High-risk Places Research Articles

COVID-19 transmission dynamics in close-contacts facilities: Optimizing control strategies

Abstract Close-contact places such as long-term facilities have been found to be high-risk and high-morbidity places in the United States during COVID-19 outbreaks. This could be due to the presence of vulnerable resident population, frequent contacts of residents with visitors, staff working at multiple facilities, and potential contaminated surfaces at these facilities. Here, we model close-contacts places to evaluate the role of different transmission pathways of COVID-19 in the presence of adaptable interventions. The model captures a coupled dynamics between three subpopulations (staff, residents, and visitors) and incorporates infection from infectious individuals and through the environment. By using parameterization of the models via real data from facilities in the United States, we identify and quantify the impact of duration and choice of interventions in real time for subpopulations to mitigate disease burden. We study the trade-off between disease burden and prevention cost using cost-effectiveness analysis. It was found that the specific time interval in which an intervention is included has an important effect when maximizing the effectiveness while minimizing the costs. We find that the presence of super-spreader healthcare workers contribute to a significantly higher peak of the number of infected cases compared to similar situation in the presence of super-spreader residents. Considering two nonpharmaceutical interventions: the use of face masks and cleaning surfaces, we observe that the later is an optimum intervention at the beginning of the system’s evolution, while wearing masks becomes an optimum strategy once the infection is widely established and population behavior changes.

SAVAGE: Simulation of Virtual Reality-Based for Building Fire Victim Rescue Learning Media

Airports are very dynamic and complex environments, making them high-risk places for incidents and accidents, both due to the aircraft's movement and to the building facilities or structures at the airport. Emergency service personnel must have high skills in emergency response, quick decision-making abilities, and a deep understanding of the various dangerous situations that may be encountered in the field. Continuous education and training are essential to ensure their readiness and ability to deal with emergencies. This study aims to develop Virtual Reality-based Search and Rescue learning media to improve the skills and understanding of training participants in search and rescue operations. This learning media is designed to provide a realistic and interactive simulation experience, allowing participants to practice rescue procedures in various dangerous scenarios without real risk. The development methods used in this study include the stages of needs analysis, design, development, implementation, and evaluation (ADDIE). At the analysis stage, the identification of training needs and competencies that must be achieved is carried out. The design stage involves designing Virtual Reality scenarios that cover various field conditions and rescue techniques. Effectiveness is evaluated by measuring the increase in skills and understanding of participants before and after using Virtual Reality media. The study results indicate that this learning media effectively improves the operational and decision-making skills of training participants in emergency situations. The feasibility assessment by media experts obtained an average score of 88.72%. Then, the feasibility assessment by material experts obtained an average score of 88.90%. After conducting a product trial on students, the evaluation results were 81.30%. Based on the results of the validation and trial of this product, Virtual Reality-based learning media can be recommended as an innovative and efficient training tool for Search and Rescue learning media.

A spatial analysis of mental health-related calls for service in Atlantic City, New Jersey

ABSTRACT Objective Police officers often find themselves responding to calls that do not involve criminal behavior, but calls related to individuals experiencing emotional distress or mental illness that requires police response. This research aims to identify high-risk places of mental health calls for service (MHCFS) in an urban setting and compare place features of these locations by police response (locations where a CIT-trained officer is dispatched versus a non-trained officer dispatched). Data/Methods Our research uses Atlantic City Police Department’s calls for service data from 1 January 2019 through 30 December 2022, including the incidents of mental incompetence with location components. After removing the calls that were not coded as mental health, a total of 2229 incidents involving perceived mental illness were geocoded and compared. We used RTMDx software to generate risk terrain models for MHCFS in Atlantic City, NJ. Findings The RTM analysis yielded no association between places of interest and MHCFS for calls involving non-CIT-trained officers. Yet, we identified five high-risk activity spaces of MHCFS where officers with CIT training were involved. Grocery stores (RRV = 2.873), places of leisure (RRV = 2.764), Health & Wellness Facilities (RRV = 2.624), Eateries & Restaurants (RRV = 2.547), and Convenience & Variety Stores (RRV = 2.280) are the risk factors identified by the RTM analysis. Given the characteristics of places identified by risk-terrain modeling, we reason that the characteristics of these places indicate that individuals experiencing perceived or actual mental health problems hang out in spaces with ease of access and in spaces where they can stay relatively longer with minimal attention. Conclusion Our research suggests that there is an association between spatial factors and MHCFS that are responded to by CIT-trained officers. City officials should consider deploying additional resources and mental health staff to these places to address the issue of mental health in urban settings. Future research should consider testing whether the places we identified in our analysis are also high-risk places for MHCFS in other urban environments.

Efficacy of Empiric Contact Precautions for Patients from High Risk Facilities

Background: Infection prevention surveillance revealed that patients admitted from two specific long term care facilities comprised the majority of multi-drug resistant organisms (MDRO) and scabies cases at our institution. Current practices include performing active surveillance for Candida auris and methicillin-resistant Staphylococcus aureus (MRSA) for specific high-risk patients, as surveillance for all MDROs and scabies is impractical. We therefore sought to create an admission screening process to efficiently identify patients from high-risk facilities (HRFs) and place them in pre-emptive contact precautions upon admission. Methods: Patients admitted from HRFs were identified on admission as part of the initial nursing assessment. For any positive responses, nursing received a Best Practice Advisory to place the patient in contact precautions and patient placement received an alert that the patient would require a private room. Infection Preventionists reviewed a report of all patients who screened positive and added a “High Risk Facility” banner to the chart. This banner remained for the duration of hospitalization and for every subsequent readmission and outpatient visit. We reviewed the electronic medical records of all patients with a HRF banner placed from March 8, 2023 to September 15, 2023 and abstracted data regarding the presence of scabies or any of the following MDROs before and after placement of the banner: C. auris, carbapenem-resistant enterobacterales (CRE), MRSA, vancomycin-resistant Enterococcus (VRE), carbapenem-resistant Acinetobacter, and MDR Pseudomonas. Results: Of the 93 patients who had a HRF banner added during the study period, 31 (33.33%) were already known to have MDRO colonization at the time of admission to our facility. Thirty-three of the remaining 62 patients (53.22%) without known MDRO colonization were subsequently found to have MDRO colonization/infection or scabies infestation that may have required contact precautions during their index admission or a subsequent admission. This included 14 patients with C. auris, 2 with CRE, 3 with MDR Pseudomonas, 12 with MRSA, 12 with carbapenem-resistant Acinetobacter, and 2 with VRE. Patients were admitted for a median of 9 days before their diagnosis, and 36 of the 93 patients (38.71%) were re-admitted to our hospital during the study period. Conclusion: We found that empiric contact precautions based solely on exposure to specific HRFs facilitated earlier isolation by a median of 9 days. This approach should be considered in acute care hospitals with a high proportion of admissions from HRFs, especially when active and passive surveillance for MDROs is limited.

Automatic edge app placement for personalized heart attack predictions

Edge computing brings data processing, analytics and storage closer to the source, but the major limitation of edge devices is that they have limited processing power and storage. Some have argued that cloud can be a solution to overcome the edge computing limitations. However, performing all tasks on the cloud introduces latency issues. Therefore, we need a solution that can use edge and cloud computing intelligently and interchangeable such that the merits of both can be utilized based on the specific scenario. Such a model has not been discussed in the literature so far which poses a very important limitation. We proposed a novel architecture that intelligently switches data processing between the cloud and edge just-in-time based on specific conditions, i.e., if a healthcare scenario demands low latency data are processed at the edge, otherwise data are automatically processed on the cloud. We illustrate this by creating an Automatic edge application to monitor high risk cardiovascular disease patients who are at the risk of heart attacks after a post-operative surgery. Low latency is very important while monitoring such patients and the application is built to automatically detect all such cases and performs heart attack predictions on the edge while other patients data is processing on the cloud. The experimental results have demonstrated that our application can automatically detect high risk cardiovascular disease patients and place their workloads on the edge which is a new and unique invention in the area of automated edge computing. We have also demonstrated that the data retrieval from the edge is 55% faster than the cloud thereby ensuring low latency with edge.

Evaluating the Motivation to Accept/Not Accept the COVID-19 Vaccination and its Related Factors in Health Care Workers: A Cross-Sectional Study

Background: Vaccination is one of the most cost-effective ways to prevent the spread of COVID-19. Objectives: The present study aimed to determine the prevalence of vaccine acceptance, side effects, and factors encouraging/disincentivizing vaccination among healthcare workers. Methods: A descriptive-analytical cross-sectional study was conducted on 315 health workers at Imam Reza Hospital, Kermanshah, Iran, in 2021. The samples were selected through a simple random sampling method. The data collection tool was a researcher-made questionnaire, and the collected data were analyzed in STATA-17 software. Results: The vaccine acceptance rate was 84.1% (n = 265), and the vaccine refusal rate was 15.9% (n = 50). The most injected vaccines were Sinopharm (n = 112, 42.3%) and Sputnik (n = 88, 33.2%), respectively. The most common side effects after vaccine injection were fatigue (34.8%, n=39) and myalgia (14.3%, n = 16). Being in a high-risk place (n = 199, 75.2%) and fear of contracting COVID-19 (n = 88, 33.5%) were the most important reasons for encouraging vaccination. About 36.7% (n = 18) of blood clotting, 26.5% (n = 14) cardiac arrest, short-term safety, and distrust were the essential factors for not accepting the vaccine. Conclusions: Based on the results, the prevalence of vaccine acceptance among health workers was high. However, a small percentage did not want to accept the vaccine due to negative news and a lack of trust in the vaccine. Therefore, it is necessary to establish strong educational and awareness-raising associations that transmit knowledge of the COVID-19 vaccine by focusing on false information.

Implementation of community health care services to counter the SARS-CoV2 pandemic

BackgroundThe COVID-19 pandemic has ravaged many countries worldwide since December 2019. The high infection rates, and the need for health care assistance for individuals with comorbidities, strained the national health care systems around the world. Outbreak peaks increased the burden on hospitals that where perceived as high-risk places by people, who often decided to cancel or defer hospital visits. Thus, Italian Local Health Authorities had to develop new organizational models to meet the increased health care needs of the population. The aim of this study is to assess the impact of strengthened community health services on the hospital burden.MethodsWe analysed the number of Emergency Department access at the Hospital De Lellis covered by the Local Health Authority in Rieti, from March 2020 to November 2021. We then assessed the effects of community health services: the Special District Continuing Care Units (SDCUs) and the the COVID hub, on the COVID-19-related ED access, admission and mortality rates. A Chi-squared test for trend and three multivariable logistic regression models were used to investigate the trends and the possible predictors of COVID ED access, COVID hospital admissions, and deaths.ResultsBeing male (OR = 1.41, CI95% 1.05–1.90; p = 0.022) and older age (OR = 1.03, CI95% 1.02–1.04; p < 0.0001) increase the likelihood of hospitalisation for Sars-CoV-2. The implementation of the nursing and medical SDCUs contributed to reducing COVID-19-related deaths (OR = 0.09, CI95% 0.03–0.29; p < 0.0001). The simultaneous implementation of the COVID hub and of the nursing SDCUs had a synergistic effect in reducing the likelihood of hospitalisation (OR = 0.24, CI95% 0.09–0.65; p = 0.005). The subsequent implementation of the medical SDCUS has further contributed to lowering the admission rates. These protective effects persisted also after potential cofounders, such as age, sex, clinical condition on admission, and the immunisation status, were adjusted.ConclusionsThese measures have helped in the management of patients in a complex context such as that of a pandemic by reducing the hospital load and playing an important role in the management of the pandemic. Further studies could assess the transferability of this model in a non-pandemic context.

Moyamoya Syndrome in Children With Sickle Cell Disease in Saudi Arabia: A Single-Center Experience.

Background Sickle cell disease (SCD) is relatively common in Saudi Arabia. Its neurologic complications such as stroke and Moyamoya syndrome (MMS) can be severe and devastating. Such complicationscan be minimized by modern investigative tools such as transcranial Doppler (TCD) ultrasound, which is unavailable in many high-risk places. Our aim is to investigate the prevalence and characteristics of these complications in children with SCD in our center where TCD is not available. Methods We conducted a retrospective record review of children with SCD admitted to the pediatric ward andvisited the pediatric hematology outpatient clinic of King Fahad Military Medical Complex, Dhahran, Saudi Arabia, from January 2010 to December 2021. The target population was children aged sixmonths to 14years with SCD and a history of stroke or transient ischemic attacks (TIAs). Their magnetic resonance imaging/magnetic resonance angiography (MRI/MRA) of the brain radiographic features were reviewed. A descriptive analysis was used to summarize the demographic characteristics and clinical features of patients with and without MMS. Results Twenty-six children (out of 385 with sickle cell anemia, originating mainly from the southwestern and eastern provinces of Saudi Arabia) experienced an overt stroke with an overall prevalence of 6.7%. All patients with stroke were originally from the Southwestern province. Their genotype was SS, and the median age at the onset of the first stroke was six years (IQR: 5.5). The main presenting symptoms were seizures (57.7%), motor weakness (42.3%), headache (15.3%), cranial nerve palsies (11.5%), cognitive deficit (7.6%), and dysphasia (3.8%). The majority of strokes were ischemic (92.3%). MMS was detected in 61.5% and was seen at the onset of the first stroke in all patients with this MRA abnormality. Seven children with moyamoya (43.8%) had recurrent strokes. Conclusion In this study, the prevalence of overt stroke is 9% in children with SCD originating from the southwestern region of Saudi Arabia (26/286), and 61.5% of them (16/26) had MMS. It is absent in the children of Eastern origin (99 children). In places lacking TCD facilities, further studies are required to determine if MRA brain screenings of children with SCD may detect MMS before the onset of stroke and help startprotective therapy.

Site Suitability Assessment for Petroleum hubs and Oil retail assets in the Jomoro District: A Hybrid Approach using Fuzzy AHP and VIKOR Method

Petroleum Infrastructure is indispensable considering the current local and global energy demands, however explosions from such establishments often cause loss of lives and properties within the surrounding communities thereby posing great concern to government and the citizenry. This condition calls for research that would provide meaningful solutions to mitigate this menace. Unlawful siting of oil refineries, petrochemical plants, berthing terminals, pipelines, storage terminals, oil and gas retail assets results from non-consideration of environmental impact on growing human population, competition for customers and lack of enforcement of energy standards. The study aims to employ a multifaceted approach comprising of suitability, proximity and spatial statistical analysis in assessing viable areas for developing petroleum hubs in the district. This study further investigated the efficiency of the method and level of compliance to standards set by the Ministry of Energy, Environmental Protection Agency (EPA) and the Town and Country Planning Department through validation using the newly acquired land for petroleum hub and existing filling stations in the study area. Primary and secondary data were used for the study. The primary data consist of locations of oil and gas filling stations picked with the Garmin handheld GPS and surveyed boundary of the land. The secondary data was obtained from the Survey and Mapping division of the land commission of Ghana. It comprises of topographic data, geology and soil maps from which soil types, lithology, roads networks, water bodies, terrain slope and land use features of the area were extracted and used. The dataset was reclassified and weighted using Fuzzy AHP and VIKOR. Spatial analyses were carried out using ArcGIS software to show areas suitable or otherwise for siting petroleum hubs in the study area. Results shows 67.44% of the area are highly suitable for establishment of petroleum hubs, 32.33% of the area falls within moderate suitability zones whereas the least suitability zones occupied 0.23% of the total area. The newly acquired government land for the petroleum hub project fell within the highly suitable zone confirming the validity of the studies in comparison with studies from field experts via environmental impact assessment. The proposed petroleum hub covered areas dominated by very high and high area suitability for its establishment constituting 75.9 km2 (90.3%) of its entire area whereas the moderate suitability zones constituted 8.2 km2 (9.7%) of the remaining areas. Towns situated in very high areas includes; Bakakole Nkwanta, Ahobre, Nawule, Allowule, Tikobo No.1, Edu, Damofu, Ave lenu and Ebonloa, Mpatabo. High areas comprises of Kengen Kpokezo, Alenda wharf, Tekyinta. Anwonakrom, Nkwamta, Elubo and Agege are among the moderate and low area zones for hub and oil retail assets establishment 75% of the oil retail assets complied with the required set standards whiles 25% defaulted. The integration of GIS techniques with multi-criteria decision analyses has proved to be an effective tool for selecting suitable sites for petroleum hubs, oil retail assets and very useful in determining places of high fire risk for proper planning of the area. It is recommended that the authorities and stakeholders put measures in place to educate, perform site suitability assessment and enforce set standards in establishment of petroleum infrastructure.

Geo-spatial risk factor analysis for drug overdose death in South Florida from 2014 to 2019, and the independent contribution of social determinants of health

PurposeThe physical environment and social determinants of health have been shown to influence health behaviors including drug use and fatal drug overdose. The current research examines the effects of the built environment, social determinants of health measures and aggregated risk from the built environment at neighborhood-level on drug overdose death locations in Miami-Dade County, Florida. MethodsRisk Terrain Modeling (RTM) was used to assess the place features risk factors that significantly increase the risk of drug overdose death spatially in Miami-Dade County ZIP Code Tabulation Areas, Florida from 2014 to 2019. An aggregated neighborhood risk of fatal drug overdose measure was developed by averaging the risk per grid cell from the RTM within census block groups each year. Six logistic and zero-inflated regression models were built to examine the effects of three indices of incident-specific social determinants of health (IS-SDH) measures and aggregated risk measures separately, and simultaneously on drug overdose death locations each year. ResultsSeven place features including parks, bus stops, restaurants and grocery stores were significantly related to the occurrence of fatal drug overdoses. When examined separately, one or more indices of the IS-SDH were significant covariates of drug overdose locations in some years. When examined simultaneously, the three indices of the IS-SDH and aggregated risk of fatal drug overdose measure could be all significant in certain years. ConclusionsThe patterns of high-risk areas and place features identified from the RTM related to drug overdose deaths may be used to inform the placement of treatment and prevention resources. A multi-factor approach that combines an aggregated neighborhood risk measure reflecting the risk from the built environment and the incident-specific social determinants of health measures can be used to identify the drug overdose death locations in certain years.

Forensic characteristics of 4866 violent injury cases in Sichuan Province, China

To evaluate the characteristics of violent injury cases in Sichuan Province, China. Overall, 4866 violent injury cases in Sichuan province, China from 2014 to 2017 were included. The injury evaluation report was used to classify and summarize the injury information, case and injury characteristics, and to describe the characteristics for each risk factor. The majority of cases were males (n = 3851, 79.14%), aged 20–60 (n = 3867, 79.47%), and living in rural areas (n = 3094, 65.55%). Many cases occurred in public areas (n = 3351, 74.19%) and in the evening (n = 1005, 29.49%). Passion was the main motive for the violent injuries (n = 2098, 82.11%) and the main types of injuries were those to the brain, face, and auricula (n = 3075, 63.21%). Blunt instruments (n = 2951, 64.86%) were most commonly used to inflict injury, and the injury evaluation determined that the majority of injuries were simple (n = 2669, 54.85%) and slight (n = 1685, 34.63%). For cases resulting from passion and money, blunt instruments were more commonly used, while sharp instruments were more commonly used for injuries resulting from emotion and revenge (p < 0.05). Compared with grievous injuries, public and entertainment areas and the use of blunt instruments were risk factors for slight injuries. The use of blunt instruments was a risk factor for simple injuries. The cases of violent injury in the Sichuan Province of China have certain characteristics and causes. In order to reduce the frequency of such cases, corresponding intervention measures should be actively conducted at the identified high risk places, times, and populations.

Evaluation of Rainfall Erosivity in the Western Balkans by Mapping and Clustering ERA5 Reanalysis Data

The Western Balkans (WB) region is highly prone to water erosion processes, and therefore, the estimation of rainfall erosivity (R-factor) is essential for understanding the complex relationships between hydro-meteorological factors and soil erosion processes. The main objectives of this study are to (1) estimate the spatial-temporal distribution R-factor across the WB region by applying the RUSLE and RUSLE2 methodology with data for the period between 1991 and 2020 and (2) apply cluster analysis to identify places of high erosion risk, and thereby offer a means of targeting suitable mitigation measures. To assess R-factor variability, the ERA5 reanalysis hourly data (0.25° × 0.25° spatial resolution) comprised 390 grid points were used. The calculations were made on a decadal resolution (i.e., for the 1990s, the 2000s, and the 2010s), as well as for the whole study period (1991–2020). In order to reveal spatial patterns of rainfall erosivity, a k-means clustering algorithm was applied. Visualization and mapping were performed in python using the Matplotlib, Seaborn, and Cartopy libraries. Hourly precipitation intensity and monthly precipitation totals exhibited pronounced variability over the study area. High precipitation values were observed in the SW with a &gt;0.3 mm h−1 average, while the least precipitation was seen in the Pannonian Basin and far south (Albanian coast), where the mean intensity was less than an average of 0.1 mm h−1. R-factor variability was very high for both the RUSLE and RUSLE2 methods. The mean R-factor calculated by RUSLE2 was 790 MJ mm ha−1·h−1·yr−1, which is 58% higher than the mean R-factor obtained from RUSLE (330 MJ mm ha−1·h−1·yr−1). The analysis of the R-factor at decadal timescales suggested a rise of 14% in the 2010s. The k-means algorithm for both the RUSLE and RUSLE2 methods implies better spatial distribution in the case of five clusters (K = 5) regarding the R-factor values. The rainfall erosivity maps presented in this research can be seen as useful tools for the assessment of soil erosion intensity and erosion control works, especially for agriculture and land use planning. Since the R-factor is an important part of soil erosion models (RUSLE and RUSLE2), the results of this study can be used as a guide for soil control works, landscape modeling, and suitable mitigation measures on a regional scale.

Measuring the colocation of crime hotspots

Crimes tend to concentrate in high-risk places known as crime hotspots. While the size and locations of such hotspots vary between different types of crime as would the underlying conditions that trigger each crime, the extent of overlaps between their hotspots is understudied. Using crime data from Chicago aggregated at the community-area and the census-tract levels, this paper investigates the patterns of overlapping hotspots between different crime types to see whether a specific group of crime types regularly form a joint cluster. Specifically, we identify statistically significant hotspots for each crime and, using the frequent-pattern-growth algorithm, analyse the frequency of each combination of crimes sharing their hotspot locations across the study area. Results suggest that crime hotspots form stable multi-layered colocations and that each area holds its subset: namely, the pervasive, primary colocations consisting of assault, battery and criminal damage to property, which are frequently joined by 7 additional (e.g. street robbery, motor vehicle theft, weapons violation) crimes to comprise secondary colocations, some of which evolving to an even larger, tertiary colocation of hotspots with up to 11 additional crime types (e.g. homicide, criminal sexual assault, narcotics) to form crime-riddled neighbourhoods. This multi-layered structure of colocations as well as the crime colocation diagrams that show the most representative crimes at each colocation size would improve our understanding of the association between different crime types and the crime indicators of other crimes.

Preventive measures focused on the urban-rural interface protect rural food-producing communities from SARS-CoV-2.

Rural food-producing communities are fundamental for the development of economic activities associated with sustainability and food security. However, despite the importance of rurality in Colombia, preventive strategies continue to be implemented homogeneously, without considering the dynamics of SARS-CoV-2 in rural food-producing communities. To model real areas in Colombia involving rural and urban populations that have intrinsic SARS-CoV-2 transmission dynamics. Characterize rural-urban interactions by means of a parameter that provides different scenarios and allows us to identify interactions capable of preventing SARS-CoV-2 transmission in rural food-producing communities. The dynamics of SARS-CoV-2 infection was modeled in five case studies (Boyacá, Caquetá, Cundinamarca, Santander and Sucre) considering urban and rural areas and their interaction (connectivity) in the urban-rural interface. For this purpose, an epidemiological compartmental model considering a classification of individuals according to their economic activity and their epidemiological status was assessed. Preventive measures focused on the urban-rural interface impact the number of deaths in rural areas. Hence, it is possible to assume that the dynamics of the disease in rural areas depend on the constant interaction with infected individuals from urban areas, which occurs due to the food production dynamics in the urban-rural interface. Preventive measures should focus on places of high transmissibility and risk for rural communities, such as the urban-rural interface. This work highlights the importance of national heterogeneous preventive measures and the protection of rural communities from the social and economic impacts of SARS-CoV-2.

Analysis of The Effect of Competence, Workload and Occupational Health and Safety (OHS): Promotion on The Safety Behavior of Health Workers at X Karawang Hospital

Hospitals as a place for health services can be dangerous and high-risk places for work safety. Work accidents are generally caused by two main things, namely unsafe behavior, and unsafe conditions, it is estimated that work accidents occur due to unsafe work behavior. The purpose of the study was to determine the effect of Competence, Workload, and OHS Promotion on the safety behavior of health workers at X Karawang Hospital. The research method used is causal associative research with quantitative techniques using a cross-sectional approach. The research population amounted to 417 people. Samples were taken using a purposive random sampling technique and obtained 179 samples of health workers. The results showed that Competence, Workload, OHS Promotion can affect the safety behavior of health workers. The conclusion of the study shows that Competence, Workload, OHS Promotion together can significantly affect the safety behavior of health workers, partially competence and health promotion variables have a significant effect on safety behavior, while the workload variable does not affect safety behavior. The implications of the research are expected to be input for the OHS committee and management on achieving zero accidents by ensuring all levels of management and all employees follow the OHS policy without exception, providing adequate facilities and resources so that health and safety policies can be implemented properly including regular OHS training, evaluation of implementation, reward and punishment.

Street images classification according to COVID-19 risk in Lima, Peru: a convolutional neural networks feasibility analysis

ObjectivesDuring the COVID-19 pandemic, convolutional neural networks (CNNs) have been used in clinical medicine (eg, X-rays classification). Whether CNNs could inform the epidemiology of COVID-19 classifying street images according to...

An Investigation of Changes in Hospital Emergency Room during the Era of Covid-19 Outbreak: An Analysis of Literature Review

The frontline of hospital in providing health services related to Covid-19 outbreak is the Emergency Room (ER), so that it comes as a high-risk place for Covid-19 transmission among patients and patients as well as patients and health workers in the medical context. To prevent the transmission, several changes should be done in ER during Covid-19 pandemic. Besides, this research aimed at analyzing the changes made to ER as an effort to prevent and control Covid-19 infection which could be utilized as a recommendation for the ER towards other hospitals during this epidemic disease. The method used in this article was a literature review by researching the design through Google Scholar, Mendeley, and PubMed. The keywords included emergency department, hospital, changes, guidelines, preparedness, and Covid-19. The criteria of selected articles were published in 2020 using full English text, and the type of research was descriptive qualitative research. In addition, the total of the articles were 5 used articles which should match the research criteria related to the topic of the research. Based on the results of the literature reviews from the experts, the changes made to ER during the Covid-19 pandemic were divided into 3 parts such as preparation, pre-triage and during triage. Likewise, the made changes during the preparation consisted of organizational structure and leadership, human resource management, infrastructure, and logistics. Likewise, the changes made during pre-triage were online clinics and patient screening. At last, the change made during triage was in line with the patients’ triage flow.

Etiological Characteristics and Treatment Outcomes of Eye Lid Laceration: A Hospital Based Prospective Study

Introduction: Lid laceration is a very common peri-ocular trauma. Regarding the etiology and treatment, it lacks studies in developing nations including Nepal.&#x0D; Aims: To assess the etiological characteristics and treatment outcomes of eyelid laceration.&#x0D; Methods: In this study, 47 cases of traumatic eyelid laceration were consecutively studied and its epidemiology, etiology and treatment outcome were evaluated.&#x0D; Results: The 47 patients were included in the study. The mean age of study population was 26.14 ± 18.02 years. Male: female ratio was 1.6:1. The trauma occurred on road in 34 (72.3%) cases, followed by at home (14.9%), at work place (8.5%) and at entertainment areas (4.2%). The most common mode of injury was road traffic accident (72.3%) followed by fall injury (17%), Physical assault (6.4%) and animal bite (4.3%). The 68.1% of had isolated lid laceration, 12.7% had other adnexal injuries and 10.6% had globe injuries, 8.5% had other facial injuries and only 4.1% had systemic trauma. The partial thickness laceration was observed on 42(89.4%) cases and full thickness laceration on 5 (10.6%) cases. The length of lid laceration ranged from 4- 45 mm (mean ±SD was 14.7±8.3 mm). The 14.9% cases had canalicular laceration. The 85% of the laceration healed without visible scar. Only 4 patients (8.5%) had thick hypertrophic scar. The visual function was intact in 44 patients whereas impaired in 3 patients with accompanying open globe injury. The complications noted were hypertrophic scar (8.6%), wound infection (2.1%), ectropion (2.1%), corneal opacity (2.1%) and phthisis bulbi (2.1%).&#x0D; Conclusion: This study highlights the high-risk people and work place for eyelid laceration and the safety precautions in dangerous settings, including daily and routine work places. Only accompanying open globe injury can damage visual function.

Regression Analysis for COVID-19 Infections and Deaths Based on Food Access and Health Issues.

COVID-19, or SARS-CoV-2, is considered as one of the greatest pandemics in our modern time. It affected people’s health, education, employment, the economy, tourism, and transportation systems. It will take a long time to recover from these effects and return people’s lives back to normal. The main objective of this study is to investigate the various factors in health and food access, and their spatial correlation and statistical association with COVID-19 spread. The minor aim is to explore regression models on examining COVID-19 spread with these variables. To address these objectives, we are studying the interrelation of various socio-economic factors that would help all humans to better prepare for the next pandemic. One of these critical factors is food access and food distribution as it could be high-risk population density places that are spreading the virus infections. More variables, such as income and people density, would influence the pandemic spread. In this study, we produced the spatial extent of COVID-19 cases with food outlets by using the spatial analysis method of geographic information systems. The methodology consisted of clustering techniques and overlaying the spatial extent mapping of the clusters of food outlets and the infected cases. Post-mapping, we analyzed these clusters’ proximity for any spatial variability, correlations between them, and their causal relationships. The quantitative analyses of the health issues and food access areas against COVID-19 infections and deaths were performed using machine learning regression techniques to understand the multi-variate factors. The results indicate a correlation between the dependent variables and independent variables with a Pearson correlation R2-score = 0.44% for COVID-19 cases and R2 = 60% for COVID-19 deaths. The regression model with an R2-score of 0.60 would be useful to show the goodness of fit for COVID-19 deaths and the health issues and food access factors.

An integrated model of aircraft routing and crew rostering problems to develop fair schedule for the crew under COVID-19 condition

This paper focuses on aircraft routing and crew rostering problems simultaneously considering the risk of COVID-19 infection. As airports are among high-risk places in COVID-19 pandemic, the crew prefer to spend less sit time in airports and come back to their home base at the end of each duty day. In this research, an integrated model is developed to assign crew and aircraft to flights in order to achieve a fair schedule for the crew. The objective function is minimisation of the difference between crew sit times. Moreover in this model, a framework including flight hours, number of days and number of take-offs is considered for maintenance requirements. Particle swarm optimisation (PSO) is used as the solution approach. To validate the solution approach, 20 test problems were solved using GAMS and PSO. The results show that PSO improved CPU time significantly (98.279% in average) in turn of 1.902% gap with GAMS in optimum solution.