Persistence and clearance of viral RNA in 2019 novel coronavirus disease rehabilitation patients.

BACKGROUND: A patient's infectivity is determined by the presence of the virus in different body fluids, secretions, and excreta. The persistence and clearance of viral RNA from different specimens of patients with 2019 novel coronavirus disease (COVID-19) remain unclear. This study analyzed the clearance time and factors influencing 2019 novel coronavirus (2019-nCoV) RNA in different samples from patients with COVID-19, providing further evidence to improve the management of patients during convalescence. METHODS: The clinical data and laboratory test results of convalescent patients with COVID-19 who were admitted to from January 20, 2020 to February 10, 2020 were collected retrospectively. The reverse transcription polymerase chain reaction (RT-PCR) results for patients' oropharyngeal swab, stool, urine, and serum samples were collected and analyzed. Convalescent patients refer to recovered non-febrile patients without respiratory symptoms who had two successive (minimum 24 h sampling interval) negative RT-PCR results for viral RNA from oropharyngeal swabs. The effects of cluster of differentiation 4 (CD4)+ T lymphocytes, inflammatory indicators, and glucocorticoid treatment on viral nucleic acid clearance were analyzed. RESULTS: In the 292 confirmed cases, 66 patients recovered after treatment and were included in our study. In total, 28 (42.4%) women and 38 men (57.6%) with a median age of 44.0 (34.0-62.0) years were analyzed. After in-hospital treatment, patients' inflammatory indicators decreased with improved clinical condition. The median time from the onset of symptoms to first negative RT-PCR results for oropharyngeal swabs in convalescent patients was 9.5 (6.0-11.0) days. By February 10, 2020, 11 convalescent patients (16.7%) still tested positive for viral RNA from stool specimens and the other 55 patients' stool specimens were negative for 2019-nCoV following a median duration of 11.0 (9.0-16.0) days after symptom onset. Among these 55 patients, 43 had a longer duration until stool specimens were negative for viral RNA than for throat swabs, with a median delay of 2.0 (1.0-4.0) days. Results for only four (6.9%) urine samples were positive for viral nucleic acid out of 58 cases; viral RNA was still present in three patients' urine specimens after throat swabs were negative. Using a multiple linear regression model (F = 2.669, P = 0.044, and adjusted R = 0.122), the analysis showed that the CD4+ T lymphocyte count may help predict the duration of viral RNA detection in patients' stools (t = -2.699, P = 0.010). The duration of viral RNA detection from oropharyngeal swabs and fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (15 days vs. 8.0 days, respectively; t = 2.550, P = 0.013) and the duration of viral RNA detection in fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (20 days vs. 11 days, respectively; t = 4.631, P < 0.001). There was no statistically significant difference in inflammatory indicators between patients with positive fecal viral RNA test results and those with negative results (P > 0.05). CONCLUSIONS: In brief, as the clearance of viral RNA in patients' stools was delayed compared to that in oropharyngeal swabs, it is important to identify viral RNA in feces during convalescence. Because of the delayed clearance of viral RNA in the glucocorticoid treatment group, glucocorticoids are not recommended in the treatment of COVID-19, especially for mild disease. The duration of RNA detection may relate to host cell immunity.

The origin of novel avian influenza A (H7N9) and mutation dynamics for its human-to-human transmissible capacity.

In February 2013, H7N9 (A/H7N9/2013_China), a novel avian influenza virus, broke out in eastern China and caused human death. It is a global priority to discover its origin and the point in time at which it will become transmittable between humans. We present here an interdisciplinary method to track the origin of H7N9 virus in China and to establish an evolutionary dynamics model for its human-to-human transmission via mutations. After comparing influenza viruses from China since 1983, we established an A/H7N9/2013_China virus evolutionary phylogenetic tree and found that the human instances of virus infection were of avian origin and clustered into an independent line. Comparing hemagglutinin (HA) and neuraminidase (NA) gene sequences of A/H7N9/2013_China viruses with all human-to-human, avian, and swine influenza viruses in China in the past 30 years, we found that A/H7N9/2013_China viruses originated from Baer's Pochard H7N1 virus of Hu Nan Province 2010 (HA gene, EPI: 370846, similarity with H7N9 is 95.5%) and duck influenza viruses of Nanchang city 2000 (NA gene, EPI: 387555, similarity with H7N9 is 97%) through genetic re-assortment. HA and NA gene sequence comparison indicated that A/H7N9/2013_China virus was not similar to human-to-human transmittable influenza viruses. To simulate the evolution dynamics required for human-to-human transmission mutations of H7N9 virus, we employed the Markov model. The result of this calculation indicated that the virus would acquire properties for human-to-human transmission in 11.3 years (95% confidence interval (CI): 11.2-11.3, HA gene).