Survival and disease burden analyses of occupational pneumoconiosis during 1958-2021 in Huangshi city, China: a retrospective cohort study.

BACKGROUND: Pneumoconiosis, a chronic disease stemming from prolonged inhalation of dust particles, stands as a significant global burden of occupational diseases. This study aims to investigate the survival outcomes of pneumoconiosis patients in Huangshi city, China, while also evaluating the disease burden on afflicted patients. METHODS: Data for this study were sourced from the Huangshi Center for Disease Control and Prevention. Survival analyses of pneumoconiosis patients were conducted employing life tables and the Kaplan-Meier method. The Cox proportional hazards models were deployed to identify factors influencing pneumoconiosis patients' survival duration. Competing risks models were employed to confirm the validity of the model outcomes. Additionally, in the disease burden assessment, disability-adjusted life years (DALYs) were computed for various demographic groups and time frames. RESULTS: A total of 5,641 pneumoconiosis cases, diagnosed in Huangshi City, Hubei Province between 1958 and 2021, were incorporated into the cohort analysis. The probability of mortality and the risk ratio increased with advancing age. Notably, the median survival time of stage III pneumoconiosis patients was significantly shorter compared with those in stages I and II. The Cox proportional hazards model and competing risks analyses underscored several significant factors influencing survival time, including dust exposure duration (HR = 1.197, 95% CI: 1.104-1.298), age at first diagnosis (HR = 3.149, 95% CI: 2.961-3.349), presence of silicosis (HR = 1.378, 95% CI: 1.254-1.515), and stage II-III pneumoconiosis (HR = 1.456, 95% CI: 1.148-1.848). Cumulatively, DALYs amounted to 7,974.35 person-years, with an average of 1.41 person-years. The period between 2000 and 2019 witnessed the highest disease burden. CONCLUSION: Our findings highlight the urgent need for improved prevention, earlier detection, and more effective management strategies for the occupational pneumoconiosis population. This study not only underscores the persistent issue of pneumoconiosis in industrial environments but also serves as a crucial call to action for policymakers and healthcare providers.

Population impact of fine particulate matter on tuberculosis risk in China: a causal inference.

BACKGROUND: Previous studies have suggested the potential association between air pollution and tuberculosis incidence, but this association remains inconclusive and evidence to assess causality is particularly lacking. We aimed to draw causal inference between fine particulate matter less than 2.5 µm in diameter (PM2.5) and tuberculosis in China. METHODS: Granger causality (GC) inference was performed within vector autoregressive models at levels and/or first-differences using annual national aggregated data during 1982-2019, annual provincial aggregated data during 1982-2019 and monthly provincial aggregated data during 2004-2018. Convergent cross-mapping (CCM) approach was used to determine the backbone nonlinear causal association based on the monthly provincial aggregated data during 2004-2018. Moreover, distributed lag nonlinear model (DLNM) was applied to quantify the causal effects. RESULTS: GC tests identified PM2.5 driving tuberculosis dynamics at national and provincial levels in Granger sense. Empirical dynamic modeling provided the CCM causal intensity of PM2.5 effect on tuberculosis at provincial level and demonstrated that PM2.5 had a positive effect on tuberculosis incidence. Then, DLNM estimation demonstrated that the PM2.5 exposure driven tuberculosis risk was concentration- and time-dependent in a nonlinear manner. This result still held in the multi-pollutant model. CONCLUSIONS: Causal inference showed that PM2.5 exposure driving tuberculosis, which showing a concentration gradient change. Air pollutant control may have potential public health benefit of decreasing tuberculosis burden.

Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China.

Background: Increasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China. Methods: We collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model. Results: There were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 µg/m3 increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04-1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5), 1.05 (95% CI: 1.01-1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 µm (PM10), and 1.11 (95%CI: 1.04-1.19, lag 10 months) for nitrogen dioxide (NO2). Ozone (O3) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model. Conclusions: Our study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.

Population-level health and economic impacts of introducing Vaccae vaccination in China: a modelling study.

INTRODUCTION: Given the ageing epidemic of tuberculosis (TB), China is facing an unprecedented opportunity provided by the first clinically approved next-generation TB vaccine Vaccae, which demonstrated 54.7% efficacy for preventing reactivation from latent infection in a phase III trial. We aim to assess the population-level health and economic impacts of introducing Vaccae vaccination to inform policy-makers. METHODS: We evaluated a potential national Vaccae vaccination programme in China initiated in 2024, assuming 20 years of protection, 90% coverage and US$30/dose government contract price. An age-structured compartmental model was adapted to simulate three strategies: (1) no Vaccae; (2) mass vaccination among people aged 15-74 years and (3) targeted vaccination among older adults (60 years). Cost analyses were conducted from the healthcare sector perspective, discounted at 3%. RESULTS: Considering postinfection efficacy, targeted vaccination modestly reduced TB burden (~20%), preventing cumulative 8.01 (95% CI 5.82 to 11.8) million TB cases and 0.20 (0.17 to 0.26) million deaths over 2024-2050, at incremental cost-effectiveness ratio of US$4387 (2218 to 10 085) per disability adjusted life year averted. The implementation would require a total budget of US$22.5 (17.6 to 43.4) billion. In contrast, mass vaccination had a larger bigger impact on the TB epidemic, but the overall costs remained high. Although both preinfection and postinfection vaccine efficacy type might have a maximum impact (>40% incidence rate reduction in 2050), it is important that the vaccine price does not exceed US$5/dose. CONCLUSION: Vaccae represents a robust and cost-effective choice for TB epidemic control in China. This study may facilitate the practice of evidence-based strategy plans for TB vaccination and reimbursement decision making.

Combined impacts of environmental and socioeconomic covariates on HFMD risk in China: A spatiotemporal heterogeneous perspective.

BACKGROUND: Understanding geospatial impacts of multi-sourced influencing factors on the epidemic of hand-foot-and-mouth disease (HFMD) is of great significance for formulating disease control policies tailored to regional-specific needs, yet the knowledge is very limited. We aim to identify and further quantify the spatiotemporal heterogeneous effects of environmental and socioeconomic factors on HFMD dynamics. METHODS: We collected monthly province-level HFMD incidence and related environmental and socioeconomic data in China during 2009-2018. Hierarchical Bayesian models were constructed to investigate the spatiotemporal relationships between regional HFMD and various covariates: linear and nonlinear effects for environmental covariates, and linear effects for socioeconomic covariates. RESULTS: The spatiotemporal distribution of HFMD cases was highly heterogeneous, indicated by the Lorenz curves and the corresponding Gini indices. The peak time (R2 = 0.65, P = 0.009), annual amplitude (R2 = 0.94, P<0.001), and semi-annual periodicity contribution (R2 = 0.88, P<0.001) displayed marked latitudinal gradients in Central China region. The most likely cluster areas for HFMD were located in south China (Guangdong, Guangxi, Hunan, Hainan) from April 2013 to October 2017. The Bayesian models achieved the best predictive performance (R2 = 0.87, P<0.001). We found significant nonlinear associations between monthly average temperature, relative humidity, normalized difference vegetation index and HFMD transmission. Besides, population density (RR = 1.261; 95%CI, 1.169-1.353), birth rate (RR = 1.058; 95%CI, 1.025-1.090), real GDP per capita (RR = 1.163; 95%CI, 1.033-1.310) and school vacation (RR = 0.507; 95%CI, 0.459-0.559) were identified to have positive or negative effects on HFMD respectively. Our model could successfully predict months with HFMD outbreaks versus non-outbreaks in provinces of China from Jan 2009 to Dec 2018. CONCLUSIONS: Our study highlights the importance of refined spatial and temporal data, as well as environmental and socioeconomic information, on HFMD transmission dynamics. The spatiotemporal analysis framework may provide insights into adjusting regional interventions to local conditions and temporal variations in broader natural and social sciences.

Investigation on activated semi-coke desulfurization.

An activated semi-coke with industrial-scale size was prepared by high-pressure hydrothermal chemistry activation, HNO3 oxidation and calcination activation in proper order from Inner Mongolia Zhalainuoer semi-coke, which is rich in resource and cheap in sale. SO2 adsorption capacity on this activated semi-coke was assessed in the fixed bed in the temperature range of 60-170 degrees C, space velocity range of 500-1300 h(-1), SO2 concentration of 1000-3000 ppmv, and N2 as balance. The surface area, elemental and proximate analysis for both raw semi-coke and activated semi-cokes were measured. The experimental results showed that the activated semi-coke has a high adsorption capacity for sulfur dioxide than the untreated semi-coke. This may be the result of increase of surface area on activated semi-coke and surface oxygen functional groups with basicity characteristics. Comparison to result of FTIR, it is known that group of -C-O-C- may be active center of SO2 catalytic adsorption on activated semi-coke.