Surges In Demand Research Articles

Determinant Factors of Limited Oxygen Supply at Marsudi Waluyo Hospital during the Covid-19 Pandemic

The demand for oxygen in hospitals has been increasing during the Covid-19 pandemic due to oxygen therapy required by most Covid-19 patients. Fulfillment of oxygen supply is related to logistics management. This study aimed to determine the factors affecting the limited oxygen supply at Marsudi Waluyo Hospital, Malang. This research was conducted with a qualitative descriptive method. Data collection was carried out by observing the process of ordering and replacing oxygen cylinders for central oxygen fulfillment at the Facility Maintenance Unit (FMU), reviewing oxygen usage and supply reports, and conducting Focus Group Discussion (FGD) to identify the root of the problem. The FGD respondents consisted of the Head of General Affairs and Administration, the Head of Finance, the Coordinator and Staff of the Facility Maintenance Unit, and the Head of the Inpatient Installation. The root of the problem was compiled using the 5 Whys method and grouped into Man, Material, Money, Method, Machine, Management, and Environment categories. The root of the problem identified was the limited number of human resources in the Facility Maintenance Unit, the procedure for procuring oxygen cylinders that did not include a case of oxygen demand surge, and no oxygen supply other than oxygen cylinders.

Modeling the impact of mitigation policies in a pandemic: A system dynamics approach

In the absence of effective and adequate vaccines, healthcare decision-makers must rely on non-pharmaceutical interventions (NPIs), such as lockdown, testing, hospital capacity building, and increasing the number of medical staff to control the outbreak of an infectious disease like COVID-19. This manuscript presents a System Dynamics (SD) model to analyze the healthcare system performance under various NPIs during a pandemic. The proposed model, which extends the commonly-used Susceptible-Exposed-Infectious-Recovered (SEIR) model, comprises four sub-models: outbreak, hospital performance, medicine supply, and staff functionality. These sub-models work in harmony to stimulate the impact of NPIs on the disease outbreak pattern and the healthcare system's response to demand surge. The proposed model considers the uncertainty about the nature of the disease, the public's behavior, medicine availability, and medical staff efficiency. The proposed model was applied for the ex-ante evaluation of candidate NPIs adoptable against the COVID-19 outbreak in Iran. Consistent with the reported statistics, the results show that the peak demand can significantly exceed the healthcare system's initial capacity if no action is taken. If simultaneously implemented, lockdown and testing can considerably delay the peak of infections, reduce its magnitude, dampen the hospital demand, and decrease mortality. The proposed model is unique as it determines the extent to which system components (e.g., community, healthcare system, and medicine supply chain) impact the observed outcomes (e.g., morbidity and mortality rates). Its structure is generic and flexible, which facilitates the extension and application of the model to evaluate candidate mitigation policies in various geographical contexts.

A GIS enhanced data analytics approach for predicting nursing home hurricane evacuation response.

Nursing homes (NHs) are responsible for caring for frail, older adults, who are highly vulnerable to natural disasters, such as hurricanes. Due to the influence of highly uncertain environmental conditions and varied NH characteristics (e.g., geo-location, staffing, residents' health conditions), the NH evacuation response, namely evacuating or sheltering-in-place, is highly uncertain. Accurate prediction of NH evacuation response is important for emergency management agencies to accurately anticipate the NH evacuation demand surge with healthcare resources proactively planned. Existing hurricane evacuation research mainly focuses on the general population. For NH evacuation, existing studies mainly focus on conceptual studies and/or qualitative analysis using a single source of data, such as surveys or resident health data. There is a lack of research to develop analytics-based method by fusing rich environmental data with NH data to improve the prediction accuracy. In this paper, we propose a Geographic Information System (GIS) data enhanced predictive analytics approach for forecasting NH evacuation response by fusing multi-source data related to storm conditions, geographical information, NH organizational characteristics as well as staffing and residents characteristics of each NH. In particular, multiple GIS features, such as distance to storm trajectory, projected wind speed, potential storm surge and NH elevation, are extracted from rich GIS information and incorporated to improve the prediction performance. A real-world case study of NH evacuation during Hurricane Irma in 2017 is examined to demonstrate superior prediction performance of the proposed work over a large number of predictive analytics methods without GIS information.

Integrated delivery of family planning and childhood immunisation services: A causal loop analysis of service responsiveness in Malawi

Evidence suggests that integrating family planning (FP) services with childhood immunisations can increase postpartum contraceptive use by providing timely contact with FP services during the year following childbirth. However, little is known about clients' experiences of FP services within this context. Systems thinking was applied to examine the responsiveness of FP services that were integrated with childhood immunisations in routine outreach clinics across two districts of Malawi. A causal loop analysis of qualitative data captured through 1) structured exit interviews with clients (n=146) and 2) semi-structured interviews with clients (n=23) and their FP providers (n=10) was carried out to explain the system dynamics influencing the responsiveness of integrated FP services. Through this analysis, six feedback loops were identified as having a balancing effect on service responsiveness. Importantly, the clinic's client load was found to drive the responsiveness experienced by clients in the studied context. Overall, the results suggest that efforts to enhance the responsiveness of integrated FP services in outreach clinics should focus on 1) enhancing the providers' ability to alter the client flow in response to fluctuations in the clinic's client load, and 2) ensuring that an appropriate buffer of FP supplies is available in clinics to enable clients to consistently receive their preferred contraceptive irrespective of surges in demand. This study represents the first attempt at modelling the responsiveness of integrated FP services and its findings can be used to inform the design and delivery of FP services that are integrated with childhood immunisations in different settings.

Optimising the turning performance of serial split-hull underwater vehicles

This paper discusses optimising the 2D turning performance of serial split-hull underwater vehicles with symmetric hulls. Compared to traditional single-hull solutions, their unique design makes them appealing for bathymetry. Analysis of the turning motion of such vehicles is a topic of tremendous research interest. During the turning motion of an underwater vehicle, the lateral forces demand both surge and sway thrusters to maintain the path without slipping. This impacts the vehicle operation, making it harder to control, and uses more power. The net lateral force and associated sway thrust requirements can be significantly reduced using a split-hull design, where the individual hulls can have different orientations. It is possible to eliminate the sway thruster and cover the circular path using a split-hull underwater vehicle. The existence of the optimal turning configuration is proved where the need for lateral thrust is minimal compared to the axial one. The effects of turning diameter, joint torque, and axial thrust are also considered when choosing the vehicle configuration for the specific operational requirement. Experiments are used to validate the outcomes of the modelling and simulation. The knowledge gained here will aid in developing and effectively operating similar vehicles.

Design and FEM Analysis of High-Torque Power Density Permanent Magnet Synchronous Motor (PMSM) for Two-Wheeler E-Vehicle Applications

Launch of electric vehicles have seen a substantial rise for the past few years in emerging economies like India. In countries like India, the growth and penetration of the electric vehicles in the Indian automotive industry specifically for the two-wheeler segments are driven by the demand surge where cost and motor metrics have a substantial deciding factor. The in-wheel hub-motor, which is the prime mover for the two wheelers, decides the comfort zone of the customer in various metrics such as efficiency, torque, speed range, charging, and hence the distance covered. This paper addresses the design formulation of achieving a high torque Permanent Magnet Synchronous Motor (PMSM) conventionally known as the hub-motor, explicitly for electric two-wheeler application. The hub-motor is aimed for the defined D and L (280 × 30 mm) of volumetric constraints to deliver the rated torque of 50 Nm at the spinning speed of 400 rpm. The hub-motor design is aimed for distance range of 108 km/charge, at the vehicle speed of 54 km/hr for the designed diametric and volumetric constraints. This will lead to a typical cost-effective e-vehicle system since the required distance range of 108 km is achievable at the defined rim size and geometry with an enhanced efficiency greater than 90%. The design is carried out by Finite Element Analysis (FEA) using the electromagnetic software MotorSolve. The results computed are analyzed and validated for the optimal loading conditions for the ambient temperature of 50°C. The results confirm the effectiveness of the proposed design formulation and methodology for achieving the high power density hub-motors for satisfying the customer’s comfort zone in establishing the performance metrics of the electromagnetic system.

An integrated distribution scheduling and route planning of food cold chain with demand surge

With the rapid development of e-commerce, customers could order online to ensure timeliness. Therefore, e-commerce enterprises need to pick and distribute customers’ orders. These two operations are interdependent. Order picking needs to consider the vehicle route planning. At the same time, the vehicle route planning is also based on the batching of orders. Considering the demand surge scenario of food cold chain, with the shortest time and lowest cost to complete all distribution tasks as the objective, this paper aims at the integrated optimization of distribution scheduling and route planning, and establishes a mixed integer programming mathematical model. Finally, we design a three-stage heuristic algorithm to solve this problem, and use the actual data to carry out numerical experiments to verify the reliability and effectiveness of the mathematical model and heuristic algorithm.

Integrated Online Order Picking and Vehicle Routing of Food Cold Chain with Demand Surge

This paper focuses on the effect of demand surge on the food cold chain, where orders arrive online. The demand surge has successively affected the order batching, batch sequencing, and route planning, compared to regular demand. This research studies the integrated optimization of food cold chain order picking and vehicle routing of online orders, where mixed integer programming model is formulated to minimize time-consuming and cost. We firstly use K-means++ algorithm to cluster all customers, and then an online batch processing algorithm is designed in each region. Finally, a genetic algorithm is used to complete the joint optimization of the picking and delivery. We use X enterprise’s e-commerce platform as a case to collect actual operating data to verify the effectiveness of the model and algorithm. And comparing the analysis results between phased optimization and integrated optimization, reasonable suggestions are put forward for management decisions.

Implementation of a Comprehensive Testing Protocol for a Rapidly Manufactured Mechanical Ventilator

IntroductionThe COVID-19 pandemic highlighted that surges in critical care demand can overwhelm existing healthcare infrastructures, most evident in the acute shortage of mechanical ventilators across the globe. Despite efforts to encourage urgent authorization of newly developed emergency ventilators, the currently available testing protocols are not internationally accepted, standardized and none address testing in clinical settings. The aim of this study was to compile and perform a comprehensive clinical testing protocol for a newly developed emergency ventilator. MethodsUsing previously available guidance, we compiled a sequential testing protocol with a: 1. preclinical, 2. safety testing, 3. clinician usability test and 4. clinical stage involving respiratory failure patients. The protocol was then tested on the Luca ventilator, a mechanical ventilator capable of sophisticated ventilator settings rapidly developed specifically in response to the COVID-19 pandemic. ResultsDuring the pre-clinical/safety stages, the ventilator produced pressure and volume changes deemed acceptable by the Rapidly Manufactured Ventilator System guideline. Furthermore, our protocol allowed the identification of a number of issues that were easily resolved with minor software adjustments. Usability was excellent (overall System Usability Scale score=90.5). Clinical testing revealed that a sampling frame of 15 critically ill patients was sufficiently powered to detect any significant, clinically relevant differences between the Luca ventilator and a standard ICU ventilator. ConclusionsThe ventilator was accurate, reliable, safe, and user-friendly. The implementation of a comprehensive, standardized pre-clinical/clinical testing protocol is feasible, potentially enabling the safe and timely emergency authorization of rapidly developed mechanical ventilators crucial in pandemic situations.

Effect of hospital case volume on clinical outcomes of patients requiring extracorporeal membrane oxygenation: a territory-wide longitudinal observational study

BackgroundThe utilization of extracorporeal membrane oxygenation (ECMO) has increased rapidly around the world. Being an overall low-volume high-cost form of therapy, the effectiveness of having care delivered in segregated units across a geographical locality is debatable.MethodsAll adult extracorporeal membrane oxygenation cases admitted to public hospitals in Hong Kong between 2010 and 2019 were included. “High-volume” centers were defined as those with >20 extracorporeal membrane oxygenation cases in the respective calendar year, while “low-volume” centers were those with ≤20. Clinical outcomes of patients who received extracorporeal membrane oxygenation care in high-volume centers were compared with those in low-volume centers.ResultsA total of 911 patients received extracorporeal membrane oxygenation—297 (32.6%) veno-arterial extracorporeal membrane oxygenation, 450 (49.4%) veno-venous extracorporeal membrane oxygenation, and 164 (18.0%) extracorporeal membrane oxygenation-cardiopulmonary resuscitation. The overall hospital mortality was 456 (50.1%). The annual number of extracorporeal membrane oxygenation cases in high- and low-volume centers were 29 and 11, respectively. Management in a high-volume center was not significantly associated with hospital mortality (adjusted odds ratio (OR) 0.86, 95% confidence interval (CI): 0.61–1.21, P=0.38), or with intensive care unit mortality (adjusted OR 0.76, 95% CI: 0.54–1.06, P=0.10) compared with a low-volume center. Over the 10-year period, the overall observed mortality was similar to the Acute Physiology And Chronic Health Evaluation IV-predicted mortality, with no significant difference in the standardized mortality ratios between high- and low-volume centers (P=0.46).ConclusionsIn a territory-wide observational study, we observed that case volumes in extracorporeal membrane oxygenation centers were not associated with hospital mortality. Maintaining standards of care in low-volume centers is important and improves preparedness for surges in demand.

Deferral of non-emergency cardiac procedures is associated with increased early emergency cardiovascular hospitalizations

BackgroundDuring the COVID-19 pandemic, in anticipation of a demand surge for high-care hospital beds, many hospitals postponed non-emergency interventions of cardiac patients.AimThe aim of this study was to assess the outcomes of cardiac patients whose non-emergency interventions had been deferred during the COVID-19 pandemic.MethodsPatients whose non-emergency cardiac intervention had been cancelled between March 19th and April 30th, 2020 were included (study group). All patients were considered as deferrable according to current recommendations. Patients’ outcomes after 12 months were compared to a seasonal control group who underwent non-emergency interventions in 2019 as scheduled. The primary endpoint was a composite of emergency cardiovascular hospitalization and death. Secondary endpoints were levels of symptoms and cardiac biomarkers.ResultsOutcomes of 193 consecutive patients in the study group were assessed and compared to 216 controls. The primary endpoint occurred significantly more often in the study group (HR 2.42, 95%CI 1.63–3.61, p < 0.001). This was driven by an increase in hospitalizations. Subgroup analyses showed that especially patients with a deferred transcatheter heart valve intervention experienced early emergency hospitalization (HR 9.55, 95%CI 3.70–24.62, p < 0.001). These findings were accompanied by more pronounced symptoms and higher biomarker levels.ConclusionsDeferral of non-emergency cardiac interventions to meet the higher demand for hospital beds during the COVID-19 crisis is associated with early emergency cardiovascular hospitalizations. Patients suffering from valvular heart disease especially constitute a vulnerable group. Consequently, our results suggest that current recommendations on the management of cardiovascular disease during the COVID-19 pandemic need revision.Graphical abstract

One crisis, different paths to supply resilience: The case of ventilator procurement for the COVID-19 pandemic

This research explores supply resilience through an equifinality lens to establish how buying organizations impacted differently by the same extreme event can strategize and all successfully secure supply. We conduct case study research and use secondary data to investigate how three European governments sourced for ventilators during the first wave of COVID-19. The pandemic had an unprecedented impact on the ventilator market. It disrupted already limited supply and triggered a demand surge. We find multiple paths to supply resilience contingent on redundant capacity and local sourcing options at the pandemic's onset. Low redundancy combined with limited local sourcing options is associated with more diverse strategies and flexibility. The most notable strategy is spurring supplier innovation by fostering collaboration among actors in disparate industries. High redundancy combined with multiple local sourcing options is associated with more focused strategies and agility. One (counter-intuitive) strategy is the rationalization of the supply base.

Characterizing relationship between demand surge and post-disaster reconstruction capacity considering poverty rates

The post-disaster reconstruction capacity of communities determines their survival after large-scale disasters. Unexpected and substantial increases in construction costs in response to the significant reconstruction demands following disasters, known as demand surge, can decrease reconstruction speed and limit the reconstruction capacity of communities. The objective of this research is to investigate the relationships between labor wage fluctuation (representing demand surge) and change in building permits (representing reconstruction capacity) of various communities considering their poverty rates. The county-level data of building permits, construction labor wages, and poverty rates were collected for the affected counties by devastating hurricanes. Multiple regression models were utilized to quantify the relationships between wage fluctuation and change in building permits in counties with above-average and below-average state poverty rates. The results show that wage fluctuation is negatively correlated with the change in building permits in counties with above-average poverty rates. In contrast, fluctuation does not show a statistically significant correlation with the change in building permits in counties with below-average poverty rates. These findings indicate that demand surge has a statistically significant negative relationship with the reconstruction capacity of counties with above-average poverty rates, while there is no meaningful relationship with the reconstruction capacity of counties with below-average poverty rates. The findings of this research can assist risk-mitigation agencies in identifying more sensitive communities, prioritizing the reconstruction needs, and enhancing risk reduction strategies considering the socioeconomic characteristics of communities.

Industrially scalable exfoliated graphene nanoplatelets by high-pressure airless spray technique for high-performance supercapacitors

The significance of Graphene-based materials in various energy conversion and storage devices has been increasing due to their high surface area helps to enhance the multidimensional storage capability. Even though a significant amount of work has been done on graphene synthesis, there is still a need for an economical and environmentally friendly large-scale graphene synthesis method. This work demonstrates the large-scale production of high-quality Graphene Nanoplatelets (GnPs) by high-pressure spray exfoliation to develop high-performance supercapacitors. The high-pressure exfoliated GnPs were used to construct symmetric supercapacitors and studied their performance in organic and aqueous electrolytes. The pronounced rectangularity of cyclic voltammetry (CV) curves in both electrolytes indicates the charge storage is mainly by electrical double layer mechanisms. Retaining rectangularity at very high scan rates (>1000 mV/s) in both electrolytes signifies the excellent rate performance of high pressure exfoliated GnP based supercapacitors. The maximum specific capacitance of 26 F g−1 in the organic electrolyte and 86 F g−1 in the aqueous electrolyte was experimentally demonstrated, comparatively better than many other graphene-based device reports. The high capacitance and energy retention in the organic and aqueous electrolyte at very high current densities (>15 A g−1) indicate the potential usage during the demand surge power supply of exfoliated GnPs for the commercialization of graphene-based supercapacitors.

The Effect of Tripping the US Equity Market-Wide Circuit Breaker on Liquidity: Evidence from the Coronavirus Selloff

We examine changes in market liquidity around the triggering of US equity market-wide circuit breakers (MWCBs). The coronavirus pandemic has led to heightened market volatility and the tripping of four MWCBs in 2020. When the market reopens following a MWCB halt, trading demand (volume) surges. The rise in trading coincides with shifts in trading activity across exchanges and dark markets, and the cost of trading rises significantly. Although the market is less liquid immediately after a halt, conditions steadily improve over time and converge to similar levels on days in which the MWCB does not trip.

Impacts of coal mine fire-related PM2.5 on the utilisation of ambulance and hospital services for mental health conditions

Climate change and an increase in the number of major fire events occurring around the world have drawn attention to the importance of understanding the association between air pollution events and mental health. In 2014, the Morwell open-cut brown coal mine adjacent to the Hazelwood power station in the Latrobe Valley region of Victoria, Australia, caught fire as a result of nearby wildfires, and exposed the local community to a prolonged period of deteriorated air quality. The aim of this study was to examine how exposure to coal mine fire-related fine particulate matter (PM2.5) during the event affected the utilisation of local health services (ambulance attendances; emergency department (ED) presentations; hospital admissions) for mental health conditions. A time-series analysis indicated that mine fire-related PM2.5 exposure was associated with short-term increases in ambulance attendances and ED presentations but not hospital admissions. To allow for delays between exposure and changes in service utilisation, different lag periods were assessed. The most prominent effects were observed over a 5-day lag period where, for each 10 μg/m3 increase in daily mean mine fire-related PM2.5, the risk of an ambulance attendance for anxiety increased by 38% (95%CI: 13%–69%) and the risk of an ED presentation for depression increased by 36% (95%CI: 3%–79%). Accordingly, ambulance and hospital services should expect to encounter an increase in the number of people seeking assistance for mental health conditions during extreme air pollution events and mechanisms need to be in place to ensure that surges in demand for mental health care during these circumstances can be accommodated.

A framework for critical care triage during a major surge in critical illness

During the COVID-19 pandemic, many jurisdictions experienced surges in demand for critical care that strained or overwhelmed their healthcare system’s ability to respond. A major surge necessitates a deviation from usual practices, including difficult decisions about how to allocate critical care resources. We present a framework to guide these decisions in the hope of saving the most lives as ethically as possible, while concurrently respecting, protecting, and fulfilling legal and human rights obligations. It was developed in Ontario in 2020–2021 through an iterative consultation process with diverse participants, but was adopted in other jurisdictions with some modifications. The framework features three levels of triage depending on the degree of the surge, and a system for prioritizing patients based on their short-term mortality risk following the onset of critical illness. It also includes processes aimed at promoting consistency and fairness across a region where many hospitals are expected to apply the same framework. No triage framework should ever be considered “final,” and there is a need for further research to examine ethical issues related to critical care triage and to increase the extent and quality of evidence to inform critical care triage.

Designing Hybrid Mechanisms to Overcome Congestion in Sequential Dutch Auctions

A common problem in many mature markets is how to deal with congestion—a situation in which transaction requests from market participants cannot be accommodated in an expedited manner. This paper examines the congestion problem in sequential Dutch auction markets. Transactions in these markets typically involve perishable goods, making market clearing speed crucial. Traditionally, sequential Dutch auctions have been implemented with fast-paced auction clocks that process equally attractive bids in the order they arrive and only award the first bidder as the winner of each round, which can lead to serious congestion in case of a demand surge. We propose a hybrid mechanism that capitalizes on the discrete nature of the auction clock and batches together the highest bids, allowing multiple transactions at the same price in each round. To evaluate the performance of the hybrid mechanism, we first develop a game-theoretic model comparing the hybrid mechanism to the traditional sequential Dutch auction mechanism. Our model predicts that the hybrid mechanism will achieve higher operational efficiency without compromising allocative efficiency. We then complement the theoretical analysis by evaluating the hybrid mechanism through a quasi-natural field experiment. The empirical analysis of the field data shows that the hybrid mechanism can significantly speed up the market clearing process and increase price stability without affecting the expected revenue. Our findings shed new light on the design and operation of multi-unit auctions.

Minding Braess Paradox amid third-party logistics hub capacity expansion triggered by demand surge

Third-party logistics (3PL) in the U.S. has been declared essential by the government and 3PL firms are tasked to continue their operations amid the pandemic. Meanwhile, demand for e-commerce deliveries have exploded due to strict enforcement of lockdowns and the public's preference to avoid physical contacts. To process the record increase in volume, 3PL firms have expanded capacities of their consolidation hubs. However, expansion in a hub capacity might risk delay propagation through the hub's conveyer systems and lead to a counterintuitive phenomenon known as Braess Paradox (BP). We present two layouts (Two-Way Secondary Sort and Direct Sorting) that are commonly employed in the 3PL hubs to accommodate high volumes. We then extend by differentiating 3PL's traffic into Regular and Express packages and include penalty cost in the model. The results show that the BP may occur in 3PL hub settings. However, both layouts are impacted differently. We compare the performances of the two sorting layouts and present value ranges where the benefits of one layout might outweigh the other in hub operations. We also expand the two-tier model by adding an extra tier of package type (i.e., Critical Package) and provide findings that are more generic to any multiple-tier model. Our findings help in identifying the conditions that 3PLs can avoid BP and improve their hub performances with suitable configurations of flow layout.

Digitally enabled supply chain as a strategic asset for the COVID-19 response in Alberta.

This provincial case study, one of seven conducted as part of a national research program on healthcare supply chain management during COVID-19, focuses on Alberta. With a history of emergency preparedness, Alberta’s unique context, one that includes having an already established, centralized, and digital healthcare supply chain strategy, sets this case apart from the others in terms of pandemic responses. A key challenge navigated by Alberta was the inadequacies of traditional sourcing and procurement approaches to meet surges in product demand, which was overcome by the implementation of unique procurement strategies. Opportunities for Alberta included the integration of supply chain teams into senior leadership structures, which enabled access to data to inform public health decision-making. This case demonstrated how Alberta’s healthcare supply chain assets—its supply chain infrastructure, data, and leadership expertise, especially—contributed to resilient supply chain capacity across the province.