A Multi-Attribute decision support system for allocation of humanitarian cluster resources , based on decision makers’ perspective

The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker’s preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released

Operations research in disaster preparedness and response: The public health perspective

Operations research is the scientific study of operations for the purpose of better decision making and management. Disasters are defined as events whose consequences exceed the capability of civil protection and public health systems to provide necessary responses in a timely manner. Public health science is applied to the design of operations of public health services and therefore operations research principles and techniques can be applied in public health. Disaster response quantitative methods such as operations research addressing public health are important tools for planning effective responses to disasters. Models address a variety of decision makers (e.g. first responders, public health officials), geographic settings, strategies modelled (e.g. dispensing, supply chain network design, prevention or mitigation of disaster effects, treatment) and outcomes evaluated (costs, morbidity, mortality, logistical outcomes) and use a range of modelling methodologies. Regarding natural disasters the modelling approaches have been rather limited. Response logistics related to public health impact of disasters have been modelled more intensively since decisions about procurement, transport, stockpiling, and maintenance of needed supplies but also mass vaccination, prophylaxis, and treatment are essential in the emergency management. Major issues at all levels of disaster response decision making, including long-range strategic planning, tactical response planning, and real-time operational support are still unresolved and operations research can provide useful techniques for decision management.-JRC.G.2-Global security and crisis managemen

Reengineering an Allergy Group Practice in Response to COVID-19: Change Management, Quality Assessment and Financial Considerations

To date, few studies have provided a comprehensive set of requirements for outpatient medical practices to consider when preparing for complex external forces that impact clinic operations. The objective of this qualitative doctoral project is to establish a set of requirements for outpatient medical practices to consider when preparing for pandemic conditions. Using the backdrop of the COVID-19 pandemic, this single case study reviews how an allergy group practice responds to the variables presented during COVID-19 through change management, quality assessment and financial considerations lenses to assist other medical practices in developing pandemic preparedness programming. Findings from this case study are presented within an adapted Lewin change management framework and supported by six domains found to be requisite for an effective outpatient medical practice pandemic response: risk mitigation, operational excellence, talent considerations, clinical excellence, patient engagement and financial vitality. Annual preparedness training and response drills may assist with developing individualized criteria that supports seamless operations during uncontrollable external forces. Medical practice leaders should swiftly develop contingency plans now to better position their medical offices for a robust response during the next pandemic. Utilizing the six domains reviewed in this case study will support an individualized, effective plan to work through issues observed during a group medical practice’s COVID-19 response

Climate Justice in a State of Emergency: What New York City Can Do

NYC Climate Justice Agenda – Climate Justice in a State of Emergency: What New York City Can Do is a roadmap with policy recommendations for how a progressive city can lead the way on environmental and climate issues while challenging the reactionary policies of the Trump administration

Role of Regional Healthcare Coalitions in Managing and Coordinating Disaster Response

A white paper prepared for the January 23-24, 2013 workshop on Nationwide Response to an Improvised Nuclear Device Attack, hosted by the Institute of Medicine’s Forum on Medical and Public Health Preparedness for Catastrophic Events together with the National Association of County and City Health Officials

Optimization models for patient allocation during a pandemic influenza outbreak.

Pandemic influenza has been an important public health concern. During the 20th century, three major pandemics of influenza occurred in 1918, 1957, and 1968. The pandemic of 1918 caused 40 to 50 million deaths worldwide and more than 500,000 deaths in the United States. The 1957 pandemic, during a time with much less globalization than now, spread to the U.S. within 4 to 5 months of its origination in China, causing more than 70,000 deaths in the U.S., and the 1968 pandemic spread to the U.S. from Hong Kong within 2 to 3 months, causing 34,000 deaths. Pandemic influenza is considered to be a relatively high probability event, even inevitable by many experts. During a pandemic influenza outbreak, some key preparedness tasks cannot be accomplished by hospitals individually; regional resource allocation, patient redistribution, and use of alternative care sites all require collaboration among hospitals both in planning and in response. The research presented in this dissertation develops optimization models to be used by decision makers (e.g. hospital associations, emergency management agency, etc.) to determine how best to manage medical resources as well as suggest patient allocation among hospitals and alternative healthcare facilities. Both single-objective and multi-objective optimization models are developed to determine the patient allocation and resource allocation among healthcare facilities. The single-objective optimization models are developed to optimize the patient allocation in terms of minimizing the travel distance between patients and healthcare facilities while considering medical resource capacity constraints. During the pandemic, the surge demand most likely would exhaust all the medical resources, at which time the models can help predict the potential resource shortage so an appropriate contingency plan can be developed. If additional resource quantities become available, the models help to determine the best allocation of these resources among healthcare facilities. Various methods are proposed to conduct the sensitivity analysis to help decision makers determine the impact of different level of each type resource on the patient service. The multi-objective optimization model not only considers the objective of minimization of the total travel distance by patients to healthcare facilities, but also considers the minimization of maximum patient travel distance. A case study from Metro Louisville, Kentucky is presented to demonstrate how the models would aid in patient allocation and resource allocation during a pandemic influenza outbreak. A web-based application based on the optimization models developed in this dissertation is presented as an initial tool for decision makers

Comparison of Disaster Logistics Planning and Execution for 2005 Hurricane Season

After Hurricane Katrina, in the Gulf Coast region, millions of lives were impacted because of the lack of availability of transportation, shelter, food, water, drugs, etc. Hurricane Katrina raised many concerns in terms of the federal government\u27s capability, including their operational plant and necessary coordination strategies between state and federal governments to come up with a robust response in these catastrophic incidents. It has become apparent that developing a better operational plan is needed. To improve disaster relief, better logistics planning, which also requires better forecasting methods, is needed. Further more, to increase collaboration at all levels, it is also necessary to have more reliable communication technologies and a better information technology structure which will enable better coordination between different agencies. Utilizing technologies such as geographic information systems (GIS) and real-time tracking systems will ensure that the available disaster relief stocks will be distributed fairly to everybody

Review of Economic Instruments in Risk Reduction

Economic instruments (EI), such as subsidies, taxes and insurance-related options are at the heart of discussions regarding novel approaches for managing risk and adapting to climate change, including in the context of multi-stakeholder partnerships (MSP) between the private and public sectors. Although the attractiveness of reducing and managing disasters has long been demonstrated, there is underinvestment into disaster risk management (DRM). A number of factors, such as lack of comprehensive information and cognitive biases are important. In particular, financial constraints and moral hazard, i.e. adverse incentives provided by current arrangements for dealing with disasters rule high. In this line of thinking, instruments that provide a price signal for risk management and incentivize behavioural change hold high appeal to policymakers including the EU. Yet, little is known about such economic instruments, their mechanics, links to risk management and concrete application in the field of disaster risk management (and climate adaptation). Knowledge gaps exist particularly for conditions that create enabling environments for innovative market based EI. Among these are, e.g., the attractiveness for stakeholders in the context of MSP or institutional settings that are required to successfully and efficiently apply the EI. This report reviews key EI according to their potential for managing and incentivising risk management in the context of the ENHANCE project. The guiding questions for this review are: What economic instruments exist for managing disaster risk? How do they contribute to risk management? What innovative options re being discussed? How do case studies plan to discuss and assess economic instruments? The overall aim of this report is to develop an inventory of EI as they support risk management generally and their anticipated uptake in the ENHANCE cases studies. This report first discusses the methodology and the mechanics of EI. Next it presents the market-based and risk financing instruments; finally it concludes with a synthesis of our findings and next steps for the case studies, which are being carried out as part of the ENHANCE project