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Background: We evaluated whether the serum procalcitonin (PCT) level could predict death in severe and critical coronavirus disease 2019 (COVID-19) patients. Methods: This study included 129 COVID-19 patients. PCT levels on admission, treatment, and death were collected. The outcomes were compared. Results: The optimum cutoff value of the PCT level determined by receiver operator characteristic curve analysis to predict all-cause death was 0.085 ng/mL, with sensitivity of 95.7% and specificity of 72.6%. Overall, 78 patients had a PCT level below 0.085 ng/mL and 51 patients had a PCT level of 0.085 ng/mL or greater. High-PCT-level patients had lower levels of lymphocytes (P = 0.001) and albumin (P = 0.002) and higher levels of creatinine (P = 0.024), D-dimer (P = 0.002), and white blood cells, neutrocytes (P < 0.001), high-sensitivity C-reactive protein (P < 0.001), interleukin-6 (P < 0.001), interleukin-8 (P = 0.001), interleukin-10 (P = 0.001), tumor necrosis factor (P < 0.001), erythrocyte sedimentation rate (P = 0.001), and ferritin (P = 0.001). During the 30-day observation period, 23 patients died. Mortality was significantly higher in high-PCT-level patients than in patients with low PCT levels (43.1% vs. 1.3%; P < 0.001). The risks of death (P < 0.0001) and ventilator use (P < 0.0001) were increased in patients with PCT levels of 0.085 ng/mL or greater. Conclusions: A PCT level of 0.085 ng/mL or greater on admission could effectively predict death and ventilator use in severe and critical COVID-19 patients. [ABSTRACT FROM AUTHOR]

Considering the high variability of Covid-19 and unknown sequelae of rebound infections. We may be caught in a long-term struggle against the virus. The evaluation and summary of past anti-epidemic policies highlight profound practical significance for either decision makers or individuals. This paper applies both theoretical and empirical approaches to study the impact of city lockdown and air pollution on Covid-19. First, we apply an extended Susceptible-Infected-Removed (SIR) model to identify the relationship between lockdown, air pollution, and Covid-19 cases. Second, we apply the Differences-in-Differences (DID) model and Poisson Pseudo-Maximum Likelihood (PPML) model to test the impact of lockdown on Covid-19, by sorting out lockdown policies implemented by cities during the epidemic. Third, we empirically analyze the impact of air pollution on Covid-19, based on daily data from 257 cities in China. Finally, we examine the mechanism by which lockdown impacts Covid-19. Newly confirmed Covid-19 cases are reduced by 31.1% nationwide (excluding Wuhan) during the lockdown period. Regions with lower air pollution experience fewer Covid-19 cases. Air pollution aggravates Covid-19, with the pollutants PM2.5, PM10, NO2, CO, and O3 having the greatest impact. The results indicate that an increase in one unit of air quality index (AQI) concentrations is associated with 1.723 more newly confirmed cases. The effects of air pollution on the spread of Covid-19 diminish as the population size increases. Lockdown can inhibit the spread of Covid-19 by reducing air pollution and population movement. [ABSTRACT FROM AUTHOR]

Introduction: COVID-19 is a coronavirus-based infectious illness that was first detected at the end of 2019 in Wuhan, China. The novel virus induces severe acute respiratory syndrome (SARS-CoV-2) and has spread globally, resulting in an ongoing pandemic. There is still a lack of evidence for direct comparison of favipiravir therapy. Network meta-analysis (NMA), may incorporate direct and indirect comparisons in a pooled computation while depending on strong assumptions and premises. This study provides evidence-based recommendations on the safety of currently used clinical pharmacological treatments compared to favipiravir for COVID-19 patients. Methodology: We conducted a systematic review and Bayesian NMA. We searched the primary databases and clinical trials center for reports of short-term, randomized controlled trials (RCTs) of favipiravir for COVID-19 treatment. The primary endpoints here considered were any adverse events observed or reported during the treatment cycle with estimates of odds ratio (OR) and 95% confidence interval (CI), until November 6, 2021. Results: Between January 2020 and July 2021, 908 individuals were randomly assigned to one of the seven active prescription medication regimens or placebo in this study, generating seven direct comparisons on 12 data points. The safety of favipiravir over the four clinically efficacious monotherapies or combinations including tocilizumab, arbidol, lopinavir + ritonavir, and chloroquine remained unknown due to the lack of a significant difference and the limited sample size. Conclusions: Overall, comparative rankings could assist doctors and guideline developers in decision-making. We have also concluded that the safety of favipiravir requires further attention. [ABSTRACT FROM AUTHOR]