Safety Equipment Research Articles

Safety of health workers during the COVID-19 pandemic and beyond: piloting WHO framework in Iran

BackgroundHealth Workers Safety (HWS) is a global health priority and essential at all times, in stable situations, in emergencies, in disease epidemics or pandemics. This study aimed to assess HWS during the COVID-19 Pandemic.MethodsThis cross-sectional study was conducted in 2022 in east Azerbaijan province, Iran. HWS was assessed based on 22 indicators suggested by WHO EMRO. We selected 15 PHC facilities and six wards from two hospitals randomly. Data collected (qualitative and quantitative) using national digital health records, staff records, and indicator-specific tools. In addition to measuring the indicator’s value, the indicators’ feasibility was also assessed. Descriptive and inferential statistics with SPSS-16 were used for data analysis.ResultsTotally, 325 Health Workers (HWs) (218 from PHC facilities and 107 from hospitals) participated in the study. Most of the participants in PHC facilities and hospitals were Community Health Workers (CHWs) (Moragheb Salamat) (45.4%) and nurses (37.38%), respectively. Most of HWs had completed the full vaccination schedule for Hepatitis B and COVID-19. Personal Protective Equipment (PPE) safety protocols were adhered by most of HWs within a healthcare facility. None of managers had attended nationally certified training for mental health support for health and care workers. Less than 20% of HWs participated in the work burnout prevention courses and most of HWs complained about work overload, or burnout. The job satisfaction level of hospital HWs (60.20%) was significantly higher than that of HWs from PHC facilities (57.18%) (P < 0.001).ConclusionEven though the mental health of HWs was not as expected, the indicators related to physical health and occupational health were at a suitable level. Also, there is not a system in PHC to audit the application of safety measures to mitigate the risk of contracting COVID-19. We recommend creating a specific system (precise and detailed) for HWs’ safety and applying safety measures in the PHC routine programs.

Prediction of mechanical characteristics of shearer intelligent cables under bending conditions.

The frequent bending of shearer cables during operation often leads to mechanical fatigue, posing risks to equipment safety. Accurately predicting the mechanical properties of these cables under bending conditions is crucial for improving the reliability and service life of shearers. This paper proposes a shearer optical fiber cable mechanical characteristics prediction model based on Temporal Convolutional Network (TCN), Bidirectional Long Short-Term Memory (BiLSTM), and Squeeze-and-Excitation Attention (SEAttention), referred to as the TCN-BiLSTM-SEAttention model. This method leverages TCN's causal and dilated convolution operations to capture long-term sequential features, BiLSTM's bidirectional information processing to ensure the completeness of sequence information, and the SEAttention mechanism to assign adaptive weights to features, effectively enhancing the focus on key features. The model's performance is validated through comparisons with multiple other models, and the contributions of input features to the model's predictions are quantified using Shapley Additive Explanations (SHAP). By learning the stress variation patterns between the optical fiber, power conductor, and control conductor in the shearer cable, the model enables accurate prediction of the stress in other cable conductors based on optical fiber stress data. Experiments were conducted using a shearer optical fiber cable bending simulation dataset with traction speeds of 6 m/min, 8 m/min, and 10 m/min. The results show that, compared to other predictive models, the proposed model achieves reductions in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) to 0.0002, 0.0159, and 0.0126, respectively, with the coefficient of determination (R2) increasing to 0.981. The maximum deviation between predicted and actual values is only 0.86%, demonstrating outstanding prediction accuracy. SHAP feature analysis reveals that the control conductor features have the most substantial influence on predictions, with a SHAP value of 0.095. The research shows that the TCN-BiLSTM-SEAttention model demonstrates outstanding predictive capability under complex operating conditions, providing a novel approach for improving cable management and equipment safety through optical fiber monitoring technology in the intelligent development of coal mines, highlighting the potential of deep learning in complex mechanical predictions.

High temperature resistant thin film thermocouple prepared based on inkjet printing

High temperature resistant thin film thermocouple prepared based on inkjet printing

Low back demands from assisting a patient with an unexpected loss of balance.

To combat the high incidence of lower back musculoskeletal injuries in healthcare workers, it is important to identify potentially injurious tasks. Although risk of injury has been estimated for many clinical tasks, assisting a patient following an unexpected loss of balance or sudden fall has not been assessed. This study aimed to quantify the lower back forces of healthcare workers when assisting a patient from a standing loss of balance. Peak L5/S1 intervertebral joint forces were estimated from thirteen healthcare workers in a laboratory setting as they assisted a patient from a standing loss of balance to a nearby wheelchair. The patient was a healthy male (64kg) who simulated a loss of balance by buckling at the knees. An additional condition with 18% of the patient's body weight unloaded was also tested. In a minority of trials, lower back demands exceeded ergonomic guidelines of 3400 and 1000N for compression and shear, respectively. Patient body weight affected both compression and resultant shear forces (p-values < .001). The lower back demands when assisting a 64-kg patient during a simulated loss of balance did not consistently exceed ergonomic safety guidelines. However, the results imply a high-risk task for heavier patients in simulated settings, or potentially all patients in realistic clinical settings. Several experimental design considerations and limitations may have created a best-case scenario that underestimated the lack of injury risk during the task studied. Use of safe patient handling and mobility equipment is advisable to minimize risk when ambulating patients.

PEREMAJAAN INSTALASI LISTRIK DI MASJID BABUSALAM PERUMAHAN DARU ESTATET, MEKAR SARI, KEC, JEMBE, KABUPATEN TANGERANG, BANTEN

Electricity is a fundamental need for all levels of society, ranging from industrial requirements to basic household necessities. Ensuring the safety of electrical installations in homes or offices is crucial, as these systems must comply with established standards to prevent incidents such as electric shocks and fires caused by short circuits, which can lead to significant material losses and even fatalities. Despite this, many communities lack adequate knowledge about proper electrical installation and maintenance procedures, increasing the risk of fires and electrocution. To address these issues, the Community Service Program (PKM) conducted by lecturers from the Electrical Engineering Study Program, Faculty of Engineering, Universitas Pamulang, focuses on the renovation of electrical installations at Babusalam Mosque, located in Daru Estate Residential Area, Mekar Sari, Jembe Subdistrict, Tangerang Regency, Banten. This activity involves replacing and upgrading outdated electrical components and systems to ensure compliance with safety standards. The program aims to enhance public awareness and understanding of safe electrical energy use, thereby promoting the safety and security of equipment, buildings, and the community. Regular and comprehensive inspections of electrical installations are emphasized as a preventive measure to mitigate potential hazards, ensuring a safer environment for all.

Incremental Machine Learning-integrated Blockchain for Real-time Security Protection in Cyber-enabled Manufacturing Systems

Abstract Cyber-enabled manufacturing systems become increasingly data-rich, generating vast amounts of real-time sensor data for quality control and process optimization. However, it also exposes these systems to significant cyber-physical security threats. For instance, attackers may delete, change, or replace data, leading to defective products, damaged equipment, or operational safety hazards. False data injection attacks can compromise machine learning (ML) models, resulting in erroneous outcomes. To mitigate these risks, it is crucial to employ robust data processing techniques that can adapt to varying process conditions and detect anomalies in real-time. In this context, incremental machine learning (IML) can be valuable, allowing models to be updated incrementally with newly collected data without retraining from scratch. Moreover, although recent studies have demonstrated the potential of blockchain in enhancing data security in manufacturing systems, most existing frameworks are primarily based on cryptography, which does not sufficiently address data quality issues. Thus, this study proposes a gatekeeper mechanism to integrate IML with blockchain and discusses how this integration could potentially increase data integrity of cyber-enabled manufacturing systems. The proposed IML-integrated blockchain can potentially address data security concerns from both intentional (e.g., malicious tampering) and unintentional alterations (e.g., process anomalies). The case study results show that the proposed gatekeeper integration algorithm can successfully filter out over 80% of malicious data entries while maintaining comparable classification performance to standard IML models. Furthermore, the integration of blockchain enables effective detection of tampering attempts, ensuring the trustworthiness of the stored information.

A reliability, availability and maintainability (RAM) model for electromechanical components in hydropower plants

Abstract Hydropower generation is world best source of renewable energy and is continuously playing a tremendous job in energy requirement. To cope up with day by day increasing demand in electric energy, it is very essential to keep the hydropower plants in sustainable operational condition. To achieve this, the maintenance strategies based on Reliability, Availability and Maintainability (RAM) analysis play a pivotal role in sustainability of the hydropower plants. In our case study various critical components of hydropower plant were identified such as turbine, governor and generator. The causes and effects of various failures in the critical components were identified using Failure Mode Effect Analysis (FMEA) and Fault tree Analysis (FTA). The main role in the study is presenting a RAM model which helps in evaluating different levels of performance in Hydropower plant. Finally, the RAM parameters were evaluated and their outcomes were suggested to find the convenient maintenance intervals. The results of the proposed model revealed that the critical flaws of the hydrogenation process such as turbines, governors and generator should to be taken on priority basis to achieve the high level of reliability and safety. The results of present framework is to achieve the high level of reliability, hence, the main flaws of the hydrogenation process such as turbines, governors and generator should to be taken on priority basis. The proposed study could be valuable for improving the availability and safety of the critical equipment in hydropower plant. As a consequence, the results of present study could be beneficial for other hydro generating facilities to achieve the sustainable maintenance and operation programs in electricity generation systems.

Research on leakage and diffusion behavior of hydrogen doped natural gas in integrated pipeline corridors based on data drive

With the wide application of hydrogen-doped natural gas (HBNG) in end users, laying pipelines in urban, comprehensive pipe corridors has become increasingly common. However, the leakage and diffusion of hydrogen-doped natural gas in confined or semi-confined spaces (e.g., utility corridors) can pose a severe safety hazard, as methane and hydrogen gas mixtures have a higher risk of explosion. Therefore, studying hydrogen-doped natural gas’s leakage and diffusion behavior in the comprehensive pipe gallery is essential to ensure its safe operation. This paper establishes a numerical model to study the diffusion law of hydrogen-doped natural gas leakage, and the concentration distribution under different conditions is analyzed. The evolution of the leakage and diffusion of hydrogen-doped natural gas under different hydrogen doping ratios, wind speeds, inlet and outlet spacing, and leakage port sizes were simulated, and the effects of these factors on gas diffusion and explosion hazard volume were discussed. In addition, the backpropagation neural network (BPNN) combined with the global optimization capability of genetic algorithm and the nonlinear mapping capability of neural network is used in this paper to provide a reliable technical means for the accurate prediction of explosion risk volume, which has important application value in the safety design of pipeline corridor and accident prevention and control. The results show that the diffusion range of gas in the pipe corridor increases significantly with the increase of hydrogen mixing ratio. When the hydrogen mixing ratio decreases from 20% to 0, the explosion volume of CH4 decreases by 12.25%. The explosion volume of H2 is close to 0. At the same time, the greater the distance between inlet and outlet, the wider the spread of the dangerous area, when the distance between inlet and outlet is reduced from 200 m to 100 m, the explosion volume of CH4 is reduced by 99.92%, and the explosion volume of H2 is reduced by 100%. In the case of emergency, the reasonable design of Distance between inlet and outlet and air flow configuration can help to quickly discharge harmful gases, ensure the safe evacuation and equipment maintenance in the pipe corridor, and have guiding significance for the ventilation design of the pipe corridor.

Factors associated with occupational injuries among bricklayers and carpenters in Building Construction: insights from a mixed methods study in Osun State, Nigeria

BackgroundOccupational injuries (OI) remains a global health issue, claiming approximately 1000 lives daily. More needs to be known about OI burdens among artisans in low-income settings. Therefore, this study assessed the factors influencing OIs among carpenters and bricklayers, who are informal artisans in Nigeria.MethodsThis mixed-methods survey was conducted in Osun state, Nigeria. The quantitative component entailed a comparative cross-sectional study of 421 bricklayers and 425 carpenters selected via simple random sampling. Information on socio-demographics and OI prevalence was obtained using a semi-structured questionnaire. The qualitative aspect comprised 12 focus group discussions (FGD) among artisans who did not participate in the quantitative aspect of the study. Thematic analysis of the qualitative data was conducted to identify pertinent themes and subthemes. Binary logistic regression analysis was conducted to assess the factors influencing OIs, p-value less than 0.05 was taken as statistically significant.ResultsAll respondents were male. The mean age was 51.3.7 ± 14.7 years for bricklayers and 50.0 ± 11.5 years for carpenters. The 3-month prevalence of OI was 39.9% for bricklayers and 51.8% for carpenters. Factors associated with OI among bricklayers included being aged 20–39 years (AOR:6.9, 95% CI:3.1–15.3) and 40–59 years (AOR:2.9, 95% CI:1.5–5.6), earning less than N50,000 (US$67) monthly (OR:2.3, 95% CI:1.2–4.7), earning N50,000-N99,000 (US$67-US$133) monthly (AOR:2.5, 95% CI: 1.2–5.2), and handling ≥ 200 kg per day at work (AOR:2.1, 95% CI:1.3–3.5). For carpenters, factors associated with OI were being aged 20–39 years (AOR:4.1, 95% CI:2.0-8.5), age 40–59 years (AOR:2.1, 95% CI:1.2–3.6) and handling 100–199 kg per day at work (AOR:1.9, 95% CI:1.02–3.4). FGD findings revealed that the use of substandard building materials, poor use of personal protective equipment and working at heights may predispose to OIs.ConclusionThe burden of OI is high among informal construction artisans in Nigeria. Safety interventions should target persons < 60 years, those handling heavy weights at work (> 100 kg) and bricklayers earning < N100,000 (< US$134) monthly. Emphasis should also be placed on the use of safety equipment and ensuring standards of building materials.

Likelihood of using a harm reduction vending machine among rural people who inject drugs in Appalachian Kentucky.

Harm reduction vending machines (HRVMs) that dispense safe injection equipment and other supplies have operated globally for more than 30 years, yet few operate in the U.S., particularly in the rural epicenters of drug-related harms. This study explores likelihood of using HRVMs and correlates thereto among people who inject drugs in rural Appalachian Kentucky. Respondent-driven sampling and outreach were used to recruit participants who were age 18 or older, resided in an Appalachian Kentucky county, and had used opioids and/or injected drugs to get high in the past 30 days. Interviewer-administered questionnaires elicited data on behavioral and demographic characteristics and likelihood of using HRVMs. Analyses were restricted to participants who injected in the past 6 months (n = 259). Generalized estimating equations were used to estimate adjusted prevalence ratios (APRs) for correlates to likelihood of using HRVMs, controlling for lifetime use of brick-and-mortar syringe service programs. Overall, 57 % reported being likely to use HRVMs. Participants who lacked consistent access to transportation, engaged in receptive and distributive syringe sharing, experienced more lifetime overdoses, and had unsuccessfully attempted to access medications for opioid use disorder (MOUD) reported being more likely to use HRVMs. Heroin and prescription opioid use were negatively associated with likelihood of HRVM use, as was experience of shame around drug use. Most people who inject drugs in this rural Appalachian sample were likely to use HRVMs, with interest being highest among those at highest risk for injection-related infections and overdose and who had faced difficulty accessing MOUD.

Диагностика бюджетных спортивных учреждений по направлению «Комплексная безопасность и противодействие коррупции»

The article shows the role of physical culture and sport as a state priority, names national goals and targets, on which the health and security of the nation will depend, as well as ensuring a comfortable and safe environment for life. The author’s definition of the system of efficiency of sports budget institutions, which is understood as an adaptive system with feedback connections consisting of subsystems, including a set of elements, performing certain functions in accordance with the requirements of the state task, Russian legislation, the needs of society in providing services in the field of physical culture and sports. Analysis and diagnosis of the activity of sports institutions in the direction «Integrated security and anti-corruption» was carried out. Multidimensional and diagnostic of the main directions related to safety in sports, identified problems requiring solutions. Attention is paid to the issues of ensuring anti-terrorist security of institutions. It is shown that an important role in the issues of anti-terrorist security is assigned to state administration and well-developed communications. The conclusion was drawn that it is necessary to eliminate existing problems, with a view to forming culture and values of healthy lifestyle as the basis for sustainable development of society. Effective horizontal communication and information exchange between the staff of the agencies is needed to ensure comprehensive security and fight against corruption. The current funding of sports institutions under the heading «Security» is insufficient to ensure the needs of institutions in technical safety equipment. To achieve the national development goals of the Russian Federation, these problems must be solved.

Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM.

Predicting the Remaining Useful Life (RUL) is vital for ensuring the reliability and safety of equipment and components. This study introduces a novel method for predicting RUL that utilizes the Convolutional Block Attention Module (CBAM) to address the problem that Convolutional Neural Networks (CNNs) do not effectively leverage data channel features and spatial features in residual life prediction. Firstly, Fast Fourier Transform (FFT) is applied to convert the data into the frequency domain. The resulting frequency domain data is then used as input to the convolutional neural network for feature extraction; Then, the weights of channel features and spatial features are assigned to the extracted features by CBAM, and the weighted features are then input into the Long Short-Term Memory (LSTM) network to learn temporal features. Finally, the effectiveness of the proposed model is verified using the PHM2012 bearing dataset. Compared to several existing RUL prediction methods, the mean squared error, mean absolute error, and root mean squared error of the proposed method in this paper are reduced by 53%, 16.87%, and 31.68%, respectively, which verifies the superiority of the method. Meanwhile, the experimental results demonstrate that the proposed method achieves good RUL prediction accuracy across various failure modes.

Efficient pressure regulation in nonlinear shell-and-tube steam condensers via a Novel TDn(1 + PIDn) controller and DCSA algorithm

Steam condensers are vital components of thermal power plants, responsible for converting turbine exhaust steam back into water for reuse in the power generation cycle. Effective pressure regulation is crucial to ensure operational efficiency and equipment safety. However, conventional control strategies, such as PI, PI-PDn and FOPID controllers, often struggle to manage the nonlinearities and disturbances inherent in steam condenser systems. This paper introduces a novel multistage controller, TDn(1 + PIDn), optimized using the diligent crow search algorithm (DCSA). The proposed controller is specifically designed to address system nonlinearities, external disturbances, and the complexities of dynamic responses in steam condensers. Key contributions include the development of a flexible multi-stage control framework and its optimization via DCSA to achieve enhanced stability, faster response times, and reduced steady-state errors. Simulation results demonstrate that the TDn(1 + PIDn) controller outperforms conventional control strategies, including those tuned with advanced metaheuristic algorithms, in terms of settling time, overshoot, and integral of time weighted absolute error (ITAE). This study marks a significant advancement in pressure regulation strategies, providing a robust and adaptive solution for nonlinear industrial systems.

Edukasi Keselamatan Wisata Sungai: Langkah Nyata Menuju Wisata Berkelanjutan di Tlatar

Safety Education in River Tourism: A Concrete Step Toward Sustainable Tourism in Tlatar The river tourism safety awareness program in Tlatar Tourism Village aimed to enhance the understanding and awareness of local communities and tourism operators regarding the importance of safety in water tourism activities. Using a participatory method, this activity involved theoretical briefings and practical simulations that provided comprehensive knowledge on the proper use of safety equipment, self-rescue techniques, and preventive measures in emergencies. The results of this activity showed a significant improvement in participants' understanding and awareness of tourism safety aspects, which is expected to reduce the risk of accidents and enhance the quality of tourism in the area. In conclusion, this awareness program successfully improved tourism safety standards and fostered environmental awareness among the local community. This activity contributes significantly to the development of safe and sustainable tourism in Tlatar Tourism Village.

Assessment and management of occupational risks in industrial projects using the HAZID technique: a case study of chain dry boom crane in Yazd alloy steel oxygen plant project

Introduction: It is necessary to pay attention to the key role of chain dry boom crane in heavy industrial projects such as the steel industry, to identify and manage occupational risks related to it. This study was conducted with the aim of identifying, evaluating, and managing job risks associated with chain dry boom cranes in the Yazd Alloy Steel Oxygen Plant project using the HAZID technique and providing control strategies to reduce the risk level. Materials and Methods: This study was conducted qualitatively using the HAZID technique. The statistical population included 50 operators, managers, and project experts, and the required information was collected through semi-structured interviews and HAZID workshops. Identified risks were classified into three categories: technical, environmental and human and were evaluated using the risk matrix. Control measures to reduce risk were also proposed and implemented. Findings: In this research, occupational hazards associated with dry chain cranes were identified and classified into three main categories including technical hazards (40%), environmental hazards (30%) and human hazards (30%). Failure of hydraulic systems, failure of boom and safety equipment were considered as technical risks, dealing with high voltage power lines and inappropriate weather effects as environmental risks, and use of unauthorized operators and ignorance of safety principles were considered as human risks. Conclusion: The results of this research showed that after the implementation of control measures, the level of risk decreased significantly. Applying the HAZID technique in similar industrial projects can improve safety and prevent accidents by accurately identifying risks and providing preventive solutions.

Facilities in City Parks Can Increase the number of Visits

City parks provide recreational space and social interaction in urban areas. One park that has great potential is Bulak Teko Indah Park in West Jakarta, which offers various facilities for visitors, especially families with children. This study aims to explore how improving facilities in this park can affect visitor visits. The method used is a qualitative descriptive approach with in-depth interviews, participant observation, and documentation. Data were collected from 15 visitors and three park managers. The results showed that better facilities, such as safe play equipment, sports space, and comfortable seating, played a significant role in increasing comfort and extending the duration of visits. Safety was the main factor for families with children, while the diversity of facilities met the needs of various groups. However, there was input to increase the number of seats and improve the cleanliness of the park. Based on these findings, park managers are advised to add educational facilities, improve cleanliness, and improve accessibility for visitors with special needs. Thus, Bulak Teko Indah Park can become a more attractive and beneficial recreational destination for the community and support the development of a more inclusive and sustainable city park.

Assessment of Occupational Hazards and Role of Life-Saving Gadgets Among Small-Scale Motorised Fishers on India’s Southernmost Coasts

ABSTRACT Objective Marine fishing ranks among the most hazardous occupations globally, with risks intensifying for small-sized vessels venturing deeper into the sea due to the scarcity of near-shore fish and high market demand. This study identifies various occupational hazards and the use of safety equipment among small-scale motorized fishers using traditional fishing methods in the southernmost coastal regions of India. Methods The primary data were collected from 253 artisanal small-scale motorized fishers through a multi-stage stratified random sampling method. For this purpose, a structured interview schedule, comprising both closed and open-ended questions was employed. The Relative Importance Index (RII) was utilized to compare fishers’ perceived impact across various occupational hazard categories, while the frequency distribution of the adoption of life-saving gadgets across various adoption categories was analyzed based on the adoption rate to assess the usage patterns of available life-saving devices. Results The findings indicate environmental, psychological, and vessel-related hazards have the greatest impact on fishers, with specific hazards including “cyclones”, “collisions”, “capsizing”, “high currents”, “lack of visibility”, “fatigue”, “stress”, “anxiety”, and “insomnia”. Despite awareness of safety measures, the usage of life jackets and life buoys remains low among fishers. Fishers in motorized crafts benefit from modern communication and navigation tools to mitigate sea-related uncertainties (Mobile phone − 84.19%, GPS − 87.75%, VHF radio − 67.98%, AIS − 20.16%). Conclusion The study highlights the urgent need for strict enforcement of safety measures during the registration and renewal processes for fishing vessels. Enhancing safety in this sector necessitates increased safety awareness, comprehensive training, and regular annual inspections.

Survey on Industrial AI: A Comprehensive Approach to Restricted Area Monitoring, Safety Equipment Detection, Pose Detection, and Fire Detection

Industrial AI has rapidly evolved as a critical technology that enhances security, safety, and operational efficiency in industrial environments. This survey provides a comprehensive overview of key Industrial AI modules, including restricted area monitoring, safety equipment detection, pose detection, and fire detection. We explore how these modules integrate into existing industrial infrastructures, improving real-time safety monitoring and emergency response systems. Future research directions on these topics are also outlined- developments such as edge computing, AI-augmented human collaboration, and improvements in detection accuracy. This work aspires to show a comprehensive understanding of the Industrial AI application and its promise to change the very nature of operations involving safety and production in industries. Keywords: Industrial AI, Restricted Area Monitoring, Safety Equipment Detection, Pose Detection, Fire Detection, Machine Learning, Computer Vision, Edge Computing, Human-AI Collaboration.

Using a Safe System Framework to Examine the Roadway Mortality Increase Pre-COVID-19 and in the COVID-19 Era in New York State.

Roadway mortality increased during COVID-19, reversing a multi-decade downward trend. The Fatality Analysis Reporting System (FARS) was used to examine contributing factors pre-COVID-19 and in the COVID-19 era using the five pillars of the Safe System framework: (1) road users; (2) vehicles; (3) roadways; (4) speed; and (5) post-crash care. Two study time periods were matched to control for seasonality differences pre-COVID-19 (n = 1725, 1 April 2018-31 December 2019) and in the COVID-19 era (n = 2010, 1 April 2020-31 December 2021) with a three-month buffer period between the two time frames excluded. Four of the five pillars of the safe system had road safety indicators that worsened during the pandemic. Mortality was 19.7% higher for motor vehicle occupants and 45.1% higher for riders of motorized two-wheeled vehicles. In adjusted analyses, failure to use safety equipment (safety belts/helmets) was associated with 44% higher mortality. Two road user groups, non-motorized bicyclists and pedestrians, did not contribute significantly to higher mortality. Urban roadway crashes were higher compared to rural crashes. Additional scientific inquiry into factors associated with COVID-19-era mortality using the Safe System framework yielded important scientific insights to inform prevention efforts. Motorized two-wheeled vehicles contribute disproportionately to pandemic-era higher mortality and constitute an emerging road safety issue that deserves further attention.

Strategi kesiapsiagaaan menghadapi bencana di Perpustakaan UIN Mahmud Yunus Batusangkar

Purpose. This study aims to determine the disaster preparedness carried out by the UIN Mahmud Yunus Batusangkar Library in disaster prevention. It is hoped that this study will be an important contribution to institutions regarding the need for a standard on disaster preparedness. Methodology. The methods used in this research use qualitative methods. In data collection researchers use direct observation techniques, semi-structured interviews, and documentation. Results and discussion. The preventive measures that the library has undertaken by organizing, training, and simulating disasters are usually held by the university every year and are dedicated only to K3 officers. In addition, the library's cooperation with local cooperating with the firefighters. Responsive action makes plans and rescue efforts collections at the UIN Mahmud Yunus Batusangkar Library, training, and disaster simulations are usually held by the university every year to occupational safety and health team. The repairs in 2009 in West Sumatra were devastated by an earthquake and caused the walls of the library to crack and the ceilings of the libraries to fall onto the shelves, as well as causing a lot of dust to burst into the books. To anticipate that, the library did a fumigation. Conclusions. Overall, the library has planned optimal disaster preparedness, which is sourced from the provision of equipment and work safety training in dealing with disasters. As a recommendation from the author, it is expected to provide disaster response training for library managers so that they can respond quickly when a disaster occurs.