Project description:AbstractTo provide references for global pandemic prevention and control, this study aimed to analyze the epidemiological characteristics and clinical manifestations of 103 new confirmed cases between June 12 and June 15, 2020, in Beijing. All confirmed cases in this study were tested with a positive SARS-CoV-2 reverse transcriptase-polymerase chain reaction and extracting data from the Beijing Municipal Health Commission (June 11 to July 6, 2020). We selected the 103 typical confirmed cases (excluding imported cases) between June 12 and June 15 for statistical analysis and explored differences among different clinical cases. A cluster of COVID-19 was reported in Beijing between June 12 and June 15, 2020, involving 103 confirmed cases. Patients aged 21 to 65 years old and the mean age was 42.38 ± 11.507, the male-to-female sex ratio was 1.40:1. All confirmed cases had a direct or indirect exposure history in the Beijing Xinfadi Market (BXM), and the clinical manifestations of 97% confirmed cases was diagnosed as mild or moderate. Different clinical classification in age (P = .041), exposure history (P = .025), fever (P = .020), and cough (P = .000) were the statistically significant difference, but there was no statistically significant difference in gender (P = .501), the type of diagnosis (P = .478), expectoration (P = .979), fatigue (P = .906), dizziness or headache (P = .848), muscle pain (P = .825), sore throat or throat discomfort (P = .852), chills (P = .933), diarrhea (P = .431) and runny nose or nasal congestion (P = .898). This study shows that Beijing's epidemic scope was mainly concentrated in the Xinfadi Market. The initial cases were epidemiologically related to the BXM, the clinical classification of most cases was mild and moderate, and the differences in age, exposure history, fever, and cough among different clinical cases were statistically significant.
Project description:ObjectivesThe aim of the study was to reconstruct the complete transmission chain of the COVID-19 outbreak in Beijing's Xinfadi Market using data from epidemiological investigations, which contributes to reflecting transmission dynamics and transmission risk factors.MethodsWe set up a transmission model, and the model parameters are estimated from the survey data via Markov chain Monte Carlo sampling. Bayesian data augmentation approaches are used to account for uncertainty in the source of infection, unobserved onset, and infection dates.ResultsThe rate of transmission of COVID-19 within households is 9.2%. Older people are more susceptible to infection. The accuracy of our reconstructed transmission chain was 67.26%. In the gathering place of this outbreak, the Beef and Mutton Trading Hall of Xinfadi market, most of the transmission occurs within 20 m, only 19.61% of the transmission occurs over a wider area (>20 m), with an overall average transmission distance of 13.00 m. The deepest transmission generation is 9. In this outbreak, there were 2 abnormally high transmission events.ConclusionsThe statistical method of reconstruction of transmission trees from incomplete epidemic data provides a valuable tool to help understand the complex transmission factors and provides a practical guideline for investigating the characteristics of the development of epidemics and the formulation of control measures.
Project description:After 56 days without coronavirus disease 2019 (COVID-19) cases, reemergent cases were reported in Beijing, China on June 11, 2020. Here, we report the genetic characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequenced from the clinical specimens of 4 human cases and 2 environmental samples. The nucleotide similarity among six SARS-CoV-2 genomes ranged from 99.98% to 99.99%. Compared with the reference strain of SARS-CoV-2 (GenBank No. NC_045512), all six genome sequences shared the same substitutions at nt241 (C → T), nt3037 (C → T), nt14408 (C → T), nt23403 (A → G), nt28881 (G → A), nt28882 (G → A), and nt28883 (G → C), which are the characteristic nucleotide substitutions of L-lineage European branch I. This was also proved by the maximum likelihood phylogenetic tree based on the full-length genome of SARS-CoV-2. They also have a unique shared nucleotide substitution, nt6026 (C → T), which is the characteristic nucleotide substitution of SARS-CoV-2 in Beijing's Xinfadi outbreak. It is noteworthy that there is an amino acid D614G mutation caused by nt23403 substitution in all six genomes, which may enhance the virus's infectivity in humans and help it become the leading strain of the virus to spread around the world today. It is necessary to continuously monitor the genetic variation of SARS-CoV-2, focusing on the influence of key mutation sites of SARS-CoV-2 on viral transmission, clinical manifestations, severity, and course of disease.
Project description:BackgroundA local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing's XFD market and inform future response efforts of resurgence across regions.MethodsA modified susceptible-exposed-infectious-recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI).ResultsOur results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31-77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment.ConclusionsThis study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere.
Project description:Table of contents A1 Proceedings of 2016 China Cancer Immunotherapy Workshop, Beijing, China Bin Xue, Jiaqi Xu, Wenru Song, Zhimin Yang, Ke Liu, Zihai Li A2 Set the stage: fundamental immunology in forty minutes Zihai Li A3 What have we learnt from the anti-PD-1/PD-L1 therapy of advanced human cancer? Lieping Chen A4 Immune checkpoint inhibitors in lung cancer Edward B. Garon A5 Mechanisms of response and resistance to checkpoint inhibitors in melanoma Siwen Hu-Lieskovan A6 Checkpoint inhibitor immunotherapy in lymphoid malignancies Wei Ding A7 Translational research to improve the efficacy of immunotherapy in genitourinary malignancies Chong-Xian Pan A8 Immune checkpoint inhibitors in gastrointestinal malignancies Weijing Sun A9 What’s next beyond PD-1/PDL1? Yong-Jun Liu A10 Cancer vaccines: new insights into the oldest immunotherapy strategy Lei Zheng A11 Bispecific antibodies for cancer immunotherapy Delong Liu A12 Updates on CAR-T immunotherapy Michel Sadelain A13 Adoptive T cell therapy: personalizing cancer treatment Cassian Yee A14 Immune targets and neoantigens for cancer immunotherapy Rongfu Wang A15 Phase I/IIa trial of chimeric antigen receptor modified T cells against CD133 in patients with advanced and metastatic solid tumors Meixia Chen, Yao Wang, Zhiqiang Wu, Hanren Dai, Can Luo, Yang Liu, Chuan Tong, Yelei Guo, Qingming Yang, Weidong Han A16 Cancer immunotherapy biomarkers: progress and issues Lisa H. Butterfield A17 Shaping of immunotherapy response by cancer genomes Timothy A. Chan A18 Unique development consideration for cancer immunotherapy Wenru Song A19 Immunotherapy combination Ruirong Yuan A20 Immunotherapy combination with radiotherapy Bo Lu A21 Cancer immunotherapy: past, present and future Ke Liu A22 Breakthrough therapy designation drug development and approval Max Ning A23 Current European regulation of innovative oncology medicines: opportunities for immunotherapy Harald Enzmann, Heinz Zwierzina