Detection of a novel coronavirus (SARS-CoV-2) by real-time reverse transcription-polymerase chain reaction, China, 2020 (preprint)

Background: During the outbreak of unexplained pneumonia in the city of Wuhan in the late December, 2019, a novel coronavirus named SARS-CoV-2 was identified as the cause of this outbreak.Methods: A real-time polymerase chain reaction, which targets the orf1ab gene of viral genome, was established to detect and identify the SARS-CoV-2. We used this assay to screen 309 samples from persons with suspected SARS-CoV-2 infection in Wuhan. Then 6 close-phylogenic coronaviruses and 7 viruses which could cause pneumonia were detected. Moreover, 57 clinical samples infected with other viruses and 77 healthy samples were also tested.Results: The limit of detection of the assay was 6.25 copies per reaction in the detection of cRNA transcribed in vitro. The results of detection of throat and fecal swabs from persons with suspected SARS-CoV-2 infection showed throat swabs were more sensitive than fecal swabs during the first 15 days after onset of symptoms (throat: 56.80%, fecal: 30.43%), while the situation was reversed after 15 days (throat: 20.83%, fecal: 27.58%). And matched pair tests suggested the sputum samples had higher virus loads than throat swabs in the patients (P < 0.05). There was no cross-reaction when we detected the inactive culture of six other coronaviruses (human coronavirus 229E, NL63, OC43, HKU1, SARS-CoV, MERS-CoV) and seven other viruses (influenza virus A H1N1, influenza virus A H3N2, influenza virus B, parainfluenza viruses 1, 2, and 3; and respiratory syncytial virus). Besides, 27 BALF samples from pneumonia patients infected with human coronavirus 229E, OC43, HKU1 or human adenovirus 7, 30 throat swabs from patients infected with H1N1 and 77 throat swabs from healthy people tested negative by this assay.Conclusions: The results indicated that the assay specifically and sensitively detected the SARS-CoV-2.

Effect of large-scale testing platform in prevention and control of the COVID-19 pandemic: an empirical study with a novel numerical model (preprint)

Background: China adopted an unprecedented province-scale quarantine since January 23rd 2020, after the novel coronavirus (COVID-19) broke out in Wuhan in December 2019. Responding to the challenge of limited testing capacity, large-scale standardized and fully-automated laboratory (Huo-Yan) was built as an ad-hoc measure. There was so far no empirical data or mathematical model to reveal the impact of the testing capacity improvement since the quarantine. Methods: We integrated public data released by the Health Commission of Hubei Province and Huo-Yan Laboratory testing data into a novel differential model with non-linear transfer coefficients and competitive compartments, to evaluate the trends of suspected cases under different nucleic acid testing capacities. Results: Without the establishment of Huo-Yan, the suspected cases would increased by 47% to 33,700, the corresponding cost of the quarantine would be doubled, and the turning point of the increment of suspected cases and the achievement of "daily settlement" (all daily new discovered suspected cases were diagnosed according to the nucleic acid testing results) would be delayed for a whole week and 11 days. If the Huo-Yan Laboratory could ran at its full capacity, the number of suspected cases could started to decrease at least a week earlier, the peak of suspected cases would be reduced by at least 44% and the quarantine cost could be reduced by more than 72%. Ideally, if a daily testing capacity of 10,500 could achieved immediately after the Hubei lockdown, "daily settlement" for all suspected cases would be achieved immediately. Conclusions: Large-scale and standardized clinical testing platform with nucleic acid testing, high-throughput sequencing and immunoprotein assessment capabilities need to be implemented simultaneously in order to maximize the effect of quarantine and minimize the duration and cost. Such infrastructure like Huo-Yan, is of great significance for the early prevention and control of infectious diseases for both common times and emergencies.

Multiple approaches for massively parallel sequencing of HCoV-19 genomes directly from clinical samples (preprint)

COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.