The rapid development of 2019-2020 Wuhan seafood market pneumonia MESHD currently posed a major public health concern in China. Genome sequencing identified a novel beta-coronavirus closely related to SARS-CoV MESHD, named 2019-nCoV by WHO, as the cause of this pandemic disease. Viruses with single stranded RNA genome are prone to evolve quickly by accumulation of mutations, such as SNV, INDEL and cross viral recombination, aiding fast transmission among hosts and cross species. Here we collected related genome sequences and investigated variations shared by different strains of 2019-nCoV, identified reoccurrence of SNV mutations in clusters of patients, an indication of rapid evolution of 2019-nCoV at the transmission from animal host to human. The information collected herein would help to understand the dynamics of current pandemic.

Background China is running a national level antivirus campaign against the novel coronavirus (2019-nCoV). Strict control measures are being enforced in either the populated areas and remote regions. While the virus is closed to be under control, tremendous economic loss has been caused. Methods and findings We assessed the pandemic risk of 2019-nCoV for all cities/regions in China using the random forest algorithm, taking into account the effect of five factors: the accumulative and increased numbers of confirmed cases, total population, population density, and GDP. We defined four levels of the risk, corresponding to the four response levels to public health emergencies in China. The classification system has good consistency among cities in China, as the error rate of the confusion MESHD matrix is 1.58%. Conclusions The pandemic risk of 2019-nCoV is dramatically different among the 442 cities/regions. We recommend to adopt proportionate control policy according to the risk level to reduce unnecessary economic loss.

The recent outbreak of COVID-19 MESHD in Mainland China is characterized by a distinctive algebraic, sub-exponential increase of confirmed cases during the early phase of the epidemic, contrasting an initial exponential growth expected for an unconstrained outbreak with sufficiently large reproduction rate. Although case counts vary significantly between affected provinces in Mainland China, the scaling law $t^{\mu}$ is surprisingly universal, with a range of exponents $\mu=2.1\pm0.3$. The universality of this behavior indicates that despite social, regional, demographical, geographical, and socio-economical heterogeneities of affected Chinese provinces, this outbreak is dominated by fundamental mechanisms that are not captured by standard epidemiological models. We show that the observed scaling law is a direct consequence of containment policies that effectively deplete the susceptible population. To this end we introduce a parsimonious model that captures both, quarantine of symptomatic infected individuals as well as population wide isolation in response to mitigation policies or behavioral changes. For a wide range of parameters, the model reproduces the observed scaling law in confirmed cases and explains the observed exponents. Quantitative fits to empirical data permit the identification of peak times in the number of asymptomatic or oligo-symptomatic, unidentified infected individuals, as well as estimates of local variations in the basic reproduction number. The model implies that the observed scaling law in confirmed cases is a direct signature of effective contaiment strategies and/or systematic behavioral changes that affect a substantial fraction of the susceptible population. These insights may aid the implementation of containment strategies in potential export induced COVID-19 MESHD secondary outbreaks elsewhere or similar future outbreaks of other emergent infectious diseases MESHD.

Since beginning of this century, there have already been three zoonotic outbreaks caused by beta coronaviruses (CoV), SA RS-CoV i MESHDn 2002-2003, MERS-CoV in 2012, and the newly identified 2019-nCoV in late 2019, Wuhan, China. As to Feb 10th, 2020, there are over 40,000 confirmed cases and over 900 deaths. However, little is known about the biology of this newly emerged virus. Here we developed a lentiviral based pseudovirus system for S protein PROTEIN of 2019-nCoV to study virus entry in BSL2 settings. First, we confirmed that human an giotensin converting enzyme 2 ( HGNChA CE2) HGNCis the main entry receptor for 2019-nCoV. Second, we found that 2019-nCoV S protein PROTEIN mediated entry on 293/hA CE2 c HGNCells was mainly through endocytosis, and PIKfyve, TP C2, HGNCand ca thepsin L a HGNCre critical for virus entry. Third, 2019-nCoV S protein PROTEIN is less stable than SARS-CoV, and it could trigger protease-independent and receptor dependent cell-cell fusion, which might help virus rapidly spread from cell to cell. Finally and more importantly, polyclonal anti-SARS S1 antibodies T62 effectively inhibited entry of SA RS-CoV S pseudovirions, MESHDbut almost had no effect on entry of 2019-nCoV S pseudovirions. Further studies using sera from one recovered SA RS-CoV p MESHDatient and five 2019-nCoV patients showed that there was only limited cross-neutralization activities between SA RS-CoV a MESHDnd 2019-nCoV sera, suggesting that recovery from one infection might not protect against the other. Our results present potential targets for development of drugs and vaccines for 2019-nCoV. 

Objectives: Amid the continuing spread of the novel coronavirus ( COVID-19 MESHD), the incubation period of COVID-19 MESHD should be regularly re-assessed as more information is available upon the increase in reported cases. The present work estimated the distribution of incubation periods of patients infected in and outside Hubei province of China. Methods: Clinical data were collected from the individual cases reported by the media as they were not fully available on the official pages of the Chinese health authorities. MLE was used to estimate the distributions of the incubation period. Results: It was found that the incubation period of patients with no travel history to Hubei was longer and more volatile. Conclusion: It is recommended that the duration of quarantine should be extended to at least 3 weeks.

The ongoing outbreak of viral pneumonia MESHD in China and beyond is associated with a novel coronavirus, provisionally termed 2019-nCoV. This outbreak has been tentatively associated with a seafood market in Wuhan, China, where the sale of wild animals may be the source of zoonotic infection MESHD. Although bats are likely reservoir hosts for 2019-nCoV, the identity of any intermediate host facilitating transfer to humans is unknown. Here, we report the identification of 2019-nCoV related coronaviruses in pangolins (Manis javanica) seized in anti-smuggling operations in southern China. Metagenomic sequencing identified pangolin associated CoVs that belong to two sub-lineages of 2019-nCoV related coronaviruses, including one very closely related to 2019-nCoV in the receptor-binding domain. The discovery of multiple lineages of pangolin coronavirus and their similarity to 2019-nCoV suggests that pangolins should be considered as possible intermediate hosts for this novel human virus and should be removed from wet markets to prevent zoonotic transmission.

The recent outbreak of a new coronavirus (SARS-CoV-2) in Wuhan, China, underscores the need for understanding the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. Here, we show that recombination in betacoronaviruses, including human-infecting viruses like SARS-CoV MESHD and MERS-CoV, frequently encompasses the Receptor Binding Domain (RBD) in the Spike gene. We find that this common process likely led to a recombination event at least 11 years ago in an ancestor of the SARS-CoV-2 involving the RBD. As a result of this recombination event, SARS-CoV and SARS-CoV-2 MESHD share a similar genotype in RBD, including two insertions (positions 432-436 and 460-472), and alleles 427N and 436Y. Both 427N and 436Y belong to a helix that interacts with the human ACE2 receptor. Ancestral state analyses revealed that SARS-CoV-2 differentiated from its most recent common ancestor with RaTG13 by accumulating a significant number of amino acid changes in the RBD. In sum, we propose a two-hit scenario in the emergence of the SARS-CoV-2 virus whereby the SARS-CoV-2 ancestors in bats first acquired genetic characteristics of SARS-CoV MESHD by incorporation of a SARS-like RBD through recombination before 2009, and subsequently, the lineage that led to SARS-CoV-2 accumulated further, unique changes specifically in the RBD.

Objective: To investigate the meteorological condition for incidence and spread of 2019-nCoV infection MESHD, to predict the epidemiology of the infectious disease MESHD, and to provide a scientific basis for prevention and control measures against the new disease. Methods: The meteorological factors during the outbreak period of the novel coronavirus pneumonia MESHD in Wuhan in 2019 were collected and analyzed, and were confirmed with those of Severe Acute Respiratory Syndrome MESHD (SARS) in China in 2003. Data of patients infected with 2019-nCoV and SARS coronavirus were collected from WHO website and other public sources. Results: This study found that the suitable temperature range for 2019-nCoV coronavirus survival is (13-24 degree Celsius), among which 19 degree Celsius lasting about 60 days is conducive to the spread between the vector and humans; the humidity range is 50%-80%, of which about 75% humidity is conducive to the survival of the coronavirus; the suitable precipitation range is below 30 mm/ month. Cold air and continuous low temperature over one week are helpful for the elimination of the virus. The prediction results show that with the approach of spring, the temperature in north China gradually rises, and the coronavirus spreads to middle and high latitudes along the temperature line of 13-18 degree Celsius. The population of new coronavirus infections MESHD is concentrated in Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai and other urban agglomerations. Starting from May 2020, the Beijing-Tianjin-Hebei urban agglomeration, the Central China Zhengzhou-Wuhan urban agglomeration, the eastern Jiangsu-Zhejiang-Shanghai urban agglomeration, and the southern Pearl River Delta urban agglomeration are all under a high temperature above 24 degree Celsius, which is not conducive to the survival and reproduction of coronaviruses, so the epidemic is expected to end. Conclusions: A wide range of continuous warm and dry weather is conducive to the survival of 2019-nCoV. The coming of spring, in addition to the original Wuhan-Zhengzhou urban agglomeration in central China, means that the prevention and control measures in big cities located in mid-latitude should be strengthened, especially the monitoring of transportation hubs. The Pearl River Delta urban agglomeration is a concentrated area of population in south China, with a faster temperature rise than those in mid-high latitudes, and thus the prevention in this area should be prioritized. From a global perspective, cities with a mean temperature below 24 degree Celsius are all high-risk cities for 2019-nCoV transmission before June.

There is large uncertainty around the case fatality risk (CFR) for COVID-19 MESHD in China. Therefore, we considered symptomatic cases outside of China (countries/settings with 20+ cases) and the proportion who are in intensive care units (4.0%, 14/349 on 13 February 2020). Given what is known about CFRs for ICU patients with severe respiratory conditions from a meta-analysis, we estimated a CFR of 1.37% (95%CI: 0.57% to 3.22%) for COVID-19 MESHD cases outside of China.

The outbreak of the novel coronavirus (2019-nCoV) epidemic has attracted world- wide attention. Herein, we propose a mathematical model to analyzes this epidemic, based on a dynamic mechanism that incorporating the intrinsic impact of hidden la- tent and infectious cases on the entire process of transmission. Meanwhile, this model is validated by data correlation analysis, predicting the recent public data, and back- tracking, as well as sensitivity analysis. The dynamical model reveals the impact of various measures on the key parameters of the epidemic. According to the public data of NHCs from 01/20 to 02/09, we predict the epidemic peak and possible end time for 5 different regions. The epidemic in Beijing and Shanghai, Mainland/Hubei and Hubei/Wuhan, are expected to end before the end of February, and before mid- March respectively. The model indicates that, the outbreak in Wuhan is predicted to be ended in the early April. As a result, more effective policies and more efforts on clinical research are demanded. Moreover, through the backtracking simulation, we infer that the outbreak of the epidemic in Mainland/Hubei, Hubei/Wuhan, and Wuhan can be dated back to the end of December 2019 or the beginning of January 2020.