Spatiotemporal evolution of COVID-19 epidemic in the early phase in China / 中华流行病学杂志

Objective: Based on the geographic information systems, we exploreed the spatiotemporal clustering and the development and evolution of COVID-19 epidemic at prefectural level in China from the time when the epidemic was discovered to the time when the lockdown ended in Wuhan. Methods: The information and data of the confirmed COVID-19 cases from December 8, 2019 to April 8, 2020 were collected from 367 prefectures in China for a spatial autocorrelation analysis with software GeoDa, and software ArcGIS was used to visualize the results. Software SatScan was used for spatiotemporal scanning analysis to visualize the hot-spot areas of the epidemic. Results: The incidence of new cases of COVID-19 had obvious global autocorrelation and the partial autocorrelation results showed that incidence of COVID-19 had different spatial distribution at different times from December 8, 2019 to March 4, 2020. There was no significant difference in global autocorrelation coefficient from March 5, 2020 to April 8, 2020. The statistical analysis of spatiotemporal scanning identified two kinds of spatiotemporal clustering areas, the first class clustering areas included 10 prefectures, mainly distributed in Hubei, from January 13 to February 25, 2020. The secondary class clustering areas included 142 prefectures, mainly distributed in provinces in the north and east of Hubei, from January 23 to February 1, 2020. Conclusions: There was a clear spatiotemporal correlation in the distribution of the outbreaks in the early phase of COVID-19 epidemic (December 8, 2019-March 4, 2020) in China. With the decrease of the case and effective prevention and control measures, the epidemics had no longer significant correlations among areas from March 5 to April 8. The study results showed relationship with time points of start and adjustment of emergency response at different degree in provinces. Furthermore, improving the early detection of new outbreaks and taking timely and effective prevention and control measures played an important role in blocking the transmission.

Predictive value of vascular health indicators on newly cardiovascular events: Preliminary validation of Beijing vascular health stratification system / 北京大学学报(医学版)

OBJECTIVE@#To explore the predictive value of carotid femoral artery pulse wave velocity (CF-PWV), carotid radial artery pulse wave velocity (CR-PWV), cardio-ankle vascular index (CAVI), and ankle brachial index (ABI) on coronary heart disease (CHD) and cerebral infarction (CI), and the preliminary validation of Beijing vascular health stratification (BVHS).@*METHODS@#Subjects with at least 2 in-patient records were included into the study between 2010 and 2017 from Vascular Medicine Center of Peking University Shougang Hospital. Subjects with CHD or CI, and without data of vascular function at baseline were excluded. Eventually, 467 subjects free of CHD [cohort 1, mean age: (63.4±12.3) years, female 42.2%] and 658 subjects free of CI [cohort 2, mean age: (64.3±12.2) years, female 48.7%] at baseline were included. The first in-patient records were as the baseline data, the second in-patient records were as a following-up data. Cox proportional hazard regression was used to establish the predictive models of CHD or CI derived from BVHS by multivariable-adjusted analysis.@*RESULTS@#The median follow-up time of cohort 1 and cohort 2 was 1.9 years and 2.1 years, respectively. During the follow-up, 164 first CHD events occurred in cohort 1 and 117 first CI events occurred in cohort 2. Four indicators were assessed as continuous variables simultaneously by multivariable-adjusted analysis. In cohort 1, CF-PWV, CR-PWV, ABI, and CAVI reached statistical significance in the multivariable-adjusted models (P<0.05). In cohort 2, only CAVI (P<0.05) was of statistical significance. In addition, the higher CF-PWV became a protector of CHD or CI (P<0.05). The prediction value of BVHS reached the statistical significance for CHD and CI in the unadjusted models (all P<0.05), however, BVHS could only predict the incidence of CHD (P<0.05), but not the incidence of CI (P>0.05) in the multivariable-adjusted models. CF-PWV, CR-PWV, ABI, and CAVI were associated factors of CHD independent of each other (P<0.05), only CAVI (P<0.05) was the risk factor of CI independent of the other three.@*CONCLUSION@#The different vascular indicators might have different effect on CHD or CI. CAVI might be a stable predictor of both CHD and CI. Higher baseline CF-PWV was not necessarily a risk factor of CHD or CI because of proper vascular health management. BVHS was a potential factor for the prediction of CHD, and further research is needed to explore the prediction value for CI.

Trends and characteristics in pre-hospital emergency care in Beijing from 2008 to 2017 / 中华医学杂志(英文版)

BACKGROUND@#We aimed to describe and analyze the pre-hospital emergency medical service (EMS) in Beijing and provide information for the government and medical institutions to optimize EMS.@*METHODS@#We collected all pre-hospital emergency data in Beijing from 2008 to 2017. The chief complaint in each case was classified according to the Medical Priority Dispatch System (MPDS). The sites' administrative districts were determined through geo-encoding of addresses and then classified into four functional regions. We analyzed the demand for EMS, emergency response times (ERT), and disease spectrum for Beijing as a whole, and for each functional region.@*RESULTS@#A total of 4,192,870 pre-hospital EMS cases met the inclusion criteria, with a significant increase (P < 0.001) of 51.60% from 2008 to 2017. EMS demand was positively associated with population (r = 0.946, P < 0.001). The pre-hospital EMS demand rate was 1907.05 in 2008 and 2172.23 in 2017 per 100,000, with no significant change (P = 0.57). ERT increased significantly (P = 0.001), from 19.18 min in 2008 to 24.51 min in 2016. According to MPDS classifications, the demand for pre-hospital care increased for 14 diseases, remained stable for 19, and decreased for only 1 disease. Cases of injury-related disease increased significantly from approximately 90,000 in 2017, accounting for 20% of all pre-hospital EMS cases, and the demand rate decreased in the core region but increased in the sub-urban regions. Cases of heart problems and stroke/transient ischemic attack also increased significantly in the four functional regions, with the highest demand rate in the Core Functional Region.@*CONCLUSIONS@#More resources and effort should be devoted to pre-hospital EMS according to the increased pre-hospital EMS demand and prolonged ERT in Beijing over our 10-year study period. Changes in disease spectrum and differences between functional regions should also be considered.

Monitoring of viral pathogens in pediatric intensive care unit and analysis of clinical significance / 中华儿科杂志

<p><b>OBJECTIVE</b>To study the characteristics of viral spectrum and clinical features of children in pediatric intensive care unit (PICU).</p><p><b>METHOD</b>Nasopharyngeal aspirate specimens (NPA) from 349 patients(1 from each) and 130 cerebrospinal fluids (CSF) specimens were collected from children who were admitted to the PICU of Second Affiliated Hospital of Shantou University Medical College. Additional 87 NPA specimens were collected from healthy children for routine examination on the physical examination center, and the clinical data were collected. Multiplex PCR was applied to detect 16 kinds of viruses from NPA and CSF. Fluorescence quantitative PCR was applied to detect 13 viruses from CSF and to analyze the clinical data of positive cases.</p><p><b>RESULT</b>There were 209 samples (59.9%) of the 349 NPA specimens were positive for viruses, which included 117 cases positive for human rhinovirus (HRV), 60 for respiratory syncytial virus (RSV), 20 for influenza virus A (Inf A), 10 for adenovirus (ADV), 6 for parainfluenza virus type 3(PIV-3), 6 for human Boca virus (HBoV), 5 for influenza virus C(Inf C), 4 for parainfluenza virus type 4(PIV-4), 4 for human coronavirus-HKU1/OC43, 3 for influenza virus B (Inf B), 3 for WU Polyomavirus (WUPyV), 2 parainfluenza virus type 1(PIV-1), 2 human metapneumovirus (HMPV) and 1 human coronavirus-NL63/229E. But none from 87 healthy controls were positive for any respiratory virus. Among the 130 CSF specimens, in 58 cases the diagnosis was viral encephalitis. There were 22 samples (37.9%) among the 58 CSF specimens positive for viruses, which included 14 enterovirus (EV), 3 human cytomegalovirus (HCMV), 2 mumps virus, 1 coxsackie virus A16 (Cox-A16), 1 herpes simplex virus (HSV) and 1 human rhinovirus (HRV). The total positive rate was 63.3% (221/349) . Co-infection by at least 2 viral pathogens under study was observed in 45 of the 349 patients (12.9% of the total number of cases, 20.4% of the positives cases). The commonest pathogens in co-infected samples were WUPyV (100%) and HMPV(100%). The positive rate of virus peaked in the first 6 months of life, the rate in boys were higher than in girls and the peak season was summer. The numbers of none serious cases in the virus positive group were less than those in the virus negative group while the numbers of extremely serious cases in the virus positive group were higher than in the virus negative group.</p><p><b>CONCLUSION</b>Viral pathogen is a major cause of infectious disease in pediatric critical illnesses and virus infection may lead to severe illness.</p>

Detection and clinical features of human rhinovirus in hospitalized children with acute respiratory tract infection in eastern areas of Guangdong province / 中华流行病学杂志

Objective To investigate the prevalence and clinical features of human rhinovirus (HRV) infection in hospitalized children with acute respiratory (ARI) in eastern areas of Guangdong province from 2008 to 2010.Methods From Oct.2008 through Sep.2010,nasopharyngeal aspirates were collected prospectively,from hospitalized children with acute lower respiratory tract infection at the Second Hospital,affiliated to the Shantou University Medical College.Multiplex PCR was applied to detect ten kinds of viruses including HRV,RSV in the hospitalized children with respiratory tract infection.Clinical data on HRV-positive cases or RSV-positive cases were collected and analyzed.Results Among all the 1335 specimens,124 were confirmed as HRV-positive cases (9.3％),with IVA-positive rate as the highest (25.1％),followed by RSV-positive rate (15.1％).HRV infection occurred sporadically around the year,with the highest HRV-positive rate seen in spring 2009 and autumn in 2010.Symptoms,signs,chest X-ray,leukocyte count and CRP count did not differ between patients with co-infection or single HRV infection.Clinical symptoms or signs were similar between those with single HRV infection or single RSV infection in children,but the single RSV infected children were more frequently seen with wheeze and cough.28.4％ of the single RSV infected children had bronchiolitis while 10.7％ of single HRV infected children were seen (x2=0.281,P=0.596).Conclusion HRV was a relatively common cause for acute respiratory infections in the eastern areas of Guangdong province.The highest HRV-positive rate was slightly different in different years.Infants and young children were generally susceptible to rhinovirus infection.Bronchiolitis,wheeze and cough associated with HRV infection happened less than those caused by RSV.

Coordination mechanism and antioxidant activity of L-hydroxyproline zinc(II) / 生物工程学报

The coordination compound of L-hydroxyproline (Hyp)-Zn (II) was synthesized with Hyp and zinc sulfate as raw materials in water medium, coordination Synthesizing Mechanism and Antioxidant Activity of Hyp-Zn(II) coordination compound has been researched. Compared with Hyp, the infrared spectrogram of Hyp-Zn (II) coordination compound emerge a new absorption peak at 1100 cm(-1). Conclusion could be obtained that there exists a coordination effect between Hyp and ZnSO4; TG and DSC curve of Hyp and Hyp-Zn(II) coordination compound were analysed. Compared with Hyp, the peak of Hyp-Zn(II) disappear at 290 degrees C and 375 degrees C. This phenomenon confirmed the front conclusion; At the NMR graph of Hyp-Zn(II) coordination compound, the disappearance of the alpha-carboxyl-hydrogen and alpha-hydroxyl-hydrogen's peak at 3.5-3.9 ppm could indicate that combination's position of Hyp is alpha-carboxyl and alpha-hydroxyl; Structure of Hyp-Zn(II) coordination compound were exosyndrome by the Atomic Force microscopy. It is showed that centr-atom Zn(II) was surrounded by several Hyp at Hyp-Zn(II) coordination compound's phase diagram; The proportion of Hyp-Zn(H) coordination compound was determined by dialysis experiment, the proportion is 4:1; Above-mentioned determination and exosyndrome indicated that the molecular formula of Hyp-Zn (II) coordination compound is Zn(Hyp)4.H2O. The results indicated that the Hyp-Zn(II) coordination compound can inhibit hydroxyl free radicals of Zn(II), and the Percentage of Inhibition is 75.5%; the total antioxidant activities of Hyp-Zn(II) coordination compound is 80.167 u/mL, the anti-superoxide activities of Hyp-Zn (II) coordination compound is 53.19 u/mL.

Study on the behavior of NK cell KIRs of donor/recipient pairs in HLA matched unrelated allo-HSCT / 中华血液学杂志

<p><b>OBJECTIVE</b>To study the biological function of killer cell immunoglobulin-like receptor (KIR) and the role of donor inhibitory KIR and recipient genetic background in HLA matched unrelated hematopoietic stem cell transplantation (HSCT).</p><p><b>METHODS</b>HLA genotype of 51 patients (ALL 18 cases, CML 15 cases, AML 10 cases and others 8 cases) and their respective matched unrelated donors from Database of China Marrow Registration was determined by polymerase chain reaction sequence oligonucleotide probes (PCR-SSOP) and sequence specific primers (PCR-SSP). The KIR genotype was determined by PCR-SSP.</p><p><b>RESULTS</b>All the patients and the donors expressed KIR2DL1, KIR2DL2/L3, KIR2DL4, KIR3DL2 and KIR3DL3. 96.7% individuals expressed KIR3DL1. Among them, 21.57% of KIR was completely identical, while 78.43% was not. Of the non-identical KIRs, 25.49% were the recipient's KIR genotype containing the donor's ones, and 27.45% was the donor's containing the recipient's. 74.62% of donor's KIR2DL1 lacked recipient's C2 ligand, 5.91% of donor's KIR2DL2/L3 lacked recipient's C1 ligand, 19.74% of donor's KIR3DL1 lacked recipient's Bw4 ligand and 54.91% of donor's KIR3DL2 lacked recipient's A3, A11 ligand.</p><p><b>CONCLUSION</b>KIR genotype and HLA class I antigen are inherited independently. KIR2DLI and KIR3DL2 of donors may cause alloreactivity of NK cell. The mismatch of KIR/HLA in donor-recipient plays a very important role in matched unrelated allo-HSCT. The outcome of HSCT can be better predicted by the model of the presence of KIRs on the donor' sNK cells and the absence of corresponding KIR ligand in the recipient's HLA.</p>

Estimating the daily trend in the size of COVID-19 infected population in Wuhan

There has been an outbreak of coronavirus disease (COVID-19) in Wuhan city, Hubei province, China since December 2019. Cases have been exported to other parts of China and more than 20 countries. We provide estimates of the daily trend in the size of the epidemic in Wuhan based on detailed information of 10,940 confirmed cases outside Hubei province.

Prediction of the COVID-19 outbreak based on a realistic stochastic model

The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID-19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing models. In this paper, a novel stochastic model is proposed which aims to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We find that, (1) instead of aberration, there is a remarkable amount of asymptomatic individuals, (2) an individual with symptoms is approximately twice more likely to pass the disease to others than that of an asymptomatic patient, (3) the transmission rate has reduced significantly since the implementation of control measures in Mainland China, (4) it is expected that the epidemic outbreak would be contained by early March in the the selected provinces and cities.

Estimation of incubation period distribution of COVID-19 using disease onset forward time: a novel cross-sectional and forward follow-up study

BackgroundThe current outbreak of coronavirus disease 2019 (COVID-19) has quickly spread across countries and become a global crisis. However, one of the most important clinical characteristics in epidemiology, the distribution of the incubation period, remains unclear. Different estimates of the incubation period of COVID-19 were reported in recent published studies, but all have their own limitations. In this study, we propose a novel low-cost and accurate method to estimate the incubation distribution. MethodsWe have conducted a cross-sectional and forward follow-up study by identifying those asymptomatic individuals at their time of departure from Wuhan and then following them until their symptoms developed. The renewal process is hence adopted by considering the incubation period as a renewal and the duration between departure and symptom onset as a forward recurrence time. Under mild assumptions, the observations of selected forward times can be used to consistently estimate the parameters in the distribution of the incubation period. Such a method enhances the accuracy of estimation by reducing recall bias and utilizing the abundant and readily available forward time data. FindingsThe estimated distribution of forward time fits the observations in the collected data well. The estimated median of incubation period is 8{middle dot}13 days (95% confidence interval [CI]: 7{middle dot}37-8{middle dot}91), the mean is 8{middle dot}62 days (95% CI: 8{middle dot}02-9{middle dot}28), the 90th percentile is 14{middle dot}65 days (95% CI: 14{middle dot}00-15{middle dot}26), and the 99th percentile is 20{middle dot}59 days (95% CI: 19{middle dot}47, 21{middle dot}62). Compared with results in other studies, the incubation period estimated in this study is longer. InterpretationBased on the estimated incubation distribution in this study, about 10% of patients with COVID-19 would not develop symptoms until 14 days after infection. Further study of the incubation distribution is warranted to directly estimate the proportion with long incubation periods. FundingThis research is supported by National Natural Science Foundation of China grant 8204100362 and Zhejiang University special scientific research fund for COVID-19 prevention and control. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSBefore the current outbreak of coronavirus disease (COVID-19) in China, there were two other coronaviruses that have caused major global epidemics over the last two decades. Severe acute respiratory syndrome (SARS) spread to 37 countries and caused 8424 cases and 919 deaths in 2002-03, while Middle East respiratory syndrome (MERS) spread to 27 countries, causing 2494 cases and 858 deaths worldwide to date. Precise knowledge of the incubation period is crucial for the prevention and control of these diseases. We have searched PubMed and preprint archives for articles published as of February 22, 2020, which contain information about these diseases by using the key words of "COVID-19", "SARS", "MERS", "2019-nCoV", "coronavirus", and "incubation". We have found 15 studies that estimated the distribution of the incubation period. There are four articles focused on COVID-19, five on MERS, and six on SARS. Most of these studies had limited sample sizes and were potentially influenced by recall bias. The estimates for mean, median, and percentiles of the incubation period from these articles are summarized in Table 1. O_TBL View this table: org.highwire.dtl.DTLVardef@119cb07org.highwire.dtl.DTLVardef@605c02org.highwire.dtl.DTLVardef@3897e9org.highwire.dtl.DTLVardef@17d4d64org.highwire.dtl.DTLVardef@164102f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONEstimates for the incubation periods of SARS, MERS, and COVID-19. C_TABLECAPTION C_TBL Added value of this studyIn the absence of complete and robust contact-tracing data, we have inferred the distribution of the incubation period of COVID-19 from the durations between departure from Wuhan and symptom onset for the confirmed cases. More than 1000 cases were collected from publicly available data. The proposed approach has a solid theoretical foundation and enhances the accuracy of estimation by reducing recall bias and utilizing a large pool of samples. Implications of all the available evidenceBased on our model, about 10% of patients with COVID-19 do not develop symptoms until 14 days after infection. Further study of individuals with long incubation periods is warranted.

Evaluating transmission heterogeneity and super-spreading event of COVID-19 in a metropolis of China

BackgroundCOVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics including heterogeneity is of vital importance for prediction and intervention of future epidemics. In addition, transmission heterogeneity usually envokes super spreading events (SSEs) where certain individuals infect large numbers of secondary cases. Till now, studies of transmission heterogeneity of COVID-19 and its underlying reason are far from reaching an agreement. MethodsWe collected information of all infected cases between January 21 and February 26, 2020 from official public sources in Tianjin, a metropolis of China. . Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k which characterized the transmission potential and heterogeneity, respectively. Furthermore, we studied the SSE in Tianjin outbreak and evaluated the effect of control measures undertaken by local government based on the heterogeneous model. ResultsA total of 135 confirmed cases (including 34 imported cases and 101 local infections) in Tianjin by February 26th 2020 entered the study. We grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of 4 generations. The estimated reproduction number R was at 0.67 (95%CI: 0.54~0.84), and the dispersion parameter k was at 0.25 (95% CI: 0.13~0.88). A super spreader causing six infections in Tianjin, was identified. In addition, our simulation results showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since January 28th. ConclusionsOur analysis suggested that the transmission of COVID-19 was subcritical but with significant heterogeneity and may incur SSE. More efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors, which is important for developing targeted measures to curb the pandemic.

Estimation of the Time-Varying Reproduction Number of 2019-nCoV Outbreak in China

BackgroundThe 2019-nCoV outbreak in Wuhan, China has attracted world-wide attention. As of February 11, 2020, a total of 44730 cases of novel coronavirus-infected pneumonia associated with COVID-19 were confirmed by the National Health Commission of China. MethodsThree approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers. ResultsA total of 71 chains of transmission together with dates of symptoms onset and 67 dates of infections were identified among 5405 confirmed cases outside Hubei as reported by February 2, 2020. Based on this information, we find the serial interval having an average of 4.41 days with a standard deviation of 3.17 days and the infectious period having an average of 10.91 days with a standard deviation of 3.95 days. ConclusionsThe controlled reproduction number is declining. It is lower than one in most regions of China, but is still larger than one in Hubei Province. Sustained efforts are needed to further reduce the Rc to below one in order to end the current epidemic.