Enhanced antibody responses in fully vaccinated individuals against pan-SARS-CoV-2 variants following Omicron breakthrough infection.

Omicron has become the globally dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, creating additional challenges due to its ability to evade neutralization. Here, we report that neutralizing antibodies against Omicron variants are undetected following COVID-19 infection with ancestral or past SARS-CoV-2 variant viruses or after two-dose mRNA vaccination. Compared with two-dose vaccination, a three-dose vaccination course induces broad neutralizing antibody responses with improved durability against different SARS-CoV-2 variants, although neutralizing antibody titers against Omicron remain low. Intriguingly, among individuals with three-dose vaccination, Omicron breakthrough infection substantially augments serum neutralizing activity against a broad spectrum of SARS-CoV-2 variants, including Omicron variants BA.1, BA.2, and BA.5. Additionally, after Omicron breakthrough infection, memory T cells respond to the spike proteins of both ancestral and Omicron SARS-CoV-2 by producing cytokines with polyfunctionality. These results suggest that Omicron breakthrough infection following three-dose mRNA vaccination induces pan-SARS-CoV-2 immunity that may protect against emerging SARS-CoV-2 variants of concern.

Real-time forecasting of the COVID 19 using fuzzy grey Markov: a different approach in decision-making

The ongoing epidemic SARS-CoV-2 named Corona Virus Disease (COVID-19) is highly infectious and subsequently spread all over the world affecting millions of people. Humans have never seen such a deadly disease so far, and as there is no specific drug or vaccination, the mortality rate of the disease has been increasing exponentially. This current situation exacerbated people’s restlessness and fear. Because of this pandemic, the world is travelling on a different path. This world has recovered from many disasters, but this is entirely a different situation. Today’s world is struggling in many ways to get rid of this disease. On the other hand, the number of people recovering from this disease gives us comfort. Yet, we have to take urgent precautionary measures to control this disease in all possible ways. Therefore, forecasting is one of the ways to take the necessary precautionary measures. In this paper, using fuzzy–grey–Markov model, we predict the number of affected and recovered patient count, death count using real-time data in different approaches and compared with the real data. The study concludes with important recommendations for the Indian government to manage the COVID 19 critical situation in advance.

Discovery and Full Genome Characterization of SARS-CoV-2 in Stool Specimen from a Recovered Patient, China.

SARS-CoV-2 was found in a recovered patient's stool specimen by combining quantitative reverse transcription PCR (qRT-PCR) and genome sequencing. The patient was virus positive in stool specimens for at least an additional 15 days after he was recovered, whereas respiratory tract specimens were negative. The discovery of the complete genome of SARS-CoV-2 in the stool sample of the recovered patient demonstrates a cautionary warning that the potential mode of the virus transmission cannot be excluded through the fecal-oral route after viral clearance in the respiratory tract.

Pulmonary fibrosis and its related factors in discharged patients with new corona virus pneumonia: a cohort study.

BACKGROUND: Thousands of Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals Persistent follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis. METHODS: This study involves 462 laboratory-confirmed patients with COVID-19 who were admitted to Shenzhen Third People's Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 to 150 days after the onset of the disease, and lung function tests were conducted about three months after the onset. The risk factors affecting the persistence of pulmonary fibrosis were identified through regression analysis and the prediction model of the persistence of pulmonary fibrosis was established. RESULTS: Parenchymal bands, irregular interfaces, reticulation and traction bronchiectasis were the most common CT features in all COVID-19 patients. During the 0-30, 31-60, 61-90, 91-120 and > 120 days after onset, 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. More than half of the COVID-19 patients revealed abnormal conditions in lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups. CONCLUSIONS: Persistent pulmonary fibrosis was more likely to develop in patients with older age, higher BMI, severe/critical condition, fever, a longer viral clearance time, pre-existing disease and delayed hospitalization. Fibrosis developed in COVID-19 patients could be reversed in about a third of the patients after 120 days from onset. The pulmonary function of less than half of COVID-19 patients could turn to normal condition after three months from onset. An effective prediction model with an average area under the curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.