Background The SARS-CoV-2 B.1.617.2 (Delta) variant has caused a new surge in the number of COVID-19 cases. The effectiveness of inactivated vaccines against this variant is not fully understood. Methods Using data from a recent large-scale outbreak of B.1.617.2 SARS-COV-2 infection in Jiangsu, China, we conducted a real-world study to explore the effect of inactivated vaccine immunization on the course of disease in patients infected with the Delta variant. Results Out of 476 patients with B.1.617.2 infection, 184 were unvaccinated, 105 were partially vaccinated, and 187 were fully vaccinated. Forty-two (8.8%) patients developed severe illness, of which 27 (14.7%), 13 (12.4%), and 2 (1.1%) were unvaccinated, partially vaccinated, and fully vaccinated, respectively ( P <0.001). All 15 (3.2%) patients who required mechanical ventilation were unvaccinated. After adjusting for age, sex, and comorbidities, fully vaccinated patients had an 88% reduced risk of progressing to severe illness (OR adjusted : 0.12, 95% CI: 0.02-0.45). However, this protective effect was not observed in partially vaccinated patients (OR adjusted : 1.11, 95% CI: 0.51-2.36). Full immunization offered 100% protection from severe illness among women. The effect of the vaccine was potentially affected by underlying medical conditions (OR adjusted : 0.26, 95% CI: 0.03-1.23). Conclusion Full vaccination with inactivated vaccines is highly effective at preventing severe illness in Delta variant-infected patients. However, partial vaccination does not offer clinically meaningful protection against severe disease.
Objectives : Previous studies have suggested a relationship between outdoor air pollution and the risk of coronavirus disease 2019 (COVID-19). However, there is a lack of data related to the severity of disease, especially in China. This study aimed to explore the association between short-term exposure to outdoor particulate matter (PM) and the risk of severe COVID-19. Methods : We recruited patients diagnosed with COVID-19 during a recent large-scale outbreak in eastern China caused by the Delta variant. We collected data on meteorological factors and ambient air pollution during the same time period and in the same region where the cases occurred and applied a generalized additive model (GAM) to analyze the effects of short-term ambient PM exposure on the risk of severe COVID-19. Results : A total of 476 adult patients with confirmed COVID-19 were recruited, of which 42 (8.82%) had severe disease. With a unit increase in PM 10 , the risk of severe COVID-19 increased by 81.70% (95% confidence interval [CI]: 35.45, 143.76) at a lag of 0-7 days, 86.04% (95% CI: 38.71, 149.53) at a lag of 0-14 days, 76.26% (95% CI: 33.68, 132.42) at a lag of 0-21 days, and 72.15% (95% CI: 21.02, 144.88) at a lag of 0-28 days. The associations remained significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models. With a unit increase in PM 2.5 , the risk of severe COVID-19 increased by 299.08% (95% CI: 92.94, 725.46) at a lag of 0-7 days, 289.23% (95% CI: 85.62, 716.20) at a lag of 0-14 days, 234.34% (95% CI: 63.81, 582.40) at a lag of 0-21 days, and 204.04% (95% CI: 39.28, 563.71) at a lag of 0-28 days. The associations were still significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models. Conclusions : Our results indicated that short-term exposure to outdoor PM was positively related to the risk of severe COVID-19, and that reducing air pollution may contribute to the control of COVID-19.
Uridine 5’-diphospho-glucuronosyl-transferase 1A1 (UGT1A1) plays an important role in the biliary excretion of bilirubin, suggesting genetic polymorphisms of UGT1A1 may have an impact on bile acid metabolism, which may be related to the development of anti-tuberculosis drug-induced liver injury (ATLI). This study explores the associations between genetic polymorphisms of UGT1A1 and ATLI in a Chinese anti-tuberculosis population. A 1:2 matched case–control study was conducted among 290 ATLI cases and 580 controls, of which causality assessment of ATLI cases was based on the updated Roussel Uclaf Causality Assessment Method (RUCAM). Conditional logistic regression was applied to calculate odds ratio (OR) and 95% confidence intervals (CIs), with weight and use of hepatoprotectant as covariates. The Bonferroni correction was used to adjust P values for multiple testing. Compared with those carrying rs6719561 TT genotype, patients with TC genotype had lower risk of ATLI (adjusted OR = 0.723, 95% CI: 0.531–0.985, P = 0.040). The haplotype TAG (rs3755319-rs2003569-rs4148323) could marginally significantly increase the risk of ATLI (adjusted OR = 5.071, 95% CI: 1.007–25.531, P = 0.049), while haplotype TC (rs4148329-rs6719561) could reduce the risk of ATLI (adjusted OR = 0.719, 95% CI: 0.527–0.982, P = 0.038). Patients with polymorphisms at rs4148328 or rs3755319 were at a reduced risk of moderate and severe liver injury under different genetic models. Based on this case–control study, genetic polymorphisms of UGT1A1 may be associated with susceptibility to ATLI in the Chinese anti-tuberculosis population.
Background The Global Health Security (GHS) Index has been developed to measure a country’s capacity to cope with a public health emergency but evidence for whether it corresponds to the response to a global pandemic is lacking. In the current study, we performed a multidimensional association analysis to explore the correlation between the GHS Index and COVID-19-associated morbidity, mortality, and disease increase rate (DIR) in 178 countries (regions). Methods GHS Index and COVID-19 epidemic data were extracted from online databases, including total cases per million (TCPM), total deaths per million (TDPM), and daily growth rate. We applied the Spearman correlation coefficient to describe the strength of the association between the GHS Index, sociological characteristics, and the epidemic situation of COVID-19. DIRs were compared, and the impact of the GHS Index on the DIR by the time of “lockdown” was visualized. Results The overall GHS Index was positively correlated with TCPM and TDPM, with coefficients of 0.34 and 0.41, respectively. Countries categorized into different GHS Index tiers had different DIRs before implementing “lockdown” measures. However, after implementing “lockdown” measures, no significant difference was observed between countries in the middle and upper tiers. The correlation between GHS Index and DIR was positive five days before “lockdown” measures were taken, but it became negative 13 days later. Conclusions The GHS Index has limited value in assessing a country's capacity to respond to a global pandemic. Nevertheless, it has potential value in determining the country’s ability to cope with a local epidemic situation.
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