Occupational Safety And Health Administration Research Articles

Revolutionizing construction safety: introducing a cutting-edge virtual reality interactive system for training US construction workers to mitigate fall hazards

The construction industry is fraught with hazards, chief among them being the risk of falls from elevated positions, which are a leading cause of both fatalities and injuries among workers. Despite the prevalence of traditional safety training methods, their effectiveness in reducing fall risks remains limited. To solve this issue, this study proposes the adoption of interactive VR technologies to provide construction workers with immersive training experiences in the critical domain of fall safety. This approach not only ensures adherence to the Occupational Safety and Health Administration (OSHA) requirements but also leverages VR’s immersive capabilities to create a comprehensive and effective learning tool. To evaluate the proposed system’s efficacy, the researchers conducted an empirical assessment involving eighty-two construction workers from two small enterprises. Participants were divided into two groups: one receiving traditional training and the other undergoing VR-based instruction. Both groups underwent pre- and post-training evaluations comprising six targeted questions designed to measure the impact of each training method on their understanding and awareness of fall safety practices. The comparative analysis revealed no significant differences in baseline knowledge between the two groups prior to the training interventions. However, post-training evaluations demonstrated a notable improvement in the VR group, with a significant decrease in the number of incorrect responses, in stark contrast to the group subjected to traditional training methods. Statistical analysis further confirmed the superiority of VR training in enhancing participants’ knowledge. This was quantified by a p-value of 0.0016, indicating a high level of statistical significance well below the conventional threshold of 0.05. This study highlights the significant advantages of VR technology in construction safety training, demonstrating its superiority over traditional training methods in terms of knowledge retention and practical application. The results strongly support the wider adoption of VR in safety training, indicating its potential to enhance safety outcomes in the construction sector.

Hydrogen sulfide chemiresistive sensor based on swift heavy ion irradiated cerium-based metal–organic framework/graphene oxide composite

Herein, we report ultrahigh sensitive and selective hydrogen sulfide (H2S) chemiresistive sensor using SHI irradiated cerium-based metal–organic framework (MOF)/graphene oxide composite (Ce-BTC/GO). The solvothermal synthesized Ce-BTC/GO coated on an indium tin oxide (ITO) electrode, irradiated by the 100MeV Au+ ion at the fluence rate 5×1010ions/sec, 5×1011ions/sec and 5×1012ions/sec has been tested for chemiresistive sensing of H2S. As irradiated, Ce-BTC/GO was multi-parametrically tested for XRD, FE-SEM, FTIR spectroscopy, Raman spectroscopy and I-V characteristics for its structural, morphological, spectroscopic and electrical characteristics. The result reveals that the irradiation treatment greatly affects the electric characteristics of the GO, achieving dramatic conductivity modulation in the presence of H2S gas, it also creates the surface sites for the H2S absorption and hence shows excellent real-time sensing performance below the maximum residue limit established by OSHA (Occupational Safety and Health Administration). SHI irradiated Ce-BTC/GO sensor also shows excellent response/recovery time, ultrahigh reproducibility, good repeatability and stability at room temperature. The sensor allows the detection of H2S with a sensitivity of 54.70% in a concentration range of 10 -100 ppm with a limit of detection 10 ppm.

Severity Analysis for Occupational Heat-related Injury Using the Multinomial Logit Model

BackgroundWorkers are often exposed to hazardous heat due to their work environment, leading to various injuries. As a result of climate change, heat-related injuries (HRIs) are becoming more problematic. This study aims to identify critical contributing factors to the severity of occupational HRIs. MethodsThis study analyzed historical injury reports from the Occupational Safety and Health Administration (OSHA). Contributing factors to the severity of HRIs were identified using text mining and model-free machine learning methods. The Multinomial Logit Model (MNL) was applied to explore the relationship between impact factors and HRIs severity. ResultsThe results indicated a higher risk of fatal HRIs among middle-aged, older, and male workers, particularly in the construction, service, manufacturing, and agriculture industries. In addition, a higher heat index (HI), collapses, heart attacks, and fall accidents increased the severity of HRIs, while symptoms such as dehydration, dizziness, cramps, faintness, and vomiting reduced the likelihood of fatal HRIs. ConclusionsThe severity of HRIs was significantly influenced by factors like workers’ age, gender, industry type, HI, symptoms, and secondary injuries. The findings underscore the need for tailored preventive strategies and training across different worker groups to mitigate HRIs risks.

A comparison of neck and shoulder postures in symptomatic and asymptomatic female office workers in the actual work environment

ObjectiveThe present study aimed to compare the static and dynamic sitting posture during computer work among symptomatic and asymptomatic office workers in actual work environment. MethodsSeventy female office workers were divided into two groups: asymptomatic (n = 35) and symptomatic (n = 35). Subsequent to this classification, adjustments to their respective workstations were implemented in accordance with Occupational Safety and Health Administration (OSHA) guidelines. The assessment of neck (CV) and shoulder (FS) angles were conducted during both a typical seated posture and at intervals of 20 min over a duration of 3 h of computer work. ResultThe asymptomatic group had a range of age from 26 to 40 years, a BMI of 21.11 ± 2.14, and a working experience ranged from 1 to 16 years. In contrast, the symptomatic group had an age range from 24 to 40 years, a BMI of 21.12 ± 2.27, and a working experience ranged from 3 to 16 years. During static sitting posture, significant differences were observed in both CV (p = 0.01) and FS angles (p = 0.00) between the two groups. Additionally, during computer work sessions lasting for 3 h, a significant time effect (p = 0.00) was noted for the CV angle. Furthermore, the FS angle exhibited significant group (p = 0.00), time (p = 0.00), and interaction (p = 0.00) effects during work. ConclusionThis study underscores the development of neck flexion during prolong working in both groups. In addition, asymptomatic group experienced a progression more rounded shoulder during a 3-h working period. Prolonged periods of sitting and computer use appear to have adverse effects on neck and shoulder health, underlining the importance of implementing measures to mitigate these effects.

Working With the Strategy Master-Dr Michael Silverstein MD, MPH [1945-2024].

New Solutions offers a short memorial statement noting the January 2, 2024, death of Dr Michael Silverstein, an internationally known leader in the field of occupational health and safety. Dr Silverstein spent 53 years specializing in the fields of occupational medicine, public health, and general preventive medicine. He was the Assistant Director for Occupational Health and Safety with the United Automobile Workers Union for 15 years. He served as the Director of Policy for the U.S. Occupational Safety and Health Administration (OSHA) during the Clinton Administration. He later served as Director of the Washington State OSHA program for 10 years and was the Assistant Director for Industrial Safety and Health in the Washington State Department of Labor and Industries. A long-time friend of New Solutions, Dr Silverstein was the journal's first Scientific Solutions editor.

Factors influencing safety behaviours of construction tradesmen

The Occupational Safety and Health Administration (OSHA) observed that 90% of fatalities arise from the familiar ‘fatal four’- falls, electrocutions, stuck-bys and caught –in between. American Industrial Hygiene Association (AIHA) also fingered other four hazards due to exposures on construction jobs not paid attention to yet far more construction workers suffer chronic injuries or illness. These infamous concerns make research findings on factors influencing safety behaviours of construction workers ever relevant and this is the focus of this paper. A total of 117 construction tradesmen out of the 159 sampled within Lagos indicated their degree of agreement with factors capable of influencing construction workers’ safety behaviour on a five-point Likert scale. These were factors adjudged to influence construction workers safety behaviour based on extant literature. The data were analysed using Mean Item Score and Factor Analysis. Construction tradesmen agreed that they are influenced by 25 of the 37 (67.56%) identified factors influencing safety behaviour firms of construction workers. Meanwhile, construction firms’ management commitment to the safety behaviour of tradesmen is the most prominent principal factor. The commitment of the management in developing safety initiatives, training, provision of personal protective equipment, and enforcement of safety rules among others will enhance safety behaviour among construction tradesmen. The study only assessed the opinions of tradesmen in the construction industry in Lagos state. The identified factors might not be generalized to construction professionals. This paper recommends that construction managers make deliberate effort in enhancing good safe behaviour of their tradesmen. This will improve their physical wellbeing, boost construction health and safety in the construction industry and significantly reduce construction fatalities. This paper fulfils a present pertinent need of reducing construction fatalities by focusing on factors influencing the safety behaviour of construction tradesmen.

[Comparison and analysis research on occupational exposure limits of coal dust between China and foreign countries].

Objective: To study and compare the occupational exposure limits (OELs) of coal dust between China and foreign countries, understand the OEL of coal dust in China, and provide data and basis for revising the OEL of coal dust in China. Methods: In August 2023, by searching the official websites of limits setting institutions in relevant countries and regions at home and abroad, collecting and sorting out the OELs of coal dust issued by 10 limit setting institutions in 6 countries and the background information of the formulation, and conducting specific analysis on the classification, limit level and formulation principles of coal dust OEL in each country/institution. Results: In China and Japan, the total dust and respirable dust of coal dust OEL were established respectively, while in other countries, only the time-weighted average concentration (TWA) of respirable coal dust exposure was established. The TWA prescribed by China's Notional Health Commission, the United States Occupational Safety and Health Administration (OSHA) , the United States Mining Safety and Health Administration (MSHA) and the Australian Safety Work Bureau when the SiO(2) content was less than 5% were 5, 2.4, 2 and 3 mg/m(3) respectively. China GBZ 2.1-2019 sets the limit of 2.5 mg/m(3) for respirable coal dust with SiO(2) content less than 10%. The TWA set by the American Conference of Government Industrial Hygienists (ACGIH) and the South African Department of Mines and Energy (DME) for anthracite coal were 0.4 and 0.8 mg/m(3), respectively, and bituminous coal or lignite were 0.9 and 1.8 mg/m(3), respectively. The respirable coal dust TWA set by the National Institute for Occupational Safety and Health (NIOSH) in the United States was 1 mg/m(3), and the TWA set by the New Zealand Work Safety Authority was 3 mg/m(3). Conclusion: At present, the OEL of coal dust in China is at a relatively loose level, and it is suggested to further explore the possibility of revising coal dust OEL.

Embedded machine learning of IoT streams to promote early detection of unsafe environments

Indoor particulate matter (PM) are small solid and liquid particles present in the air, and its monitoring is one of the key challenges regarding workplace safety because of its impact on human health. To address this issue, the Internet of Things (IoT) paradigm allows the implementation of hyperlocal monitoring systems, typically using traditional cloud architectures, which can be enhanced using edge computing architectures. For this reason, we propose an IoT-Edge-Cloud architecture for a platform which promotes the early detection of unsafe environments through machine learning, composed of a sensing layer that collects all the data, an edge layer that performs the artificial intelligence tasks and a cloud layer orchestrating. This architecture is based on the FogFlow framework and the FIWARE components. Our solution proposes an embedded model that can predict the occurrence of PM values higher than the recommended ones—according to the Occupational Safety and Health Administration (OSHA) indicators—with an 87 % of accuracy and a reduction of latency of 26 %. Our platform is innovative because it is based on the FogFlow framework for edge computing and supported by the Smart Spot device validated in a field test. This step is missing from similar state-of-the-art platforms. Thus, we believe that this work contributes to demonstrating the usefulness of AIoT to monitor workplace safety and make trustable predictions, avoiding risky environments.

Acute occupational inhalation injuries-United States, 2011-2022.

Inhalation injuries due to acute occupational exposures to chemicals are preventable. National surveillance of acute inhalation exposures is limited. This study identified the most common acute inhalation exposure-related incidents by industry sector among US workers. To characterize inhalation-related injuries and their exposures during April 2011-March 2022, state and federal records from the Occupational Safety and Health Administration (OSHA) Occupational Safety and Health Information System (OIS) accident database were analyzed. Industry-specific injury, hospitalization, and fatality rates were calculated. The most frequent acute inhalation incidents investigated by OSHA were caused by inorganic gases (52.9%) such as carbon monoxide (CO) or acids, bases, and oxidizing chemical agents (12.9%) such as anhydrous ammonia. The largest number of fatal and nonfatal injuries were reported in the manufacturing (28.6%) and construction (17.2%) sectors. Workers were affected by acute inhalation exposures in most industries. Using this surveillance, employers can recognize frequently-occurring preventable acute inhalation exposures by industry, such as inorganic gases in the manufacturing sector, and implement prevention measures. Training of workers on exposure characteristics and limits, adverse health effects, and use of protective equipment by exposure agent can prevent inhalation injuries.

Employee investigation and contact tracing program in a pediatric cancer hospital to mitigate the spread of COVID-19 among the workforce, patients, and caregivers.

Case investigations and contact tracing are essential disease control measures used by health departments. Early in the pandemic, they were seen as a key strategy to stop COVID-19 spread. The CDC urged rapid action to scale up and train a large workforce and collaborate across public and private agencies to halt COVID-19 transmission. We developed a program for case investigation and contact tracing that followed CDC and local health guidelines, compliant with the Occupational Safety and Health Administration (OSHA) regulations and tailored to the needs and resources of our institution. Program staff were trained and assessed for competency before joining the program. From March 2020 to May 2021, we performed 838 COVID-19 case investigations, which led to 136 contacts. Most employees reported a known SARS-CoV-2 exposure from the community (n = 435) or household (n = 343). Only seven (5.1%) employees were determined as more likely than not to have SARS-CoV-2 infection related to workplace exposure, and when so, lapses in following the masking recommendations were identified. Between June 2021-February 2022, our program adjusted to the demand of the different waves, particularly omicron, by significantly reducing the amount of data collected. No transmission from employees to patients or caregivers was observed during this period. Prompt implementation of case investigation and contact tracing is possible, and it effectively reduces workplace exposures. This approach can be adapted to suit the specific needs and requirements of various healthcare settings, particularly those serving the most vulnerable patient populations.

Forensic Analysis of Lung Cancer from Secondhand Smoke Exposure of a Motel Worker

Background: In July 2018, Ms. PJM, a 50-year-old lifelong nonsmoker, was diagnosed with primary Stage IV lung adenocarcinoma with secondary metastasis to the brain, after being hospitalized for a fall in the motel where she worked, in Los Angeles, California. She had been employed as a maid cleaning rooms in this motel for 20 years, where she was exposed to secondhand and thirdhand tobacco smoke daily. Her death certificate, dated June 2021, declared metastatic lung cancer to be the cause of her death at age 53. Occupational disability and death claims filed by her attorney were contested by her employer. Aims: To conduct a forensic analysis using mathematical modeling to quantify Ms. PJM’s toxic secondhand and thirdhand smoke exposures, in order to estimate her risk of lung cancer from exposure to tobacco combustion products and other potential carcinogenic agents to which she might have been exposed. Methods: A quantitative analysis employing assessment of Hazard, Exposure, Dose, Dose-Response, and Risk plus a Discussion of Uncertainty. It is routinely used by U.S. federal regulatory agencies, including the Occupational Safety and Health Administration (OSHA), and the Environmental Protection Agency (EPA). Results: Ms. PJM’s modeled exposure to fine particulate matter from secondhand smoke ranged from the Hazardous to Significant Harm Levels of the EPA Air Quality Index for fine particles (PM2.5). Her modeled dose of serum cotinine ranged from the 90th to beyond the 95th percentile of nonsmokers’ dose, measured in a statistical sample of the U.S. nonsmoking population. Her estimated risk exceeds OSHA’s Significant Risk of Material Impairment of Health Level by a factor of three. She is estimated to have been exposed to the thirdhand smoke of at least 1.4 million cigarettes outgassing from room surfaces during her 20 years of labor. As for potential confounders, there were no known carcinogens in any of the cleaning agents she used; there is no evidence that she was exposed to asbestos, and she resided in a low-radon area of Los Angeles. Conclusions: As a result of her occupational exposure to secondhand and thirdhand smoke, Ms. PJM lost an estimated 33 years of life expectancy. The State of California has been remiss in failing to extend its workplace smoking ban to hotels and motels, leaving their workstaff at grave risk of the manifold diseases of passive smoking.

Assessing the Risk of Occupational Hazard Using the FMEA Tool Among Hospital Staff at Multispecialty Hospital

Considering the importance of occupational hazard assessment, this study has been performed to identify the risks for employees who especially undergo a major occupational hazard that affects their efficiency and productivity. The study aimed to assess the risk of occupational hazard using Failure Mode and Effect Analysis (FMEA) and strategy to modify the healthcare packages provided by the hospital to the staff. A survey and personal interviews were done at a private multispecialty hospital in Chennai using a descriptive study methodology. The survey included 150 hospital employees from four departments: CSSD (6 participants, covering all available samples), Maintenance (41 participants, chosen at random), Nursing (60 participants, chosen at random), and Housekeeping (43 participants, chosen at random). To collect data, a standardized questionnaire aligned with the Occupational Safety and Health Administration (OSHA) was used (https://www.osha.gov/laws-regs/standardinterpretations/1987-08-06). In addition, unstructured personal interviews with key workers were undertaken. The data revealed that CSSD workers encountered most of the stated dangers, with 100% admitting to workplace risks such as needle sticks, chemical allergies, the risk of burns, and awkward ergonomic postures. Maintenance workers reported a 54% risk of pain and discomfort, 32% of sleep loss following night shifts, and 37% of chemical risks. Nursing personnel cited poor ergonomic posture (68%) as a key concern, followed by sleep loss (62%), and the risk of cuts (52%). Housekeeping personnel cited hazards of falls (69%), poor ergonomic postures (40%), and infectious disease exposure (31%). The study emphasizes the need to address occupational health risks in healthcare settings by thoroughly reviewing the many occupational health hazards that impact healthcare professionals. However, it is important to remember that the study relied on data from the previous six months, potentially leaving out undetected risks. Furthermore, the study emphasized the impact of these dangers on healthcare personnel, emphasizing the problem of events being underreported inside the institution. Notably, the study emphasized the importance of paying close attention to occupational dangers such as needle sticks, chemical exposure, burns and ergonomic concerns in healthcare professionals' daily health management.

Harnessing Virtual Reality to Mitigate Heat-Related Injuries in Construction Projects

The construction industry has witnessed a surge in heat-related accidents alongside rising summertime temperatures, exposing workers to potential injuries. The absence of specific heat stress standards by the Occupational Safety and Health Administration (OSHA) underscores the urgent need for more comprehensive and interactive educational materials to prevent such incidents in construction projects. This study proposes the adoption of an interactive Virtual Reality (VR) application to offer construction workers realistic and effective training, mitigating heat-related injuries. During the training sessions, VR headsets were utilized to immerse workers in two lifelike scenarios: (1) Addressing self-care during heat exhaustion; (2) Assisting a coworker experiencing heat exhaustion. A case study evaluated the effectiveness of the proposed VR training for 82 construction workers from two companies. Company A had traditional training, while Company B used VR training. Both groups took pre- and post-assessment surveys with six questions. The pre-assessment found no significant knowledge difference between the groups. After training, VR showed a significant reduction in incorrect answers compared to traditional training. Statistical tests confirmed the superiority of VR training (p-value = 0.00152 < 0.05), suggesting its effectiveness in preventing heat-related injuries in construction compared to traditional training methods.

Metal–organic framework-reduced graphene oxide (Zn-BDC@rGO) composite for selective discrimination among ammonia, carbon monoxide, and sulfur dioxide

The structural diversity and high surface reactivity of the metal–organic frameworks (MOFs) offer an ideal material platform for various applications such as gas storage, gas separation, catalyst, etc. However, their use in chemiresistive gas sensing is limited due to the requirement of optimized gas adsorption properties with electrical conductivity. In the present investigation, we have modulated the electrical properties of zinc benzene dicarboxylate (Zn-BDC) MOF by modifying it with partially reduced graphene oxide (rGO). The Zn-BDC and rGO composite (Zn-BDC@rGO) was synthesized by utilizing a solvothermal method and multiparametrically tested by various techniques such as X-Ray diffraction (XRD), UV–visible spectroscopy, Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), thermogravimetric analysis (TGA), and I–V characteristics, for its structural, spectroscopic, morphological, surface area analysis, thermal stability, and electrical characterization, respectively. The synthesized Zn-BDC@rGO composite was deposited via drop casting method on the copper electrodes on a glass substrate (100 µm gap) using the shadow mask technique by the e-beam evaporator, and tested for the detection of ammonia, carbon monoxide, and sulfur dioxide using chemiresistive modality. The principal component analysis (PCA) indicates that the developed sensor selectively discriminates among the NH3, CO, and SO2 gases with low response/recovery time, i.e., 60/120 s at 20 ppm, which is far below the permissible exposure limit (PEL) suggested by The Occupational Safety and Health Administration (OSHA), USA for CO and NH3 and very close to the PEL level of SO2.

Managing Safety Risks from Overlapping Construction Activities: A BIM Approach

Addressing safety risks in construction is an ongoing priority, and integrating safety considerations into construction scheduling is a crucial aspect of this effort. A notable challenge is the safety risk posed by concurrent tasks, which has received limited attention in prior research. This study aims to address this research gap by introducing a novel Building Information Modeling (BIM)-based model that assesses the increased hazardousness resulting from overlapping construction activities. Historically, research has predominantly focused on individual task safety, with less emphasis on the risks associated with overlapping activities. Our innovative approach introduces the concept of a ‘source–target’ match, which evaluates the degree of hazardousness escalation when activities overlap. Drawing on data from the Occupational Safety and Health Administration (OSHA) and the National Institute for Occupational Safety and Health (NIOSH) fatal accident reports, we extracted 11 hazardous and 9 susceptibility attributes to build a source–target match table. This table reveals the characteristics of activities that generate hazardous conflicts when overlapping. The key contribution of this research is the assessment, prioritization, and visualization of risk levels in a BIM environment. This framework empowers safety managers to proactively address safety risks resulting from overlapping construction activities, ultimately reducing accidents in the construction industry. By shedding light on this overlooked aspect of construction safety, our research highlights the importance of integrating safety considerations into construction scheduling and provides a practical tool for mitigating risks, enhancing workplace safety, and ultimately improving project outcomes.

Concentrations of respirable crystalline silica and radon among tanzanite mining communities in Mererani, Tanzania.

Globally, the number of small-scale miners (SSM) is estimated to be more than 25 million, but it supports the livelihoods of around 100 million individuals. In Tanzania, the number of SSM has increased from an estimated 150,000 in 1987 to ~1.5 million in 2017. The miners are at a high risk of occupational-related health challenges. The study aimed to assess the concentrations of respirable crystalline silica (RCS) and radon among the tanzanite mining communities in Simanjiro District, Tanzania. We carried out a cross-sectional study involving the Mererani mines in Tanzania. These are underground mines comprised of informally employed miners, i.e. SSM. Concentrations of RCS and radon gas were measured in 44 study units, i.e. 22 mining pits and within 22 houses in the general community, e.g. shops in the peri-mining community. A total of 132 respirable personal dust exposure samples (PDS), 3 from each of the study units were taken, but only 66 PDS from the mining pits were analysed, as this was the main interest of this study. Radon concentration was measured by continuous monitoring throughout the working shift (and overnight for residences) using AlphaGuard monitor. The medians and comparison to the reference values, OSHA USA PEL and WHO/IARC references, were done for RCS and radon, respectively, using SPSS Ver. 27.0.0). The median time-weighted average (TWA) concentration of the RCS in the mining pits was 1.23 mg/m3. Of all 66 personal dust samples from the mining pits, 65 (98.5%) had concentrations of RCS above the Occupational Safety and Health Administration (OSHA) permissible exposure limit (PEL) of 0.05 mg/m3. Mining pits had a median radon concentration of 169.50 bq/m3, which is above the World Health Organization (WHO)/International Commission on Radiation Protection (ICRP) recommended reference of 100.00 bq/m3 but not above the upper reference of 300.00 bq/m3, while the community buildings had a median radon concentration of 88.00 bq/m3. Overall, 9 (20.5%) and 17 (38.6%) radon measurements were above 300.00 bq/m3 and between 100.00 and 300.00 bq/m3 references, respectively. Specifically, in the mining pits, 9 (40.9%) test results were above 300.00 bq/m3, while none of the test results in the community was above 300.00 bq/m3. The tanzanite SSM in Mererani we highly exposed to RCS, which increases the risk of pulmonary diseases, including silicosis, tuberculosis, and pulmonary malignancies. Immediate action by OSHA Tanzania should be enforcement of wearing respirators by all miners throughout the working hours. Health education programmes to the SSM must be strengthened and OSHA Tanzania should adopt the 0.05 mg/m3 PEL, and enforce other occupational health and safety measures, including regular use of dust suppression mechanisms (water spray and wet drilling) and monitoring of RCS exposures among SSM. Monitoring of radon exposure both in the mining pits and community buildings should be conducted, and mitigation measures should be implemented in areas that exceed the reference level of 100.00 bq/m3.

Improving Regulatory Effectiveness through Better Targeting: Evidence from OSHA

We study how a regulator can best target inspections. Our case study is a US Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection led to 2.4 (9 percent) fewer serious injuries over the next 5 years. Using new machine learning methods, we find that OSHA could have averted as much as twice as many injuries by targeting inspections to workplaces with the highest expected averted injuries and nearly as many by targeting the highest expected level of injuries. Either approach would have generated up to $850 million in social value over the decade we examine. (JEL C63, J28, J81, K32, L51)

A methodology for occupational exposure assessment of organic pollutants emitted through aerosols from recycling of e‐waste

AbstractEmission of airborne particulate matter is produced by the industrial processes of metal extraction from electronic waste (e‐waste). These aerosols can transport organic contaminants, such as polyaromatic hydrocarbons (PAHs) and polybrominated biphenyls. These pollutants are proven to have long‐term effects on workers' health. In this work, we characterize aerosol particles and dust deposited from a recycling process of printed circuit boards in a recycling plant. This study also explores the significance of the secondary aerosol sources, and their importance, as an additional burden compared to primary sources. A Scanning Mobility Particles Counter and Sizer (SMPCS) was used to measure the size distributions of ultrafine particles. A Micro‐Orifice Uniform Deposition Impactor (MOUDI) collected aerosol particle samples for chemical analysis. All plant compartments checked are subject to high particulate matter concentrations during work hours. Concentrations of organic pollutants in the machinery compartments do not pose a short or long‐term health risk according to US Occupational Safety and Health Administration (OHSA). The application of the model presented in this work revealed that the accumulation of contaminants in other compartments should be considered in an occupational exposure assessment because it can present an equally important burden to workers’ health.

Fatal injuries associated with rear step riding among municipal solid waste collection workers (United States, 1984-2020).

United States solid waste workers suffer a high fatal injury rate due to their frequent exposures to refuse-vehicle-related hazards. The Occupational Safety and Health Administration (OSHA) allows workers to ride on the rear steps of a garbage truck (exterior riding) if employers abide by American National Standard Z245.1 (ANSI Z245.1). The State of California (CA) has banned exterior riding since 1984, and the City of New York (NYC) has implemented its own initiatives to prevent exterior riding deaths. Fatal exterior riding incidents were identified from two online databases. Variables relating to deceased workers, employers, and injury circumstances were analyzed. The study identified 181 exterior riding deaths from 604 refuse-vehicle-related fatal incidents (deaths either directly caused by a refuse vehicle or one in which the victim was performing a refuse-vehicle-related task) in the United States (1984-2020). A total of 50 (27.6%) of the exterior riding deaths had no ANSI Z245.1 violations. Risk factors other than those addressed by ANSI Z245.1 contributed to these worker deaths. Exterior riding deaths identified by this study were all preventable. Temporary workers and workers in the public sector may be at higher risk for exterior riding deaths. Both CA and NYC had taken measures to prohibit the practice of exterior riding, and both had lower numbers of exterior riding deaths. ANSI Z245.1 and current OSHA enforcement policy do not address the inherent dangers of falling off a moving heavy vehicle while standing on a small and elevated platform, and are not effective in preventing fatal exterior riding incidents.

A semi-automated coding scheme for occupational injury data: An approach using Bayesian decision support system

IntroductionOver the past few years, classic Machine Learning approaches such as Multinomial Naïve Bayes, Support Vector Machine as well as regularized Logistic Regression have been adapted to autocode injury narratives collected by the Bureau of Labour Statistics to reduce the manual effort needed to assign codes to these narratives. However, the effectiveness of these algorithms is yet to be explored on severe injury reports collected by the Occupational Safety and Health Administration (OSHA). This study aims to explore the performances of two Bayesian models for autocoding these reports, segregate narratives that require manual reviewing, and analyse the usefulness of presenting top k predictions for such reviews to human coders. MethodThe severe injury reports collected by OSHA from January 2015 to February 2021 were used in this study. Firstly, Unigram (UNB) and Bigram (BNB) Naïve Bayes models are used to classify the injury narratives, and their performance is analyzed. Furthermore, two filtering strategies are used a) Instances where the UNB and BNB models agree are autocoded b) Only cases where the two models agree and whose prediction probability is above a minimum threshold are autocoded. The remaining cases are filtered out to be reviewed and coded by manual coders. The sensitivity of top k predictions for the UNB, BNB, and UNB-BNB models are also compared and analyzed to aid human coders in assigning codes to the narratives that are filtered out. ResultsFor fully autocoded data, the sensitivity of the UNB model is 75.21%, and that of the BNB model is 75.17%. The filtering approach has an overall sensitivity of 88.17%, flagging 31% of the injury narratives for manual review. The UNB model performs slightly better than the BNB model, and the accuracy increases as cases where the two models agree are considered and a prediction probability threshold is set. For the top 5 predictions, a maximum F1-score of 55% is achieved by the UNB-BNB model.