Background: Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history.Methods: We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results.Results: In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio (OR) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score (OR = 0.8650) and a history of cancer (OR = 0.9096), while a significant synergy interaction was observed between SES and EPS (OR = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis.Conclusions: Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.

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. 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. Of 476 patients with B.1.617.2 infection, 184 were unvaccinated, 105 were partially vaccinated, and 187 were fully vaccinated. A total of 42 (8.8%) patients developed severe illness, of whom, 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). Full vaccination with inactivated vaccines is highly effective in preventing severe illness in Delta variant–infected patients. However, partial vaccination does not offer clinically meaningful protection against severe disease.

The polygenic score (PGS) is an estimate of an individual’s genetic susceptibility to a specific complex trait and has been instrumental to the development of precision medicine. As an increasing number of genome-wide association studies (GWAS) have emerged, numerous sophisticated statistical and computational methods have been developed to facilitate the PGS construction. However, both the complex statistical estimation procedure and the various data formats of summary statistics and reference panel make the PGS calculation challenging and not easily accessible to researchers with limited statistical and computational backgrounds. Here, we propose PGSFusion, a webserver designed to carry out PGS construction for targeting variety of analytic requirements while requiring minimal prior computational knowledge. Implemented with well-established web development technologies, PGSFusion streamlines the construction of PGS using 17 PGS methods in four categories: 11 single-trait, one multiple-trait, two annotation-based and three cross-ancestry based methods. In addition, PGSFusion also utilizes UK Biobank data to provide two kinds of in-depth analyses for 201 complex traits: i) prediction performance evaluation to display the consistency between PGS and specific traits and the effect size of PGS in different genetic risk groups; ii) joint effect analysis to investigate the interaction between PGS and covariates, as well as the effect size of covariates in different genetic subgroups. PGSFusion benchmarks the prediction performances for different methods in one summary statistics. PGSFusion automatically identifies the required parameters in different data formats of uploaded GWAS summary statistics files, provides a selection of suitable methods, and outputs calculated PGSs and their corresponding epidemiological results. Finally, we showcase three case studies in different application scenarios, highlighting its versatility and values to researchers. Overall, PGSFusion presents an easy-to-use, effective, and extensible platform for PGS construction, promoting the accessibility and utility of PGS for researchers in the field of precision medicine. PGSFusion is freely available at http://www.pgsfusion.net/ .

Schistosomiasis remains a major public health concern in Africa, despite global efforts to eliminate the disease by 2030. This study estimates the burden, trends, and inequalities of schistosomiasis in Africa from 1990 to 2021, and projects future prevalence to inform the WHO’s elimination strategies. Data from the Global Burden of Disease Study (GBD 2021) were used to calculate annual average percentage change (AAPC) and annual percentage change (APC), with spatial global autocorrelation analysis performed to examine temporal and spatial trends. Five modeling algorithms were constructed to predict disease burden in Africa from 2022 to 2041. The age-standardized prevalences rate (ASPR) of schistosomiasis in Africa decreased from 18,495.51 per 100,000 in 1990 to 9,461.76 per 100,000 in 2021. The total number of cases, disability-adjusted life-years (DALYs), and mortality accounted for 84.25%, 87.92% and 87.28% of the global totals, respectively. ARIMA modeling predicts that by 2030, the ASPR will reach 3.99%. Despite progress, the burden remains significant, and intensified efforts are needed, particularly in high-burden regions like West Africa, to meet the WHO’s 2030 elimination targets.

The long-term benefits of direct-acting antiviral (DAA) therapy after achieving sustained virological response (SVR) remain uncertain in the Chinese population. This study evaluates the incidence of hepatocellular carcinoma (HCC), hepatic decompensation, and all-cause mortality among Chinese hepatitis C patients treated with DAAs. We included patients diagnosed since 2011 and followed them until November 1, 2022. The primary outcomes were HCC, hepatic decompensation, and mortality. Multivariable proportional hazards model was used to assess the impact of SVR and cirrhosis status. The cohort consisted of 1272 patients with SVR (92.1%) and 109 without SVR (7.9%), with a median follow-up of 61 months. The incidence of HCC was significantly lower in the SVR group (5.1 per 1000 person-years) compared to the no-SVR group (15.0 per 1000 person-years). Achieving SVR was associated with a significantly reduced risk of HCC (adjusted hazard ratio: 0.32; 95% CI 0.16–0.67). Cirrhosis was linked to an increased risk of developing HCC and hepatic decompensation. These findings highlight the importance of early DAA treatment, particularly for patients with cirrhosis.