Analysis of coinfections in patients with hematologic malignancies and COVID-19 by next-generation sequencing of bronchoalveolar lavage fluid (preprint)

Background Coinfections in patients with coronavirus disease 2019 (COVID-19) affect patient prognosis. Patients with hematologic malignancies (HMs) are usually immunosuppressed and may be at high risk of coinfection, but few related data have been reported. Here, we conducted a retrospective study to explore coinfections in patients with HMs and COVID-19 by next-generation sequencing (NGS) of bronchoalveolar lavage fluid (BALF).Methods The data of hospitalized patients with pneumonia who underwent NGS analysis of BALF were reviewed. COVID-19 patients with HMs were enrolled in the HM group, and those without HMs were enrolled in the non-HM group. The coinfections of the two groups identified by NGS were analyzed.Results Fifteen patients were enrolled in the HM group, and 14 patients were enrolled in the non-HM group. The coinfection rates in the HM group and non-HM group were 80.0% and 85.7%, respectively. The percentage of coinfected bacteria in the HM group was significantly lower than that in the non-HM group (20.0% vs 71.4%, p = 0.005). The coinfection rates of fungi and viruses were 60.0% and 35.7%, respectively, in the HM group and 35.7% and 78.6%, respectively, in the non-HM group, with no significant differences. The most common coexisting pathogen in patients with HMs was Pneumocystis jirovecii (33.3%), and the most common coexisting pathogen in patients without HMs was human gammaherpesvirus 4 (50%). Coinfection with herpesviruses occurred frequently in both groups.Conclusions Our study showed that hospitalized patients with COVID-19 had a high incidence of coinfection. Pneumocystis jiroveci and herpesvirus are commonly coinfected pathogens in patients with HMs. Bacterial coinfection is rare in patients with HMs but is more common in patients without HMs.

Study on fire evacuation in public places during COVID-19 epidemic control

In order to explore the influence of the opening state of safety exits in public buildings on the personnel evacuation during the COVID-19 epidemic control, the evacuation management of public buildings and the opening state of safety exits were understood through the field investigation.The Pathfinder was used to simulate the fire evacuation of an office building in a university before and after the COVID-19 epidemic control, and the total length of individual congestion, the longest continuous congestion duration and the evacuation route in the personnel evacuation process were analyzed.Three recommended exits opening schemes were proposed, and the optimal scheme was obtained by Pathfinder simulation.The results showed that during the period of epidemic control, all the public buildings closed partial safe exits for the body temperature detection.The length of personnel congestion increased significantly during the epidemic control period, the per capita congestion time was 16.01 s, and the longest individual congestion time was 120.45 s before COVID-19,while the per capita congestion time was 23.92 s, and the longest individual congestion time was 168.23 s after COVID-19.Some personnel in region A converged to region B,resulting in an increase in the personnel density of stair 2 and the congestion of stairs on the 2～3 floors.The scheme Ⅲ with opening exits Ⅰ and Ⅳ simultaneously was the optimal opening scheme.

Unspecific reactivity must be excluded in COVID-19 epidemiological analyses or virus tracing based on serologic testing: Analysis of 46,777 post-pandemic samples and 1,114 pre-pandemic samples

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Serologic testing is complementary to nucleic acid screening to identify SARS-CoV-2. This study aimed to evaluate unspecific reactivity in SARS-CoV-2 serologic tests. Materials and methods Total anti-SARS-CoV-2 antibodies from 46,777 subjects who were screened for SARS-CoV-2 were retrospectively studied to evaluate the incidence and characteristics of the unspecific reactivity. A total of 1,114 pre-pandemic samples were also analysed to compare unspecific reactivity. Results The incidence of unspecific reactivity in anti-SARS-CoV-2 total antibody testing was 0.361% in 46,777 post-pandemic samples, similar to the incidence of 0.359% (4/1,114) in 1,114 pre-pandemic samples (p = 0.990). Subjects ≥ 19 years old had a 2.753-fold [95% confidence interval (CI), 1.130–6.706] higher probability of unspecific reactivity than subjects < 19 years old (p = 0.026). There was no significant difference between the sexes. The unspecific reactivity was associated with 14 categories within the disease spectrum, with three tops being the skin and subcutaneous tissue diseases (0.93%), respiratory system diseases (0.78%) and neoplasms diseases (0.76%). The percentage of patients with a titer ≥ 13.87 cut-off index (COI) in the unspecific reactivity was 7.69%. Conclusion Our results suggest a unspecific reactivity incidence rate of 0.361% involving 14 categories on the disease spectrum. Unspecific reactivity needs to be excluded when performing serologic antibody testing in COVID-19 epidemiological analyses or virus tracing.

A review on quality control, toxicity and clinical application of Amomum tsao-ko Crevost & Lemarié

The dried fruit of Amomum tsao-ko Crevost & Lemarié, a perennial herb of Cardamom in Zingiberaceae, has been widely used in food and as a folk medicine. It is used not only as an important food additive and spice for removing peculiar smell and improving taste, but also as a traditional Chinese medicine with significant efficacy in treating many kinds of disorders. Based on the high edible and medicinal value, large amounts of investigation have been reported for A. tsaoko in the past several years. This review specifically summarises its quality control, toxicology and clinical application, about which no literature had systematically reviewed, based on our best acknowledge. The current quality control of A. tsaoko is based on the content of volatile oil, which should be no less than 1.4% according to the Pharmacopoeia of the People's Republic of China (2020 edition), while a more possible Q-Markers should be developed to focus on either a specific bioactive ingredient or a component correlated with a certain clinical efficacy. Toxicity research suggests that A. tsaoko actually belongs to the non-toxic substance, although citral and 1,8-cineole, two main components of A. tsaoko, is hepatotoxic for the former and displays low acute toxicity and sub-chronic oral toxicity for the latter, but no obviously accumulative toxicity has so far been discovered for A. tsaoko. In clinical practice, A. tsaoko is often used in treatment of dampness/cold resistance, malaria, vomiting, fullness and epigastric distension across additional disorders, such as SARS, COVID-19 and hepatitis.

Death Risk Analysis for Patients With Severe COVID-19 Pneumonia (preprint)

Background: Coronavirus Disease 2019 (COVID-19) is currently a global pandemic. Information about the death predicting of severe COVID-19 is not clear. Methods: 151 in-patients from January 23th to March 8th 2020 were divided into severe and critically severe group, as well as survival and death group. The analysis of differences of clinical and imaging data were performed between groups. The logistic regression analysis of factors associated with death in COVID-19 were conducted, and the prediction model of death risk was developed.Results: Many clinical and imaging indices were significantly different between groups, including the age, the epidemic history, the past medical history, the duration of symptoms prior to admission, blood routine, inflammatory related factors, Na+, myocardial zymogram, liver and renal function, coagulation function, fraction of inspired oxygen and complications. The proportion of patients in imaging stage III and comprehensive CT scores was increased significantly in death group. The area under receiver operating characteristic curve of the prediction model was 0.9593.Conclusions: The clinical and imaging data reflect the severity of COVID-19 pneumonia. The prediction model of death risk might be a promising method to help clinicians to quickly identify and screen potential individuals who had a high-risk of death.

Diagnosis of Coronavirus Disease 2019 (COVID-19): Neither Chest CT nor RT-PCR Fits All (preprint)

BackgroundComputed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) are the recommended tools for the diagnosis of coronavirus disease 2019 (COVID-19). The present study aimed to investigate the correlation between chest CT and RT-PCR while describing the atypical CT imaging features of COVID-19.MethodsIn this study, 418 patients in Jiangsu, China, clinically diagnosed with COVID-19 from January 10 to February 17, 2020, were included. Patients who fulfilled the following conditions were evaluated further: (1) Patients had positive RT-PCR and negative CT; (2) Patients had initial negative RT-PCR and positive CT, and follow-up PT-PCR tests were positive; (3) Patients had atypical CT findings.ResultsOf the 418 initial chest CT scans, 30 (7.2%) patients had normal CT presentation, and 6 (1.4%) patients had initial negative RT-PCR results and positive CT scans. Next, 10 (2.4%) cases of patients showed atypical CT findings, including 2 case of solid nodule, 4 cases of halo sign (solid nodule or mass surrounded by ground glass opacity), and 4 cases of predominant fibrous stripes.ConclusionsFalse-negative results can be found on both chest CT and RT-PCR; hence, the diagnosis of COVID-19 should consider both CT and RT-PCR. CT manifestations, such as solitary nodule, halo sign, and pulmonary fibrous stripes, might indicate the possibility of COVID-19 to the radiologists.

Association of infected probability of COVID-19 with ventilation rates in confined spaces: a Wells-Riley equation based investigation (preprint)

Background: A growing number of epidemiological cases are proving the possibility of airborne transmission of coronavirus disease 2019 (COVID-19). Ensuring adequate ventilation rate is essential to reduce the risk of infection in confined spaces. Methods: We obtained the quantum generation rate by a COVID-19 infector with a reproductive number based fitting approach, and then estimated the association between infected probability and ventilation rate with the Wells-Riley equation. Results: The estimated quantum generation rate of COVID-19 is 14-48 /h. To ensure infected probabolity less than 1%, ventilation rate lareger than common values (100-350 m3/h and 1200-4000 m3/h for 15 minutes and 3 hours exposure, respectively) is required. If both the infector and susceptibles wear masks, the ventilation rate ensuring less than 1% infected probability is reduced to 50-180 m3/h and 600-2000 m3/h correspondingly, which is easier to be achieved by normal ventilation mode applied in some typical scenarios, including offices, classrooms, buses and aircraft cabins. Interpretation: The risk of potential airborne transmission in confined spaces cannot be ignored. Strict preventive measures that have been widely adopted should be effective in reducing the risk of airborne transmitted infection.

Complete genome characterisation of a novel coronavirus associated with severe human respiratory disease in Wuhan, China (preprint)

Emerging and re-emerging infectious diseases, such as SARS, MERS, Zika and highly pathogenic influenza present a major threat to public health1-3. Despite intense research effort, how, when and where novel diseases appear are still the source of considerable uncertainly. A severe respiratory disease was recently reported in the city of Wuhan, Hubei province, China. At the time of writing, at least 62 suspected cases have been reported since the first patient was hospitalized on December 12nd 2019. Epidemiological investigation by the local Center for Disease Control and Prevention (CDC) suggested that the outbreak was associated with a sea food market in Wuhan. We studied seven patients who were workers at the market, and collected bronchoalveolar lavage fluid (BALF) from one patient who exhibited a severe respiratory syndrome including fever, dizziness and cough, and who was admitted to Wuhan Central Hospital on December 26th 2019. Next generation metagenomic RNA sequencing4 identified a novel RNA virus from the family Coronaviridae designed WH-Human-1 coronavirus (WHCV). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that WHCV was most closely related (89.1% nucleotide similarity similarity) to a group of Severe Acute Respiratory Syndrome (SARS)-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) previously sampled from bats in China and that have a history of genomic recombination. This outbreak highlights the ongoing capacity of viral spill-over from animals to cause severe disease in humans.