Characteristics of patients with SARS-COV-2 PCR re-positivity after recovering from COVID-19.

The purpose of this study was to analyse the clinical characteristics of patients with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) PCR re-positivity after recovering from coronavirus disease 2019 (COVID-19). Patients (n = 1391) from Guangzhou, China, who had recovered from COVID-19 were recruited between 7 September 2021 and 11 March 2022. Data on epidemiology, symptoms, laboratory test results and treatment were analysed. In this study, 42.7% of recovered patients had re-positive result. Most re-positive patients were asymptomatic, did not have severe comorbidities, and were not contagious. The re-positivity rate was 39%, 46%, 11% and 25% in patients who had received inactivated, mRNA, adenovirus vector and recombinant subunit vaccines, respectively. Seven independent risk factors for testing re-positive were identified, and a predictive model was constructed using these variables. The predictors of re-positivity were COVID-19 vaccination status, previous SARs-CoV-12 infection prior to the most recent episode, renal function, SARS-CoV-2 IgG and IgM antibody levels and white blood cell count. The predictive model could benefit the control of the spread of COVID-19.

Public Health Measures During the COVID-19 Pandemic Reduce the Spread of Other Respiratory Infectious Diseases.

Background: Public health measures (such as wearing masks, physical distancing, and isolation) have significantly reduced the spread of the coronavirus disease-2019 (COVID-19), but the impact of public health measures on other respiratory infectious diseases is unclear. Objective: To assess the correlation between public health measures and the incidence of respiratory infectious diseases in China during the COVID-19 pandemic. Methods: We collected the data from the National Health and Construction Commission in China on the number of patients with six respiratory infectious diseases (measles, tuberculosis, pertussis, scarlet fever, influenza, and mumps) from 2017 to 2020 and assessed the correlation between public health measures and the incidence of respiratory infectious diseases. Finally, we used the data of the six respiratory infectious diseases in 2021 to verify our results. Results: We found public health measures significantly reduced the incidence of measles (p = 0.002), tuberculosis (p = 0.002), pertussis (p = 0.004), scarlet fever (p = 0.002), influenza (p = 0.034), and mumps (p = 0.002) in 2020, and prevented seasonal peaks. Moreover, the effects of public health measures were most marked during the peak seasons for these infections. Of the six respiratory infectious diseases considered, tuberculosis was least affected by public health measures. Conclusion: Public health measures were very effective in reducing the incidence of respiratory infectious diseases, especially when the respiratory infectious diseases would normally have been at their peak.