OBJECTIVE: To study the neurological manifestations of patients with coronavirus disease 2019 MESHD ( COVID-19 MESHD). DESIGN: Retrospective case series SETTING: Three designated COVID-19 MESHD care hospitals of the Union Hospital of Huazhong University of Science and Technology in Wuhan, China. PARTICIPANTS: Two hundred fourteen hospitalized patients with laboratory confirmed diagnosis of severe acute respiratory syndrome MESHD from coronavirus 2 (SARS-CoV-2) infection MESHD. Data were collected from 16 January 2020 to 19 February 2020. MAIN OUTCOME MEASURES: Clinical data were extracted from electronic medical records and reviewed by a trained team of physicians. Neurological symptoms fall into three categories: central nervous system (CNS) symptoms or diseases ( headache MESHD, dizziness MESHD, impaired consciousness MESHD, ataxia MESHD, acute cerebrovascular disease MESHD, and epilepsy MESHD), peripheral nervous system (PNS) symptoms ( hypogeusia MESHD, hyposmia, hypopsia, and neuralgia MESHD), and skeletal muscular symptoms. Data of all neurological symptoms were checked by two trained neurologists. RESULTS: Of 214 patients studied, 88 (41.1%) were severe and 126 (58.9%) were non-severe patients. Compared with non-severe patients, severe patients were older (58.7 {+/-} 15.0 years vs 48.9 {+/-} 14.7 years), had more underlying disorders (42 [47.7%] vs 41 [32.5%]), especially hypertension MESHD (32 [36.4%] vs 19 [15.1%]), and showed less typical symptoms such as fever MESHD (40 [45.5%] vs 92 [73%]) and cough (30 [34.1%] vs 77 [61.1%]). Seventy-eight (36.4%) patients had neurologic manifestations. More severe patients were likely to have neurologic symptoms (40 [45.5%] vs 38 [30.2%]), such as acute cerebrovascular diseases MESHD (5 [5.7%] vs 1 [0.8%]), impaired consciousness MESHD (13 [14.8%] vs 3 [2.4%]) and skeletal muscle injury MESHD (17 [19.3%] vs 6 [4.8%]). CONCLUSION: Compared with non-severe patients with COVID-19 MESHD, severe patients commonly had neurologic symptoms manifested as acute cerebrovascular diseases MESHD, consciousness impairment and skeletal muscle symptoms MESHD.

Background. The clinical presentation of 2019 Novel Coronavirus (2019-nCov) infected pneumonia MESHD (NCIP) resembles that of other etiologies of community-acquired pneumonia MESHD (CAP). We aimed to identify clinical laboratory features to distinguish NCIP from CAP. Methods. We compared the ability of the hematological and biochemical features of 84 patients with NCIP at hospital admission and 316 patients with CAP. Parameters independently predictive of NCIP were calculated by multivariate logistic regression. The receiver operating characteristic (ROC) curves were generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability. Results. Most hematological MESHD and biochemical indexes of patients with NCIP were significantly different from patients with CAP. Nine laboratory parameters were identified to be highly predictive of a diagnosis of NCIP by multivariate analysis. The AUCs demonstrated good discriminatory ability for red cell distribution width (RDW) with an AUC of 0.88 and Hemoglobin (HGB) with an AUC of 0.82. Red blood cell (RBC), albumin ( ALB HGNC), eosinophil (EO), hematocrit (HCT), alkaline phosphatase ( ALP HGNC), and white blood cell (WBC) had fair discriminatory ability. Combinations of any two parameters performed better than did the RDW alone. Conclusions. Routine laboratory examinations may be helpful for the diagnosis of NCIP. Application of laboratory tests may help to optimize the use of isolation rooms for patients when they present with unexplained febrile respiratory illnesses.

The Coronavirus Disease 2019 MESHD ( COVID-19 MESHD) epidemic began in Wuhan, China in late 2019 and continues to spread globally, with exported cases confirmed in 28 countries at the time of writing. During the interval between February 19 and 23, 2020, Iran reported its first 43 cases with eight deaths. Three exported cases originating in Iran were identified, suggesting a underlying burden of disease in that country than is indicated by reported cases. A large epidemic in Iran could further fuel global dissemination of COVID-19 MESHD. We sought to estimate COVID-19 MESHD outbreak size in Iran based on known exported case counts and air travel links between Iran and other countries, and to anticipate where infections originating in Iran may spread to next. We assessed interconnectivity between Iran and other countries using using International Air Transport Association (IATA) data. We used the methods of Fraser et al. to estimate the size of the underlying epidemic that would result in cases being observed in the United Arab Emirates (UAE), Lebanon, and Canada. Time at risk estimates were based on a presumed 6 week epidemic age, and length of stay data for visitors to Iran derived from the United Nations World Tourism Organization (UNWTO). We evaluated the relationship between the strength of travel links with Iran, and destination country rankings on the Infectious Disease Vulnerability Index (IDVI), a validated metric that estimates the capacity of a country to respond to an infectious disease MESHD outbreak . Scores range between 0-1, with higher scores reflecting greater capacity to manage infectious outbreaks. UAE, Lebanon, and Canada ranked 3rd, 21st, and 31st, respectively, for outbound air travel volume from Iran in February 2019. We estimated that 18,300 (95% confidence interval: 3770 to 53,470) COVID-19 MESHD cases would have had to occur in Iran, assuming an outbreak duration of 1.5 months in the country, in order to observe these three internationally exported cases reported at the time of writing. Results were robust under varying assumptions about undiagnosed case numbers in Syria, Azerbaijan and Iraq. Even if it were assumed that all cases were identified in all countries with certainty, the "best case" outbreak size was substantial (1820, 95% CI: 380-5320 cases), and far higher than reported case counts. Given the low volumes of air travel to countries with identified cases of COVID-19 MESHD with origin in Iran (such as Canada), it is likely that Iran is currently experiencing a COVID-19 MESHD epidemic of significant size for such exportations to be occurring. This is concerning, both for public health in Iran itself, and because of the high likelihood for outward dissemination of the epidemic to neighbouring countries with lower capacity to respond to infectious diseases MESHD epidemics.

The outbreak of COVID-19 MESHD originated in Wuhan has become a global epidemic of contagious diseases, which poses a serious threat to human life and health, especially for those with underlined diseases. However, Impacts of COVID-19 MESHD epidemic on HD center and HD patients are still unknown. In this report, we reviewed the whole course of the epidemic emerged in the HD center of Renmin Hospital, Wuhan University from January 14, 2020, the day the first case was confirmed, to February 17, 2020, the day the epidemic extinction. There are totally 37 cases among 230 HD patients and 4 cases among 33 staff being diagnosed with COVID-19 MESHD. The epidemiology, clinical presentation and immune profile of dialysis patients contracted COVID-19 MESHD were further studied. We found that the two key measures we took in response to the epidemic, one was upgrading level of prevention and protection on January 21 and the other one starting universal screening, isolating, and distributing the infected cases on February 4, were effective in the epidemic control. No new COVID-19 MESHD case had been diagnosed since February 13. During the epidemic, 7 HD patients died, including 6 with COVID-19 MESHD and 1 without COVID-19 MESHD. The presumed causes of death MESHD were not directly related to pneumonia MESHD, but due to cardiovascular and cerebrovascular diseases MESHD, hyperkalemia MESHD, etc. Most of the leukocytes in the peripheral blood of the HD patients infected with COVID-19 MESHD decreased, and the CT images of the chest mostly showed the ground glass like changes on the right side. The symptoms of most of the patients were mild, and there were no cases admitted to ICU. The frequency of lymphocytes in PBMCs and the serum level of inflammatory cytokines were assessed in HD patients contracted COVID-19 MESHD or not, non-HD COVID-19 MESHD patients, as well as healthy volunteers. The results showed that lymphocytes of T cell, Th cells, killer T cells, as well as NK cells in PBMCs of HD patients decreased significantly than other groups. HD patients with COVID-19 MESHD also displayed remarkable lower serum level of inflammatory cytokines than other COVID-19 MESHD patients. Our study indicates that HD patients are the highly susceptible population and HD centers are high risk area in the outbreak of COVID-19 MESHD epidemic. Measures of prevention, protection, screening, isolation, and distribution are essential in the epidemic management and should be taken in the early stage. HD Patients with COVID-19 MESHD are mostly clinical mild and unlikely progress to severe pneumonia MESHD due to the impaired cellular immune function and incapability of mounting cytokines storm. More attention should be paid to prevent cardiovascular events, which may be the collateral impacts of COVID-19 MESHD epidemic on HD patients.

Objectives: Simulate the transmission process of COVID-19 MESHD in a cruise ship HGNC, and then to judge how many infections there will be in the 3711 people in the "Diamond Princess" and analyze measures that could have prevented mass transmission. Methods: Based on the crowd flow model, the virus transmission rule between pedestrians is established, to simulate the spread of the virus caused by the close contact during pedestrians' daily activities on the cruise ship HGNC. Measurements and main results: Three types of simulation scenarios are designed, the Basic scenario focus on the process of virus transmission caused by a virus carrier and the effect of the personal protective measure against the virus. The condition that the original virus carriers had disembarked halfway and more and more people strengthen self-protection are considered in the Self-protection scenario, which would comparatively accord with the actual situation of "Diamond princess" cruise. Control scenario are set to simulate the effect of taking recommended or mandatory measures on virus transmission Conclusions: There are 850~1009 persons (with large probability) who have been infected with COVID-19 MESHD during the voyage of "Diamond Princess". The crowd infection percentage would be controlled effectively if the recommended or mandatory measures can be taken immediately during the alert phase of COVID-19 MESHD outbreaks.

Since late December 2019 a new epidemic outbreak has emerged from Whuhan, China. Rapidly the new coronavirus has spread worldwide. China CDC has reported results of a descriptive exploratory analysis of all cases diagnosed until the 11th February 2020, presenting the epidemiologic curves and geo-temporal spread of COVID-19 MESHD along with case fatality rate according to some baseline characteristics, such as age, gender and several well-established high prevalence comorbidities. Despite this, we intend to increase even further the predictive value of that manuscript by presenting the odds ratio for mortality due to COVID-19 MESHD adjusted for the presence of those comorbidities and baseline characteristics such as age and gender. Besides, we present a way to determine the risk of each particular patient, given his characteristics. We found that age is the variable that presents higher risk of COVID-19 MESHD mortality, where 60 or older patients have an OR = 18.8161 (CI95%[7.1997; 41.5517]). Regarding comorbidities, cardiovascular disease appears to be the riskiest (OR=12.8328 CI95%[10.2736; 15.8643], along with chronic respiratory disease (OR=7.7925 CI95%[5.5446; 10.4319]). Males are more likely to die from COVID-19 MESHD (OR=1.8518 (CI95%[1.5996; 2.1270]). Some limitations such as the lack of information about the correct prevalence of gender per age or about comorbidities per age and gender or the assumption of independence between risk factors are expected to have a small impact on results. A final point of paramount importance is that the equation presented here can be used to determine the probability of dying from COVID-19 MESHD for a particular patient, given its age interval, gender and comorbidities associated.

The CoViD-19 MESHD outbreak has escalated to a pandemic in the last few months. Pharmaceutical solutions based upon virologic studies, at this point, remain inconclusive, with no proven pharmaceutical solution so far. In contrast, this paper looks towards creating more accurate epidemiological models during this phase of viral growth in order to provide better feedback measures to public health officials and agencies, in particular, by providing a responsive, timely model of the R value based on the previous few days' results. Such an R value, although bearing less statistical precision due to limited sampling, could allow R to become a more effective, responsive standalone measure of infectious transmission. It demonstrates that the R value can be used as a dynamic, time-dependent indicator without the use of curve-fitting, and also estimates the most recent R-value of the CoViD-19 MESHD outbreak to be between 1.32 and 1.35.

288 cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized importations timeline to assess the rapidity of isolation, and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the upcoming weeks. Time from travel to detection has considerably decreased since the first importation, however 6 cases out of 10 were estimated to go undetected. Countries outside China should be prepared for the possible emergence of several undetected clusters of chains of local transmissions.

As of March 31, 2020 the ongoing COVID-19 MESHD epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19 MESHD. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued. Here we estimate the effective reproduction number, Rt, of COVID-19 MESHD in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts. The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI: 0.3, 1.0) during the first transmission wave by February 14, 2020 while the overall R based on the cluster size distribution as of March 17, 2020 was estimated at 0.6 (95% CI: 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI: 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p<0.001). The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

Background A novel coronavirus ( COVID-19 MESHD) has emerged recently as an acute respiratory syndrome MESHD. The outbreak was originally reported in Wuhan, China, but has subsequently been spread world-widely. As the COVID-19 MESHD continues to spread rapidly across the world, computed tomography (CT) has become essentially important for fast diagnoses. Thus, it is urgent to develop an accurate computer-aided method to assist clinicians to identify COVID-19 MESHD-infected patients by CT images. Materials and Methods We collected chest CT scans of 88 patients diagnosed with the COVID-19 MESHD from hospitals of two provinces in China, 101 patients infected with bacteria pneumonia MESHD, and 86 healthy persons for comparison and modeling. Based on the collected dataset, a deep learning-based CT diagnosis system (DeepPneumonia) was developed to identify patients with COVID-19 MESHD. Results The experimental results showed that our model can accurately identify the COVID-19 MESHD patients from others with an excellent AUC of 0.99 and recall (sensitivity) of 0.93. In addition, our model was capable of discriminating the COVID-19 MESHD infected MESHD patients and bacteria pneumonia-infected MESHD patients with an AUC of 0.95, recall (sensitivity) of 0.96. Moreover, our model could localize the main lesion features, especially the ground-glass opacity (GGO) that is of great help to assist doctors in diagnosis. The diagnosis for a patient could be finished in 30 seconds, and the implementation on Tianhe-2 supercompueter enables a parallel executions of thousands of tasks simultaneously. An online server is available for online diagnoses with CT images by http://biomed.nscc-gz.cn/server/Ncov2019. Conclusions The established models can achieve a rapid and accurate identification of COVID-19 MESHD in human samples, thereby allowing identification of patients.