted regression (GWR) model was used to explore the local association between factors and TB prevalence. EFA and PLS-PM indicated significant associations between TB prevalence and its latent factors. Altitude, longitude, climate, and education burden played an important role; primary industry employment, population density, air quality, and economic level had hysteresis with different lag time; health service and unemployment played a limited role but had limited hysteresis. Additionally, the GWR model showed that each latent factor had different effects on TB prevalence in different areas. It is necessary to formulate regional measures and strategies for TB control and prevention in China according to the local regional effects of specific factors.

Spatial interpolation of fine particulate matter concentrations using the shortest wind-field path distance.

Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.

Spatial-temporal characteristics of epidemic spread in-out flow-Using SARS epidemic in Beijing as a case study.

For better detecting the spatial-temporal change mode of individual susceptible-infected-symptomatic-treated-recovered epidemic progress and the characteristics of information/material flow in the epidemic spread network between regions, the epidemic spread mechanism of virus input and output was explored based on individuals and spatial regions. Three typical spatial information parameters including working unit/address, onset location and reporting unit were selected and SARS epidemic spread in-out flow in Beijing was defined based on the SARS epidemiological investigation data in China from 2002 to 2003 while its epidemiological characteristics were discussed. Furthermore, by the methods of spatial-temporal statistical analysis and network characteristic analysis, spatial-temporal high-risk hotspots and network structure characteristics of Beijing outer in-out flow were explored, and spatial autocorrelation/heterogeneity, spatial-temporal evolutive rules and structure characteristics of the spread network of Beijing inner in-out flow were comprehensively analyzed. The results show that (1) The outer input flow of SARS epidemic in Beijing concentrated on Shanxi and Guangdong provinces, but the outer output flow was disperse and mainly includes several north provinces such as Guangdong and Shandong. And the control measurement should focus on the early and interim progress of SARS breakout. (2) The inner output cases had significant positive autocorrelative characteristics in the whole studied region, and the high-risk population was young and middle-aged people with ages from 20 to 60 and occupations of medicine and civilian labourer. (3) The downtown districts were main high-risk hotspots of SARS epidemic in Beijing, the northwest suburban districts/counties were secondary high-risk hotspots, and northeast suburban areas were relatively safe. (4) The district/county nodes in inner spread network showed small-world characteristics and information/material flow had notable heterogeneity. The suburban Tongzhou and Changping districts were the underlying high-risk regions, and several suburban districts such as Shunyi and Huairou were the relatively low-risk safe regions as they carried out minority information/material flow. The exploration and analysis based on epidemic spread in-out flow help better detect and discover the potential spatial-temporal evolutive rules and characteristics of SARS epidemic, and provide a more effective theoretical basis for emergency/control measurements and decision-making.

Exploring the epidemic transmission network of SARS in-out flow in mainland China.

The changing spatiotemporal patterns of the individual susceptible-infected-symptomatic-treated-recovered epidemic process and the interactions of information/material flows between regions, along with the 2002-2003 Severe Acute Respiratory Syndrome (SARS) epidemiological investigation data in mainland China, including three typical locations of individuals (working unit/home address, onset location and reporting unit), are used to define the in-out flow of the SARS epidemic spread. Moreover, the input/output transmission networks of the SARS epidemic are built according to the definition of in-out flow. The spatiotemporal distribution of the SARS in-out flow, spatial distribution and temporal change of node characteristic parameters, and the structural characteristics of the SARS transmission networks are comprehensively and systematically explored. The results show that (1) Beijing and Guangdong had the highest risk of self-spread and output cases, and prevention/control measures directed toward self-spread cases in Beijing should have focused on the later period of the SARS epidemic; (2) the SARS transmission networks in mainland China had significant clustering characteristics, with two clustering areas of output cases centered in Beijing and Guangdong; (3) Guangdong was the original source of the SARS epidemic, and while the infected cases of most other provinces occurred mainly during the early period, there was no significant spread to the surrounding provinces; in contrast, although the input/output interactions between Beijing and the other provinces countrywide began during the mid-late epidemic period, SARS in Beijing showed a significant capacity for spatial spreading; (4) Guangdong had a significant range of spatial spreading throughout the entire epidemic period, while Beijing and its surrounding provinces formed a separate, significant range of high-risk spreading during the mid-late period; especially in late period, the influence range of Beijing's neighboring provinces, such as Hebei, was even slightly larger than that of Beijing; and (5) the input network had a low-intensity spread capacity and middle-level influence range, while the output network had an extensive high-intensity spread capacity and influence range that covered almost the entire country, and this spread and influence indicated that significant clustering characteristics increased gradually. This analysis of the epidemic in-out flow and its corresponding transmission network helps reveal the potential spatiotemporal characteristics and evolvement mechanism of the SARS epidemic and provides more effective theoretical support for prevention and control measures.

Aspirin-triggered lipoxin A4 attenuates LPS-induced pro-inflammatory responses by inhibiting activation of NF-κB and MAPKs in BV-2 microglial cells.

BACKGROUND: Microglial activation plays an important role in neurodegenerative diseases through production of nitric oxide (NO) and several pro-inflammatory cytokines. Lipoxins (LXs) and aspirin-triggered LXs (ATLs) are considered to act as 'braking signals' in inflammation. In the present study, we investigated the effect of aspirin-triggered LXA4 (ATL) on infiammatory responses induced by lipopolysaccharide (LPS) in murine microglial BV-2 cells. METHODS: BV-2 cells were treated with ATL prior to LPS exposure, and the effects of such treatment production of nitric oxide (NO), inducible nitric oxide synthase (iNOS), interleukin-1ß (IL-1ß) and tumour necrosis factor-α (TNF-α) were analysed by Griess reaction, ELISA, western blotting and quantitative RT-PCR. Moreover, we investigated the effects of ATL on LPS-induced nuclear factor-κB (NF-κB) activation, phosphorylation of mitogen-activated protein kinases (MAPKs) and activator protein-1 (AP-1) activation. RESULTS: ATL inhibited LPS-induced production of NO, IL-1ß and TNF-α in a concentration-dependent manner. mRNA expressions for iNOS, IL-1ß and TNF-α in response to LPS were also decreased by ATL. These effects were inhibited by Boc-2 (a LXA4 receptor antagonist). ATL significantly reduced nuclear translocation of NF-κB p65, degradation of the inhibitor IκB-α, and phosphorylation of extracellular signal-regulated kinase (ERK) and p38 MAPK in BV-2 cells activated with LPS. Furthermore, the DNA binding activity of NF-κB and AP-1 was blocked by ATL. CONCLUSIONS: This study indicates that ATL inhibits NO and pro-inflammatory cytokine production at least in part via NF-κB, ERK, p38 MAPK and AP-1 signaling pathways in LPS-activated microglia. Therefore, ATL may have therapeutic potential for various neurodegenerative diseases.

CD81 inhibits the proliferation of astrocytes by inducing G(0)/G (1) arrest in vitro.

Astrocytes play a major role in the reactive processes in response to neuronal injuries in the brain. Excessive gliosis is detrimental and can contribute to neuronal damage. CD81 (TAPA), a member of the tetraspanin family of proteins, is upregulated by astrocytes after traumatic injury to the rat central nervous system (CNS). To further understand the role of CD81 in the inhibition of astrocytes, we analyzed the effects of a CD81 antibody, on cultured rat astrocytes. The results indicated that the effect worked in a dose-dependent manner with certain dosage range. It, however, reached a dosage equilibrium at a high dosage. Furthermore, anti-CD81 antibody remarkably inhibited the proliferation of astrocytes after incubation with astrocytes for different periods of time and the effect presented a time-dependent fashion. However, anti-CD81 antibody substantially inhibited the proliferation of astrocytes at low density and middle density but slightly inhibited the proliferation of astrocytes at high density, suggesting that the effect was positively correlated with the proliferative ability of astrocytes. Finally, the cell cycle of astrocytes exposured to anti-CD81 antibody was arrested in S phase at the initial stage and at G(0)/G(1) phase over time. These findings indicated that CD81 exert significant inhibitory effect, dose-dependently and time-dependently, on the proliferation of astrocytes and the effect is positively correlated with the proliferative capability of astrocytes.

Transmission of SARS in three Chinese hospitals.

OBJECTIVE: To quantify the transmissibility of severe acute respiratory syndrome (SARS) in hospitals in mainland China and to assess the effectiveness of control measures. METHODS: We report key epidemiological details of three major hospital outbreaks of SARS in mainland China, and estimate the evolution of the effective reproduction number in each of the three hospitals during the course of the outbreaks. RESULTS: The three successive hospital outbreaks infected 41, 99 and 91 people of whom 37%, 60% and 70% were hospital staff. These cases resulted in 33 deaths, five of which occurred in hospital staff. In a multivariate logistic regression, age and whether or not the case was a healthcare worker (HCW) were found to be significant predictors of mortality. The estimated effective reproduction numbers (95% CI) for the three epidemics peaked at 8 (5, 11), 9 (4, 14) and 12 (7, 17). In all three hospitals the epidemics were rapidly controlled, bringing the reproduction number below one within 25, 10 and 5 days respectively. CONCLUSIONS: This work shows that in three major hospital epidemics in Beijing and Tianjin substantially higher rates of transmission were initially observed than those seen in the community. In all three cases the hospital epidemics were rapidly brought under control, with the time to successful control becoming shorter in each successive outbreak.

Geographical spread of SARS in mainland China.

OBJECTIVES: To describe the spatiotemporal diffusion of the severe acute respiratory syndrome (SARS) epidemic in mainland China, and to analyse the spatial pattern of SARS transmission from the Beijing epicentre to its neighbouring areas. METHODS: Probable SARS cases occurring between November 2002 and May 2003 in mainland China were compiled from different sources and geo-coded into a geographical information database based on onset location. Spatial analyses including kernel density estimation, and spatial statistical and tracking analyses were performed to characterise the spatiotemporal distribution of SARS cases based on onset location/date. SARS cases that got infected in Beijing but were reported in three provinces surrounding Beijing were mapped, and logistic regression using a 'case-control' design at the county level was performed to analyse the impact of travel-related risk factors in the diffusion pattern. RESULTS: The SARS epidemic in mainland China spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas in Shanxi Province, Inner Mongolia Autonomic Region, Hebei Province and Tianjin. Counties in the neighbourhood of Beijing that were crossed by a national highway or inter-provincial freeway showed the highest risk of acquiring SARS infections, even after correction for population density and medical staff density. Being intersected by a railway did not significantly associate with risk of SARS. CONCLUSIONS: This study provides the first complete documentation of the spatial and temporal characteristics of the SARS epidemic in mainland China. Our analyses confirmed that SARS had benefited from national highways and inter-provincial freeways for its spread from epicentres to neighbouring areas, whereas trains showed no significant association. This knowledge may be important for the control of re-emerging SARS, or other future emerging human-to-human transmittable infections.

Effect of ciliary neurotrophic factor on activation of astrocytes in vitro.

Objective To observe the activating effect of ciliary neurotrophic factor (CNTF) on astrocyte in vitro. Methods Astrocytes cultured purely from newborn rats. Cerebral cortex was raised in normal and serum deprivation condition with different concentrations (in ng/ml: 0, 2, 20, or 200) of CNTF. After cultured for 24 h, the shape and the cell cycle of astrocytes were examined by immunocytochemistry and flow cytometer, respectively. Results The immunoactivity of glial fibrillary acidic protein (GFAP) and the nuclear size of astrocytes were increased when CNTF was applied, whether cells were cultured in medium with or without serum. CNTF promoted astrocytes to enter the cell cycle in medium with serum, but had no this effect in medium without serum. Conclusion In medium without serum, astrocytes could differentiate into activated state cells with CNTF application, but could not proliferate; in medium with serum, astrocytes could proliferate with aid of CNTF.