Evacuation Costs Research Articles

Costs of medical evacuation and transportation of First Nations Peoples and Inuit who travel for medical care in Canada: A systematic review.

For First Nations people and Inuit who live on reserves or in rural and remote areas, a guideline requires their travel to urban centres once their pregnancy reaches 36-38weeks gestation age to await labour and birth. While not encoded in Canadian legislation, this guideline-and invisible policy-is reinforced by the lack of alternatives. Research has repeatedly demonstrated the harm of obstetric evacuation, causing emotional, physical, and financial stress for pregnant and postpartum Indigenous women and people. Our objective was to describe the costs of obstetric evacuation, as reported in the literature. We conducted a systematic review using online searches of electronic databases (Ovid EMBASE, CINAHL, Ovid Healthstar, PubMed, ScienceDirect, PROSPERO, and Cochrane Database of Systematic Reviews) and identified studies that reported costs related to medical evacuation or transportation in rural and remote Indigenous communities. We performed critical appraisal of relevant studies. We identified 19 studies that met the inclusion criteria. The studies reported various types of cost, including direct, indirect, and intangible costs. Medical evacuation costs ranged from CAD $7714 to CAD $31,794. Indirect and intangible costs were identified, including lost income and lack of respect for cultural practices. Costs associated with obstetric evacuation are high, with medical evacuation as the most expensive direct cost identified. Although we were able to identify a range of costs, information on financing and funding flows was unclear. Across Canada, additional research is required to understand the direct costs of obstetric evacuation to Indigenous Peoples and communities.

A cost-benefit analysis of WildFireSat, a wildfire monitoring satellite mission for Canada.

In anticipation of growing wildfire management challenges, the Canadian government is investing in WildFireSat, an Earth observation satellite mission designed to collect data in support of Canadian wildfire management. Although costs of the mission can be reasonably estimated, the benefits of such an investment are unknown. Here we forecast the possible benefits of WildFireSat via an avoided cost approach. We consider five socio-economic components: suppression costs (fixed and variable), timber losses, property, asset and infrastructure losses, evacuation costs, and smoke related health costs. Using a Monte Carlo analysis, we evaluated a range of possible changes to these components based on expert opinions. The resulting Net Present Value (NPV) estimates depend on the presumed impact of using WildFireSat decision support data products, with pessimistic and conservative assumptions generating mission costs that typically exceed potential benefits by 1.16 to 1.59 times, while more optimistic assumptions generate benefits in excess of costs by 8.72 to 10.48 times. The analysis here excludes some possibly significant market and non-market impacts expected from WildFireSat due to data limitations; accounting for these additional impacts would likely generate positive NPVs under even cautious impact assumptions.

Understanding household evacuation preferences during the COVID-19 pandemic in Puerto Rico

The added threat from the COVID-19 pandemic created a complex dilemma for households that were also facing evacuation decisions during natural disasters. This paper characterized household concerns and evacuation preferences in the context of both hurricanes and pandemic risks. We conducted a survey of 504 households across 119 different zip code areas in Puerto Rico impacted by Hurricane Maria (2017). The households were asked to make a choice between staying isolated at home or evacuating with or without isolation in the event of a future hurricane threat during a pandemic. Our findings revealed that households, in the early stages of the COVID-19 pandemic, expressed greater concern about the risks associated with a pandemic compared to those related to hurricanes, and that there was a risk–risk trade-off when making the critical evacuation decision. In addition to hurricane-related concerns, past evacuation experiences, and the consideration of evacuation costs, we found that evacuation preferences were heterogeneous across age, gender, and ethnic groups, and were also driven by perceptions of infection risks and attitudes towards social distancing. Our research aimed to provide valuable insights to help develop effective responses and preparations for coastal hurricanes that consider the complexities of multiple hazards and health risks.

Route Dominance on Symmetric Type Transit-based Evacuation Network

The selection of dominant routes for transit-based evacuation planning problems mainly depends upon the structure and nature of the available network. To achieve efficient evacuation planning, the problem is not only on the selection of a route and a shelter for each route on the available network topology but also on the route-to-vehicle assignment and vice versa, which is more complex and challenging in real practice. The evacuation network adds complexity to the solution and impacts the problem. In this paper, the transit-based evacuation network has been revised from different perspectives focusing on the symmetric type networks with their dominant evacuation planning routes to have the minimum evacuation cost.

Treaties for "offshoring" hospital treatment of Asian patients from Christmas Island, 1963-1985: a racist chapter in the history of Australian medical care.

Treaties for "offshoring" hospital treatment of Asian patients from Christmas Island, 1963-1985: a racist chapter in the history of Australian medical care.

Effect of floor openings on evacuation efficiency in multipurpose commercial buildings: IFC mall in Yeouido, Seoul, Korea

ABSTRACT To achieve evacuation-optimized design at the architectural planning phase, this study analyzed the effect of floor openings in multipurpose commercial buildings on their evacuation efficiency. Herein, the IFC Mall in Yeouido, Seoul, Korea was considered the study site, because all the factors influencing the evacuation efficiency can be controlled owing to the underground location of all floors. Therefore, all evacuees followed the same evacuation direction. Comprehensively, a spatial analysis methodology(Cellular ECEM) was employed to derive the evacuation costs through the sum of visibility cost and distance cost. Subsequently, the evacuation costs were compared in all cases to review the hindrances in evacuation according to the type and area ratio of the planned floor opening, and several causes of evacuation cost deviations were discussed. Overall, increasing the area of the floor opening deteriorates the evacuation efficiency. The evacuation efficiency increased if the area of the floor opening is appropriately separated and a bridge is constructed in the middle to connect a path. Furthermore, following the longer path around the floor opening to use the main vertical means of circulation, owing to the connection between the atrium and floor opening, is more vulnerable toward evacuation efficiency than other floor opening types.

A Spatio-Temporal Cognitive Framework for Individual Route Choice in Outdoor Evacuation Scenarios

Route choice is a complex issue in simulating individual behaviors and reproducing collective phenomena during evacuations. A growing concern has been given to the individual cognitive mechanism to investigate how routing decisions are made in specific situations. However, the essential role of multiple spatio-temporal scales has not been completely considered in the current cognitive frameworks, which leads to the inaccuracy of cognition representation in evacuation decisions. This study proposes a novel spatio-temporal cognitive framework integrated with multiple spatio-temporal scales for individual route choice. First, a complete spatio-temporal cognitive mechanism is constructed to depict the individual evacuation cognition process. Second, a spatio-temporal route choice strategy that emerges from agent-based simulation and extends into the spatio-temporal potential field is designed to represent the overall time-varying cost along routes in individual subjective estimation. Finally, a spatio-temporal A* algorithm is developed for individual optimal route planning in complex outdoor evacuation scenarios. The experimental results show that the proposed framework outperformed the conventional potential field model in evacuation performance, in both objective crowd evacuation evaluation metrics and individual subjectively estimated evacuation cost in cognition, and may provide more insights on crowd evacuation management and guidance.

Estimating Future Residential Property Risk Associated with Wildfires in Louisiana, U.S.A.

Wildfire is an important but understudied natural hazard in some areas. This research examined historical and future wildfire property risk at the census-block level in Louisiana, a U.S.A. state with relatively dense population and substantial vulnerability to loss from wildfire, despite its wet climate. Here wildfire risk is defined as the product of exposure and vulnerability to the hazard, where exposure is a function of the historical and anticipated future wildfire frequency/extent, and vulnerability is a function of population, structure and content property value, damage probability, and percent of properties damaged. The results revealed a historical (1992–2015) average annual statewide property loss due to wildfire of almost USD 5.6 million (in 2010 USD), with the greatest risk in southwestern inland, east-central, extreme northwestern, and coastal southwestern Louisiana. The geographic distribution of wildfire risk by 2050 will remain similar to that today, but the magnitude of losses was projected to increase statewide to over USD 11 million by 2050 (in 2010 USD), an increase of more than 100% over 2010 values. These estimates are conservative, as they did not include crop, forestry, or indirect losses (e.g., cost of evacuation and missed time at work). Overall, results suggested that increased efforts are needed to contain wildfires, to reduce the future risk of this increasing and underestimated hazard.

Departure Timing Preference during Extreme Weather Events: Evidence from Hurricane Evacuation Behavior

Hurricane evacuation has become an increasingly complicated activity in the U.S. as it involves moving many people who live along the Atlantic coast and Gulf coast within a very limited time. A good deal of research has been conducted on hurricane evacuation, but only a limited number of studies have looked into the timing aspect of evacuation. This paper intends to contribute to the literature on evacuation timing decisions by investigating what factors influence the time preference at the household level. Two hurricane survey data sets were used to analyze household evacuation behaviors across the Gulf coast as well as the Northeast and Mid-Atlantic coast in a comparative perspective. Using the Heckman selection model, we examined various factors identified in the literature on the two possible outcomes (evacuation and early evacuation). We found that the most important determinants of evacuation were prior evacuation experience, evacuation orders, and risk perceptions, while the most important determinants of early evacuation were prior evacuation experiences, days spent at the evacuation destination, and the cost of evacuation. Socioeconomic factors also influenced the two decisions but differently. These results provide implications for future hurricane evacuation planning and for improving emergency management practices.

Factors to Promote Ocean Energy in India

India's energy demand is expected to rise to 4000 TWh by 2030. The country will require five times more renewable energy (RE) in 2030 to meet the policy targets. The current RE development plans are land-intensive, highly intermittent, low-capacity utilization, and the inability to support the baseload requirement. It is time for India to diversify its RE basket and accommodate ocean energy (OE) in its policy landscape. Studies have identified factors for RE sources such as solar, onshore wind, and offshore wind etc. Literature clarifies that policy plays a vital role in developing RE. Hence, this study aims to identify the factors for OE development. The responses were collected from the stakeholders interested in RE development in India. This study has ranked grid connection and capacity building as the top two variables using the weighted average method. Factor Analysis results identified six factors: government support, regulatory and fiscal incentives, financing mechanisms, economic tools, promotion of local content, and capacity-building for research and skill development. Promotion of local content and capacity-building are additions to the literature as factors. This paper advocates the socialisation of evacuation cost, financial, fiscal certainty and continuity, priority sector lending, and demand-supply side support for OE development.

Warning Decision-Making for Landslide Dam Breaching Flood Using Influence Diagrams

Warning and evacuation are among the most effective ways for saving human lives and properties from landslide dam hazards. A new warning decision model for landslide dam break is developed using Influence Diagrams to minimize the total losses. An Influence Diagram is a simple visual representation of a decision problem. It analyzes the qualitative (causal) relationships between the variables via a logic diagram and determines the quantitative relationships via conditional probability and Bayes’ theorem. The model is applied for the warning decision-making of the 2008 Tangjiashan landslide dam. The new model unifies the dam failure probability, evacuation, life loss, and flood damage in an Influence Diagram. Besides, a warning criterion is proposed for efficient decision-making. The model is more advanced than the decision tree since the inter-relationships of influence factors are qualitatively analyzed with causality connections and quantitatively analyzed with conditional probabilities. It is more efficient than a dynamic decision-making model (DYDEM) as it can directly calculate the three types of flood loss (i.e., evacuation cost, flood damage, and monetized life loss) and the expected total loss. Moreover, the probabilities of the influence factors leading to known results can be obtained through inversion analysis based on Bayesian theory. The new warning decision model offers an efficient way to save lives from landslide dam breaking and avoid unnecessary expenses from premature warning and evacuation.

Penetapan Tarif Ambulans Untuk Evakuasi Medis Berbasis Unit Cost

Background:
 An ambulance is a vehicle designed to be able to handle emergency patients, provide first aid and carry out intensive care while on the way to a referral hospital. Ambulance operations require a large amount of funds obtained from APBD funds through tariffs that were passed through the DKI Jakarta Governor Regulation five years ago. For this reason, a new tariff is required to adjust to current conditions.
 Objectives:
 The purpose of this study is to calculate the unit cost of ambulance services in DKI Jakarta to be a consideration in the tariff setting policy in DKI Jakarta province.
 Research Metodes: 
 This study uses a quantitative descriptive approach to obtain information about the unit cost of the Jakarta ambulance production unit. The method used is the calculation of real cost using the basis of the causes of costs. This research was conducted at the DKI Jakarta Emergency Ambulance using secondary data on investment costs, operational costs and maintenance costs in 2018.
 Results: 
 The total cost of emergency ambulance in 2018 is known that the proportion of three cost components, namely operational costs, is 76%, followed by investment costs of 20% and maintenance costs of 3%. The calculation of the total cost of medical evacuation using the double distribution method is Rp. 98,915,016,805.00 divided by the number of medical evacuations in 2018 of 37,564 activities, the unit cost of medical evacuation for the AGD of DKI Jakarta Health Office is Rp. 2,633,215.00 without subsidies. APBD costs, while if the subsidy component is included in the calculation, the unit cost for one trip to the AGD of the Health Office is Rp. 604,071.00. This is still far above the current tariff of Rp. 450.00, so the cost recovery rate (CRR) is still below. 100%.
 Conclusion: 
 From the three cost components consisting of investment, operational and maintenance costs,the largest proportion was operational costs at 76%. The Cost Recovery Rate has not reached 100% so that the existing rates have not covered the costs incurred.
 
 Keywords: ambulance; price fixing; unit cost

Penetapan Tarif Ambulans Untuk Evakuasi Medis Berbasis Unit Cost (Penelitian di AGD Dinas Kesehatan DKI Jakarta)

Background:
 An ambulance is a vehicle designed to be able to handle emergency patients, provide first aid and carry out intensive care while on the way to a referral hospital. Ambulance operations require a large amount of funds obtained from APBD funds through tariffs that were passed through the DKI Jakarta Governor Regulation five years ago. For this reason, a new tariff is required to adjust to current conditions.
 Objectives:
 The purpose of this study is to calculate the unit cost of ambulance services in DKI Jakarta to be a consideration in the tariff setting policy in DKI Jakarta province.
 Research Metodes: 
 This study uses a quantitative descriptive approach to obtain information about the unit cost of the Jakarta ambulance production unit. The method used is the calculation of real cost using the basis of the causes of costs. This research was conducted at the DKI Jakarta Emergency Ambulance using secondary data on investment costs, operational costs and maintenance costs in 2018.
 Results: 
 The total cost of emergency ambulance in 2018 is known that the proportion of three cost components, namely operational costs, is 76%, followed by investment costs of 20% and maintenance costs of 3%. The calculation of the total cost of medical evacuation using the double distribution method is Rp. 98,915,016,805.00 divided by the number of medical evacuations in 2018 of 37,564 activities, the unit cost of medical evacuation for the AGD of DKI Jakarta Health Office is Rp. 2,633,215.00 without subsidies. APBD costs, while if the subsidy component is included in the calculation, the unit cost for one trip to the AGD of the Health Office is Rp. 604,071.00. This is still far above the current tariff of Rp. 450.00, so the cost recovery rate (CRR) is still below. 100%.
 Conclusion: 
 From the three cost components consisting of investment, operational and maintenance costs,the largest proportion was operational costs at 76%. The Cost Recovery Rate has not reached 100% so that the existing rates have not covered the costs incurred.

Health technology assessment of telemedicine applications in Northern borders of India

BackgroundEconomic evaluations of health technology help to decide which interventions are to be continued and which are to be terminated. In the Armed Forces, the provision of efficient medical services requires meticulous planning for optimal utilization of scarce resources. We report a cost analysis of telemedicine and air transportation of casualties, and attempt to identify the strengths, weaknesses, opportunities and threats of telemedicine services. MethodsThe costs incurred in telemedicine were compared with the cost of air evacuation. A qualitative assessment of telemedicine was undertaken through in-depth interviews with the hospital authorities and focused group discussions with medical officers and paramedical staff. Results34.2% of casualties could successfully be stabilized on-site using available healthcare resources with the peripheral hospitals. 18 casualties were managed at the periphery on-site by teleconsultations each year, averting air-transportation efforts. Estimated cost savings achieved in the initial management of casualty by teleconsultation was Rs. 146,111 per case. The strengths of telemedicine are knowledge updation, faster decision making, improved pre-hospital care and improved confidence in case management. ConclusionThe reduction in air efforts and remote management of casualties make a substantive case for scaling up telemedicine interventions.

Risk-Based Warning Decision Making of Cascade Breaching of the Tangjiashan Landslide Dam and Two Smaller Downstream Landslide Dams

Mega earthquakes or serious rainfall storms often cause crowded landslides in mountainous areas. A large part of these landslides are very likely blocking rivers and forming landslide dams in series along rivers. The risks of cascading failure of landslide dams are significantly different from that of a single dam. This paper presented the work on risk-based warning decision making on cascading breaching of the 2008 Tangjiashan landslide dam and two small downstream landslide dams in a series along Tongkou River. The optimal decision was made by achieving minimal expected total loss. Cascade breaching of a series of landslide dams is more likely to produce a multi-peak flood. When the coming of the breaching flood from the upstream dam perfectly overlaps with the dam breaching flood of the downstream dam, a higher overlapped peak flood would occur. When overlapped peak flood occurs, the flood risk would be larger and evacuation warning needs to be issued earlier to avoid serious life loss and flood damages. When multi-peak flood occurs, people may be misled by the warning of the previous peak flood and suddenly attacked by the peak flood thereafter, incurring catastrophic loss. Systematical decision making needs to be conducted to sufficiently concern the risk caused by each peak of the breaching flood. The dam failure probabilityPflinearly influences the expected life loss and flood damage but does not influence the evacuation cost. The expected total loss significantly decreases withPfwhen the warning time was insufficient. However, it would not change much withPfwhen warning time is sufficient.

Strategic Evacuation for Hurricanes and Regional Events with and without Autonomous Vehicles

A scheduling algorithm is developed for optimal planning of large-scale, complex evacuations to minimize total delay plus travel time across residents. The algorithm is applied to the eight-county Houston-Galveston region and land use setting under the 2017 Hurricane Harvey scenario with multiple destinations. Autonomous vehicle (AV) use under central guidance is also tested, to demonstrate the evacuation time benefits of AVs. Higher share of AVs delivers more efficient evacuation performance, thanks to greater reliability on evacuation order compliance, lower headways, and higher road capacity. Furthermore, 100% AV use delivers lower overall evacuation costs and network clearance times and less uncertainty in travel times (via lower standard deviation in). Based on evaluations of different evacuation schedules, a 50% compressed evacuation time span resulted in longer travel times and network congestion. A 50% longer evacuation time span reduced residents' total travel time and network congestion, but increased the evacuation cost. As expected, evacuation efficiency falls when evacuees do not comply with evaucation schedules. Large shares of AVs will not be possible in the near future, so methods to enhance evacuees' compliance behavior (e.g., enforced and prioritized evacuation orders) should be considered until a meaningful level of AV technical maturity and penetration rate is available. This paper demonstrates the benefits of scheduled departure times, AV use, and evacuation order compliance, which help balance conflicting objectives during emergencies.

Evolutionary game analysis of decision-making dynamics of local governments and residents during wildfires

The existing literature is short of exploring the interactions of stakeholders' decisions during wildfires from a dynamic perspective. Evolutionary game theory proposed based on Darwin's theory of evolution can capture the dynamic process and provide a method to analyze the complexity. This study utilizes a tripartite evolutionary game model to analyze the dynamic evolutionary process of evacuation decision-making for different decision makers in a wildfire event. The decision makers include (1) local governments who are responsible for warning, communicating with, and/or placing evacuation order, (2) residents who decide to evacuate, and (3) residents who chose to stay. Through this dynamic analysis, this study identifies evolutionary stable strategies (ESS) of different stakeholders and the whole system. A numerical example based on system dynamics (SD) is given to validate the stability of equilibrium points and analyze the influence of relative factors. The results show that (1) there are four ESS in the system among all the equilibrium points; (2) the local government would be quicker in reaching the ESS points in all scenarios; (3) local government's decision is influenced by reward and support from the higher level of government, regulation cost, and residents' behavior; whereas (4) the residents' behavior can be affected by the expected evacuation cost, loss of health and property, expected loss from looting, etc. The insights of this study could deepen understandings of the relationship between decision makers in emergency and provide guidance for effective wildfire disaster management strategies.

Consequences of a large-scale nuclear accident and guidelines for evacuation: a cost-effectiveness analysis

Purpose We aimed for a quantitative evaluation that justifies guidelines for evacuation which take into consideration both the human and economic costs. To the best of our knowledge, such an evaluation has not been performed yet. The present guidelines published by the International Atomic Energy Agency (IAEA) are probably based on averting radiation risk only; IAEA did not cite any quantitative estimation of the human cost of evacuation. Materials and methods Quantitative estimation of the human and monetary costs of evacuation and, alternatively, the human and monetary costs of radiation exposure (non-evacuation). Associating human life with monetary value is psychologically difficult and somewhat challenging ethically; however, there is no escape from such an association (cost-effectiveness analysis) when making decisions regarding public health and safety, since extraneous public expenditures lead to a statistical life shortening. Estimating worst-case health consequences of irradiation, we used the conservative linear no-threshold (LNT) model because this model is widely used in spite of its controversy. In our estimation of the human cost of evacuation, we considered three factors: (a) direct loss of life (after Fukushima, 1% of the evacuees died within 2 years due to causes directly related to their evacuation), (b) loss of quality of life, and (c) loss of wealth leading to loss of life. The connection of economic loss with loss of life was performed according to the median cost-effectiveness threshold of 50–100 thousand USD per quality-adjusted life year. Results Even according to mortality calculations based on LNT, the overall loss of life due to evacuation is higher than the loss of life due to irradiation if the population-averaged first-year radiation dose is 500 mSv or less. Conclusions Based on the performed analysis, we suggest avoiding evacuation if the projected first-year dose is below 500 mSv. This suggested action level is about five-fold higher than the action level presently recommended by the IAEA (100 mSv per year).

Medical evacuations among offshore oil and gas industries in the Gulf of Thailand.

Medical evacuation in the offshore oil and gas industry is costly and risky. Previous studies have found that the main cause of medical evacuation due to illness is increasing. In Thailand, there have been no studies on the causes and costs of medical evacuation in the offshore oil and gas industry. This study aims to study on the causes and costs of medical evacuation among offshore oil and gas industry in the Gulf of Thailand. A retrospective review of data of medical evacuation among the offshore oil and gas industry in the Gulf of Thailand from 2016 to 2019 for a period of 36 months. During the research period, a total of 416 cases were evacuated. The majority of the causes of Medevac (84.13%) were illness. We found that 60.1% of all Medevacs were unpreventable or difficult to prevent, and only 39.9% were preventable. The cost of Medevac ranged from 10,000 to 880,000 THB per case. The cost of Medevac occurring from preventable causes was 17,160,000 THB for this period of 36 months. Reducing the cost of Medevac can be done by: 1) vaccination to prevent vaccine-preventable diseases, 2) screening to prevent people at risk of getting complications from pre-existing diseases to work offshore, and 3) increasing treatment capability of offshore facilities. Offshore oil and gas industry may consider cost-benefit of these approaches compared to status quo.

From flooding to finance: NHS ambulance‐assisted evacuations of care home residents in Norfolk and Suffolk, UK

AbstractFocusing on the counties of Norfolk and Suffolk (UK), this investigation examines the effect of coastal and fluvial flooding on the use of ambulance service vehicles in the assisted evacuation of care home residents and quantifies the cost of this service to the NHS under flood conditions. This was completed using GIS Network Analyst functions to identify the impacts of flood probability (high: 1 in 30, medium: 1 in 30 to 1 in 100, and low: 1 in 100 to 1 in 1000) and target ambulance response‐times (7, 18, 120, and 180 min) on ambulance service area, road network accessibility, the number of vulnerable care homes and their accessibility, the appropriateness of pre‐identified evacuation routes, and the drive‐time based evacuation cost to the National Health Service (NHS). The results indicate that approximately 68 care homes and 2,320 residents in Norfolk and Suffolk are at risk of inundation, and care home accessibility, in addition to ambulance service area, decreases with shorter ambulance response‐times and lower flood probabilities. Additionally, the use of pre‐identified evacuation routes, by the ambulance service, promotes efficient navigation between ambulance stations, care homes, and rest centres, but can unfavourably cause network clustering if unmanaged. In association with these routes, an estimated cost of evacuation based on ambulance drive‐time was calculated at £34,000–£42,000 depending on flood probability. The importance of this research is highlighted by the current lack of identified flood evacuation and accessibility maps for emergency responder use, and the associated lack of evacuation cost estimations to be used by the government and NHS to budget for aid assistance during these natural disasters. Therefore, the application of this approach at a national level in the flood emergency planning process would be beneficial to promote strategic efficiency and financial preparedness of ambulance services for the purpose of ambulance‐assisted flood evacuations.