Burden of carbon monoxide poisoning in China, 1990-2019: A systematic analysis of data from the global burden of disease study 2019.

Background: Carbon monoxide (CO) poisoning is one of the most common toxic occupational diseases, but related data in China are scarce. A better understanding of the burden of CO poisoning is essential for improving its management. Methods: A systematic analysis of data from the Global Burden of Disease (GBD) Study 2019 was conducted. Following the general analytical strategy used in the GBD Study 2019, the sex- and age-specific incidence and mortality rates of CO poisoning and disability-adjusted life years (DALYs) due to CO poisoning in China were analyzed. Estimated average annual percentage changes (AAPCs) in age-standardized rates were calculated by joinpoint regression analysis. The effects of age, period and cohort on the incidence of CO poisoning and DALYs due to CO poisoning were estimated by an age-period-cohort model. Results: The age-standardized incidence and mortality rates as well as DALYs of CO poisoning per 100,000 population were estimated to be 21.82 [95% uncertainty interval (UI): 15.05-29.98], 0.93 (95% UI: 0.63-1.11), and 40.92 (95% UI: 28.43-47.85), respectively, in 2019. From 1990 to 2019, the AAPCs in the age-standardized incidence significantly increased in both males and females, while the age-standardized mortality rates and DALYs significantly decreased in both males and females. The incidence of CO poisoning peaked in individuals aged 15-19 years. Males had a higher burden of CO poisoning than females. The age effect showed that the relative risks (RRs) of incident CO poisoning decreased with age among males and females and that individuals aged 15-24 years had the highest RRs. The RRs of incident CO poisoning increased with time. The cohort effect showed that the incidence increased in successive birth cohorts. Conclusions: The incidence of CO poisoning in China increased from 1990 to 2019. More attention should be given to improving the burden of CO poisoning in Chinese adolescents. The results of this study can be used by health authorities to inform preventative measures to reduce the burden of CO poisoning.

The Impact of a Health Forecasting Service on the Visits and Costs in Outpatient and Emergency Departments for COPD Patients - Shanghai Municipality, China, October 2019-April 2020.

WHAT IS ALREADY KNOWN ON THIS TOPIC?: The morbidity and mortality of chronic obstructive pulmonary disease (COPD) is associated with adverse weather and air pollution. However, COPD patients are not able to be alerted in advance of high risk environments. WHAT IS ADDED BY THIS REPORT?: This prospective controlled trial conducted in Pudong New Area of Shanghai from October 2019 to April 2020 provided evidence of COPD risk forecasting service on the reductions in visits and costs of COPD patients in outpatient and emergency departments in China for the first time. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: This study suggests that COPD risk forecasting service could be integrated into existing COPD management in public health to improve the health and economic outcomes.

Developing the relationship between metal ionic characters and ecological risk assessment screening values using QICAR.

Metals are widely released and distributed in soil and may have a negative impact on terrestrial organisms. Over the past years, a series of criteria or standards for assessing the ecological risks and toxicity of metals have been published in many countries; however, few studies have investigated their metal ionic properties and toxicity. In the present study, the ecological risk assessment screening values (ERASV) recommended by the Oregon Department of Environmental Quality were selected to investigate the correlation between metal toxicity and their ionic characters based on the hard and soft acids and bases (HSAB) concept. The results showed that more ionic characters were significantly correlated with ERASV using the HSAB theory, while only one metal ionic characteristic was correlated with ERASV in organisms. For borderline metal ions, maximum complex stability constants (log ßn) and the softness (δp) of borderline ions were correlated with ERASV, while log ßn and electronegativity (Xm) were significantly related to ERASV for borderline plus hard ions, and the boiling point (BP) and electron density (AR/AW) (AR indicates atomic radius and AW is atomic mass) were significantly related to ERASV for borderline plus soft ions. These results indicated that different metal ion characteristics play different roles in different types of metal toxicity in organisms and the mechanisms of toxicity are different. Based on these relationships, a set of quantitative ion characteristic parameter-activity relationship (QICAR) was developed. The QICAR predicted ERASV for metals that were reasonably consistent with those recommended by the Oregon Department of Environmental Quality, with differences between them generally < 2.0 orders of magnitude. However, there were discrepancies between the recommended and predicted values, and these discrepancies may be related to terrestrial geochemical properties. These soil properties should be further considered when developing QICAR models in future studies, such as soil type, organic matter, and pH. Overall, the QICAR models were able to determine the relationships between metal ionic properties and their toxicity and will be useful for assessing toxicity data on unknown toxic metals and will provide a basis for ecological assessment.

Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early Warning: 2018⁻2019 Field Testing in Southwest China.

Earthquake Early Warning (EEW) was proved to be a potential means of disaster reduction. Unfortunately, the performance of the EEW system is largely determined by the density of EEW network. How to reduce the cost of sensors has become an urgent problem for building a dense EEW. A low-cost seismic sensor integrated with a Class C MEMS accelerometer was proposed in this paper. Based on minimal structure design, the sensor's reliability was enhanced, while the costs were cut down as well. To fully reveal the performance, ten of the seismic sensors were installed and tested in Sichuan Province, southwest of China from May 2018 to February 2019. The seismic records obtained by the MNSMSs were compared with those by the traditional strong motion seismographs. The records obtained by the MNSMSs have good consistency with the data obtained by the Etnas. The MNSMSs can obtain clear seismic phases that are enough to trigger earthquake detections for EEW. By noise analysis, different channels of the same sensor and different sensors have good consistency. The tested dynamic range (over 87 dB) and useful resolution (over 14.5 bits) are completely in conformity with the designed parameters. Through real field testing, small earthquakes (M 3.1-3.6) can be detected by all three components E-W, N-S, and U-D within 50 km. In all, the low-cost seismic sensor proposed as a high-performance Class C MEMS sensor can meet the needs of dense EEW in terms of noise, dynamic range, useful resolution, reliability, and detecting capabilities.

Accelerated MR parameter mapping with a union of local subspaces constraint.

PURPOSE: A new reconstruction method for multi-contrast imaging and parameter mapping based on a union of local subspaces constraint is presented. THEORY: Subspace constrained reconstructions use a predetermined subspace to explicitly constrain the relaxation signals. The choice of subspace size ( K ) impacts the approximation error vs noise-amplification tradeoff associated with these methods. A different approach is used in the model consistency constraint (MOCCO) framework to leverage the subspace model to enforce a softer penalty. Our proposed method, MOCCO-LS, augments the MOCCO model with a union of local subspaces (LS) approach. The union of local subspaces model is coupled with spatial support constraints and incorporated into the MOCCO framework to regularize the contrast signals in the scene. METHODS: The performance of the MOCCO-LS method was evaluated in vivo on T1 and T2 mapping of the human brain and with Monte-Carlo simulations and compared against MOCCO and the explicit subspace constrained models. RESULTS: The results demonstrate a clear improvement in the multi-contrast images and parameter maps. We sweep across the model order space ( K ) to compare the different reconstructions and demonstrate that the reconstructions have different preferential operating points. Experiments on T2 mapping show that the proposed method yields substantial improvements in performance even when operating at very high acceleration rates. CONCLUSIONS: The use of a union of local subspace constraints coupled with a sparsity promoting penalty leads to improved reconstruction quality of multi-contrast images and parameter maps.