The economic and operational value of using drones to transport vaccines

Drone a technological leap in health care delivery in distant and remote inaccessible areas: A narrative review

In developing countries, last-mile delivery of medical products is a challenge, especially in hilly and rural areas where there is no road connectivity. As helicopters or other air services are not affordable all the time, drones can be used for the supply of medical products. They are cost-effective as compared to other air or road transport. However, the carrying capacity of drone is less, it is not able to carry heavier payloads. Also, operating drones requires trained operators, and it is a new venture in a developing country so possibilities of confusion and lack of clarity on operating procedures are there. Drones are becoming increasingly reliable for the health care delivery. This narrative review explores the use of drones in healthcare delivery globally.

Improving early infant diagnosis for HIV-exposed infants using unmanned aerial vehicles for blood sample transportation in Conakry, Guinea: a comparative cost-effectiveness analysis

BACKGROUND

Early infant diagnosis (EID) for HIV-exposed infants is essential due to high mortality during the first months of their lives. In Conakry (Guinea), timely EID is difficult as traffic congestion prevents the rapid transport of blood samples to the central laboratory. We investigated the cost-effectiveness of transporting EID blood samples by unmanned aerial vehicles (UAV), also known as drones.

METHODS AND FINDINGS

Using Monte Carlo simulations, we conducted a cost-effectiveness comparative analysis between EID blood samples transportation by on-demand UAV transportation versus the baseline scenario (ie, van with irregular collection schedules) and compared with a hypothetic on-demand motorcycle transportation system. Incremental cost-effectiveness ratio (ICER) per life-year gained was computed. Simulation models included parameters such as consultation timing (eg, time of arrival), motorcycle and UAV characteristics, weather and traffic conditions. Over the 5-year period programme, the UAV and motorcycle strategies were able to save a cumulative additional 834.8 life-years (585.1-1084.5) and 794.7 life-years (550.3-1039.0), respectively, compared with the baseline scenario. The ICER per life-year gained found were US$535 for the UAV strategy versus baseline scenario, US$504 for the motorcycle strategy versus baseline scenario and US$1137 per additional life-year gained for the UAV versus motorcycle strategy. Respectively, those ICERs represented 44.8%, 42.2% and 95.2% of the national gross domestic product (GDP) per capita in Guinea-that is, US$1194.

CONCLUSION

Compared with the baseline strategy, both transportation of EID blood samples by UAVs or motorcycles had a cost per additional life-year gained below half of the national GDP per capita and could be seen as cost-effective in Conakry. A UAV strategy can save more lives than a motorcycle one although the cost needed per additional life-year gained might need to consider alongside budget impact and feasibility considerations.

A robust optimization problem for drone-based equitable pandemic vaccine distribution with uncertain supply

Widespread vaccination is the only way to overcome the COVID-19 global crisis. However, given the vaccine scarcity during the early outbreak of the pandemic, ensuring efficient and equitable distribution of vaccines, particularly in rural areas, has become a significant challenge. To this end, this study develops a two-stage robust vaccine distribution model that addresses the supply uncertainty incurred by vaccine shortages. The model aims to optimize the social and economic benefits by jointly deciding vaccination facility location, transportation capacity, and reservation plan in the first stage, and rescheduling vaccinations in the second stage after the confirmation of uncertainty. To hedge vaccine storage and transportation difficulties in remote areas, we consider using drones to deliver vaccines in appropriate and small quantities to vaccination points. Two tailored column-and-constraint generation algorithms are proposed to exactly solve the robust model, in which the subproblems are solved via the vertex traversal and the dual methods, respectively. The superiority of the dual method is further verified. Finally, we use real-world data to demonstrate the necessity to account for uncertain supply and equitable distribution, and analyze the impacts of several key parameters. Some managerial insights are also produced for decision-makers.

An impact assessment of the use of aerial logistics to improve access to vaccines in the Western-North Region of Ghana

BACKGROUND

Prevention of infectious diseases among children is crucial to improve child health and survival. However, many countries in Sub-Saharan Africa struggle to achieve vaccination targets due to supply chain challenges, which lead to vaccine shortages, stockouts, and increased costs. We evaluated the effects of aerial logistics (centralized storage and delivery by drones) on vaccine stock, stockouts, vaccination coverage and vaccine preventable outcomes in the Western North Region of Ghana.

METHODS

The study combined retrospective quasi-experimental and cross-sectional designs to evaluate supply chain, programmatic, and clinical outcomes. Surveys to health providers were used to collect information from a random sample of 156 facilities, and secondary data on vaccination coverage and clinical outcomes was analyzed at the district level for the years 2017-2021.

RESULTS

Facilities served by aerial logistics reported significant reductions in the duration of vaccine stockouts (30 %, p-value < 0.05), as well as in the frequency of missed opportunities for vaccination (44 %, p-value < 0.05). Being served by aerial logistics was associated with increased satisfaction with access to vaccines. Significant differences in vaccination coverage were found for most vaccines, in a range between 13.1 and 37.5 percentage points in vaccination coverage for served districts. Infectious diarrhea cases in children between 5 and 9 years old were reduced by 41.6 % (p-value < 0.05).

CONCLUSION

End-to-end aerial logistics appears as an effective tool to improve the performance of the supply chain for vaccines. The strategy potentially increases the resilience of the health system and contributes to increased vaccination coverage and higher levels of satisfaction among providers in the Western North Region of Ghana.

Vaccine distribution with drones for less developed countries: A case study in Vanuatu

Drones (uncrewed aerial vehicles or UAVs) introduce new opportunities to improve vaccine distribution systems, particularly in regions with limited transportation infrastructure where maintaining the cold chain is challenging. This paper addresses the use of drones to deliver vaccines to hard-to-reach populations using a novel optimization model to strategically design a multimodal vaccine distribution network. The model is illustrated in a case study for distributing routine childhood vaccines in Vanuatu, a South Pacific island nation with limited transportation infrastructure. Our research incorporates multiple drone types, recharging of drones, a cold chain travel time limit, transshipment delays for switching transport modes, and practical limits on the vaccine paths and drone trips. The goal is to locate facilities (distribution centers, drone bases, and relay stations) and design vaccine paths to minimize transportation costs, including the fixed costs for facilities and transportation links and variable costs for transportation through the network. Results show large potential cost savings and improved service quality provided by incorporating drones in a multimodal vaccine distribution system. Results also show the impact of introducing drones on the usage of other more expensive or slower transport modes.

Elevating Healthcare: Rapid Literature Review on Drone Applications for Streamlining Disaster Management and Prehospital Care in Saudi Arabia

Saudi Arabia's health sector faces pressing challenges in disaster and prehospital care delivery, such as prolonged response times, limited access to remote areas, and strained medical resources. Integrating drone technology has emerged as an innovative approach to address these challenges and revolutionize healthcare delivery. Drones can significantly enhance response times, increase access to underserved areas, and reduce the burden on existing medical infrastructure. A detailed analysis of global case studies demonstrates the successful use of drones in healthcare delivery, emphasizing the importance of regulatory frameworks and public-private partnerships. These examples provide valuable insights into Saudi Arabia's health sector transformation. The potential benefits of integrating drone technology include improved patient outcomes, increased efficiency, and cost savings. To ensure the successful implementation of this transformative approach, it is crucial to establish clear regulatory guidelines, invest in research and development, and foster collaboration between the government, private sector, and healthcare stakeholders. The aim of this study is to explore the potential of drone technology in transforming healthcare delivery in Saudi Arabia, particularly within disaster response and prehospital care services.

The Use of Drones to Deliver Rift Valley Fever Vaccines in Rwanda: Perceptions and Recommendations

Given the recent emergence of Rift Valley Fever (RVF) in Rwanda and its profound impact on livelihoods and health, improving RVF prevention and control strategies is crucial. Vaccinating livestock is one of the most sustainable strategies to mitigate the impact of RVF on health and livelihoods. However, vaccine supply chain constraints severely limit the effectiveness of vaccination programs. In the human health sector, unmanned aerial vehicles, i.e., drones, are increasingly used to improve supply chains and last-mile vaccine delivery. We investigated perceptions of whether delivering RVF vaccines by drone in Rwanda might help to overcome logistical constraints in the vaccine supply chain. We conducted semi-structured interviews with stakeholders in the animal health sector and Zipline employees in Nyagatare District in the Eastern Province of Rwanda. We used content analysis to identify key themes. We found that stakeholders in the animal health sector and Zipline employees believe that drones could improve RVF vaccination in Nyagatare. The primary benefits study participants identified included decreased transportation time, improved cold chain maintenance, and cost savings.

Innovation in humanitarian logistics and supply chain management: a systematic review

The COVID-19 global health crisis forced border closings, strained resources and tightened funding, forcing humanitarian organisations to innovate. This paper aims to identify gaps in the literature on innovation in humanitarian supply chains, and to develop an appropriate framework for future research through a systematic literature review. We use a systematic literature review approach and synthesis the discussion of innovation in humanitarian supply chains after reviewing 43 papers. The synthesis identifies the different contexts for and outcomes of innovation in humanitarian supply chains. Our findings indicate that research on innovation in humanitarian supply chains is an underdeveloped topic. Gaps we identified in regards to the humanitarian context are: (1) a limited discussion of the contribution by the beneficiary to the supply chain; (2) a limited discussion of reconstruction innovations; (3) a lack of study on field application for complex innovations; (4) the lack of discussion of the role of individual knowledge in humanitarian supply chain innovation and finally (5) a lack of study of position innovations where humanitarian organisations use supply chains as a way to market effectively towards donors.

Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning

Vaccination offers health, economic, and social benefits. However, three major issues-vaccine quality, demand forecasting, and trust among stakeholders-persist in the vaccine supply chain (VSC), leading to inefficiencies. The COVID-19 pandemic has exacerbated weaknesses in the VSC, while presenting opportunities to apply digital technologies to manage it. For the first time, this study establishes an intelligent VSC management system that provides decision support for VSC management during the COVID-19 pandemic. The system combines blockchain, internet of things (IoT), and machine learning that effectively address the three issues in the VSC. The transparency of blockchain ensures trust among stakeholders. The real-time monitoring of vaccine status by the IoT ensures vaccine quality. Machine learning predicts vaccine demand and conducts sentiment analysis on vaccine reviews to help companies improve vaccine quality. The present study also reveals the implications for the management of supply chains, businesses, and government.

Drones delivering automated external defibrillators: A new strategy to improve the prognosis of out-of-hospital cardiac arrest

BACKGROUND

Out-of-hospital cardiac arrest (OHCA) is a serious threat to human life and health, characterized by high morbidity and mortality. However, given the limitations of the current emergency medical system (EMS), it is difficult to immediately treat patients who experience OHCA. It is well known that rapid defibrillation after cardiac arrest is essential for improving the survival rate of OHCA, yet automated external defibrillators (AED) are difficult to obtain in a timely manner.

OBJECTIVE

This review illustrates the feasibility and advantages of AED delivery by drones by surveying current studies on drones, explains that drones are a new strategy in OHCA, and finally proposes novel strategies to address existing problems with drone systems.

RESULTS

The continuous development of drone technology has been beneficial for patients who experience OHCA, as drones have demonstrated powerful capabilities to provide rapid delivery of AED. Drones have great advantages over traditional EMS, and the delivery of AED by drones for patients with OHCA is a new strategy. However, the application of this new strategy in real life still has many challenges.

CONCLUSION

Drones are promising and innovative tools. Many studies have demonstrated that AED delivery by drones is feasible and cost-effective; however, as a new strategy to improve the survival rate of OHCA patients, there remain problems to be solved. In the future, more in-depth investigations need to be conducted.

Unmanned Aerial Vehicle in the Logistics of Pandemic Vaccination: An Exact Analytical Approach for Any Number of Vaccination Centres

While the development and manufacture of pandemic vaccines is a daunting task, the greatest challenge lies in how to deliver these vaccines to billions of people around the world. This requires an efficient strategy of deliveries, at constrained costs and deadlines. This paper proposes an exact analytical approach and operational strategy to the logistics of any pandemic vaccination efforts, applicable both to sparsely populated areas or deficient infrastructure, and to very dense urban fabrics where mobility is highly constrained. Our strategy consists in dividing the territory concerned into zones and districts in a concentric way. We opt for the use of unmanned aerial vehicles to free ourselves from land constraints. This involves serving, from a logistics centre (central depot), any number n of vaccination centres, while optimizing costs and deadlines. We have determined all equivalent and optimal flight path plans for a fixed and optimal number of drones, which depend on domain D(d); d being the demand of vaccination centers. The analysis of the results led us to define what we will call the “degeneracy of domain D”. All our results are expressed as a function of the parameter n.

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

A bi-objective optimization model for the medical supplies' simultaneous pickup and delivery with drones

In the COVID-19 pandemic, it is essential to transport medical supplies to specific locations accurately, safely, and promptly on time. The application of drones for medical supplies delivery can break ground traffic restrictions, shorten delivery time, and achieve the goal of contactless delivery to reduce the likelihood of contacting COVID-19 patients. However, the existing optimization model for drone delivery is cannot meet the requirements of medical supplies delivery in public health emergencies. Therefore, this paper proposes a bi-objective mixed integer programming model for the multi-trip drone location routing problem, which allows simultaneous pick-up and delivery, and shorten the time to deliver medical supplies in the right place. Then, a modified NSGA-II (Non-dominated Sorting Genetic Algorithm II) which includes double-layer coding, is designed to solve the model. This paper also conducts multiple sets of data experiments to verify the performance of modified NSGA-II. Comparing with separate pickup and delivery modes, this study demonstrates that the proposed optimization model with simultaneous pickup and delivery mode achieves a shorter time, is safer, and saves more resources. Finally, the sensitivity analysis is conducted by changing some parameters, and providing some reference suggestions for medical supplies delivery management via drones.

U-Space and UTM Deployment as an Opportunity for More Complex UAV Operations Including UAV Medical Transport

Unmanned Aerial Vehicles (UAVs) or Unmanned Aircraft Systems (UASs) commonly called drones are relatively new entrants to the airspace. The regulatory agencies, numerous States and entities are involved in creation of the safe integration with manned aviation. The so-called U-space concept announced by the European Commission is one of the approaches to achieve that goal. There is also known concept of Unmanned Traffic Management (UTM) – a tool which would enable the services needed for safe conduct of UAV flights in generally accessible airspace. There are quite a few European projects which focuses on testing UTM capabilities in order to find a solution which could enable the market and ensure safe UAV operations. One of those systems is PansaUTM – which was developed in order to coordinate drone flights in different types of airspace in Poland. The first part of the paper will present an example of the implementation of this system as a foundation for new possible applications of drones and increasing number of operations. The conclusion of the first part of the article is that, in line rapid growth of UAS flights and different applications of drone services, the European drone ecosystem should evolve even further to deploy very complex drone operations in scalable manner. In order to accommodate unmanned air taxi operations, cargo flights, medical cargo flights, automatic surveillance flights, etc. Europe is preparing towards deployment of Advanced Air Mobility (AAM).

The second part of the text indicate the possibility of extensive use of drones in medical logistics as well as minimizing the epidemiological risk as a result of the use of this mean of transport. At the same time, it should be stressed out that the medical transport using drones can be used in urgent situations, where the main variable that has an impact on the success of life and health saving is the breaking of barriers to reaching difficult-to-reach places. In addition, the development of transport using drones can have a lasting impact on improving the quality of life of chronically ill patients who experience severe disease recurrence and thus on the need to implement emergency prevention or treatment measures.

The second part of the article focuses as well on the U-space concept as an opportunity for UAVs to be widely used in the field of day-to-day supplies as well as health-related supplies. In the context of the spread of SARS-CoV-2 virus, drones may be used to provide diagnostic screening tests, medicinal products and septic materials, transport of samples of biological material, as well as an information campaign on how to deal with an epidemic, quarantine or isolation at home. The use of UAV for medical supplies is economically and legally justified. The U-space environment from the operational and regulatory side is a multidisciplinary approach that requires the interaction of aviation, law, medicine, robotics, mechatronics and engineering experts. The legal framework for the development of U-space should be taken into account, as well as sector-specific regulations taking into account the principles of the use of drones in strictly defined areas, including in the process of medical supply, and liability for damage caused by UAV medical supply or AI-controlled intelligent machines.

Drone Applications for Emergency and Urgent Care: A Systematic Review

Introduction:

In recent years, the use of drones in health emergencies has increased. Among their main benefits are avoiding endangering rescuers, travelling long distances in a short time, or contacting victims in risky situations; but despite their multiple advantages, their use has not been fully demonstrated.

Study Objective:

This study aims to identify the available evidence on the use of drones in emergency health care compared to traditional health care.

Methods:

Systematic review of the literature was conducted. Search protocols were developed to locate studies that met the established selection criteria. Six experimental or quasi-experimental studies with high methodological quality published from the beginning of indexing until 2020 were included.

Results:

Drones covered a significantly larger area than other traditional tracking methods and were very useful for performing preliminary triage, determining needs, and knowing the scene prior to the arrival of rescuers. In addition, drones reduced the time required to locate the victim.

Conclusions:

Drones are an element to be taken into account when attending health emergencies as they significantly improve the distance travelled to locate accident victims, have the possibility of performing triage prior to the arrival of the health care units, and improve the time and quality of the care provided.

Telemedicine for Patient Management in Remote Areas and Underserved Populations

Access to care services in remote areas is challenging. The use of telemedicine technology in these areas facilitates access to health care. This study aimed to summarize the current research on telemedicine in remote areas such as mountains and forests. A systematic search was conducted in databases including Medline (through PubMed), Scopus, IEEE Xplore Digital Library, and ISI Web of Science to identify relevant studies published until May 12, 2021. Screening of retrieved articles for selection and inclusion in the study was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes extension for Scoping Reviews (PRISMA-ScR) checklist. A total of 807 articles were identified after removing duplicates, from which 20 studies meeting our inclusion criteria were selected. Challenges, opportunities, and equipment required to use telemedicine in remote areas were extracted from the selected studies. The results revealed that telemedicine implementation in remote areas had many challenges, including harsh weather conditions, Internet connectivity problems, difficult equipment transportation, and ethical issues. Telemedicine also has many benefits, such as cost and time savings for patients, improving patients' quality of life, and improving patient satisfaction. Telemedicine for inhabitants of forested and mountainous areas facilitates rapid access to health care and enhances patient satisfaction. Distinguishing advantages and barriers as well as reducing restrictions will have an essential role in accelerating the use of this technology.

Uncovering interrelationships between barriers to unmanned aerial vehicles in humanitarian logistics

Recent disasters, such as the ongoing COVID-19 pandemic, have sparked an interest in new applications for unmanned aerial vehicles (UAVs) in humanitarian aid. Nevertheless, there are still many divisive changes that need to be made in order to implement UAVs into a country’s humanitarian sector successfully. Hence, this paper aims to analyze the various barriers hindering the implementation of UAVs in humanitarian logistics for both developed and developing nations. To accomplish this, the study is presented in three steps. First, previous literature and opinions from experts are analyzed to illuminate particular factors that hinder UAV implementation. Next, we propose an interval-valued intuitionistic fuzzy set (IVIFS) based graph theory and matrix approach (GTMA) to calculate a drone implementation hindrance index (DIHI). The GTMA method used in this paper utilizes the PERMAN algorithm to calculate the permanent function. Finally, the DIHI values are plotted and analyzed to compare the readiness of drone implementation between developed and developing economies. A sensitivity analysis is then performed to provide validity to the results obtained. The study has revealed that both types of countries must first improve their inadequate government regulations regarding humanitarian UAVs. Developing countries must also focus on enhancing the technological awareness of their population. The results of this study can be used by policymakers and practitioners to smoothly implement UAVs in their country's humanitarian sector. The general index defined in this paper can also be calculated for specific countries using the steps mentioned in the manuscript.

Drone Usage for Medicine and Vaccine Delivery during the COVID-19 Pandemic: Attitude of Health Care Workers in Rural Medical Centres

Rural areas are often difficult to access reliably with medicine and vaccines. This study aimed to examine rural health care workers’ attitude towards drone delivery for medicine and vaccines and the factors that influenced it. Health care workers from four rural health care facilities were sampled. Participants self-reported their demographic information, attitude towards medicine and vaccine delivery using drones, perception of benefits and risks of using drones, and perceived leadership innovativeness through an online or a pen-and-paper questionnaire. A total of 272 health care workers (mean age = 36.19, SD = 8.10) from all of the sites participated in this study. More than half of the study participants agreed or strongly agreed that using a drone to deliver medicine and vaccines is a good idea (54.2%, 95% CI [47.5, 60.8]), a wise idea (54.6%, 95% CI [47.9, 61.2]), and is desirable (52.5%, 95% CI [45.7, 59.0]). Males (β = 0.223), workers from the Obstetrics and Gynaecology department (β = 0.135), a lower perceived delivery risk (β = −0.237), and higher leadership innovativeness (β = 0.336) predicted positive attitudes towards drone usage. Assistant medical officers (β = −0.172) had a negative attitude. There is a need to further understand the roles of occupation and leadership innovativeness in predicting health care workers’ attitude towards drone usage, as these differences could be embedded within their roles in the health care system.

The optimization of the "UAV-vehicle" joint delivery route considering mountainous cities

As a new transportation tool, unmanned aerial vehicle (UAV), has a broad application prospect in logistics distribution, especially for mountainous cities with complex terrain. Due to the limited delivery conditions of UAV, considering the advantages of traditional vehicle delivery, this paper proposes a joint delivery mode of UAV and vehicle, and designs three steps for the joint delivery problem of single UAV and single vehicle: first, mark all special nodes; Secondly, the route of UAV and vehicle is planned; Finally, the total delivery route is optimized to minimize the total delivery distance. Genetic algorithm and single distribution terminal optimization are used to solve the problem, and the joint delivery in this paper is compared with the traditional vehicle delivery and the independent delivery of UAV and vehicle. The results show that UAV and vehicle can cooperate with each other to complete the delivery of all customer demand nodes, and the joint delivery of UAV and vehicle can effectively reduce the total delivery distance. Finally, the sensitivity analysis of UAV's maximum load, maximum flight distance, relative speed between UAV and vehicle, and road impedance coefficient is carried out. By relaxing the restrictions of UAV, the UAV can deliver more customers at a single time, and it complete the delivery task with vehicles efficiently.

Design of a Service for Hospital Internal Transport of Urgent Pharmaceuticals via Drones

The internal transport of medical goods in a hospital heavily relies on human resources that carry the materials on foot. Such mode of transport may be affected by inefficiencies, e.g., due to bottlenecks, and other logistic challenges. Thus, it may benefit from the use of unmanned aircraft systems in several aspects. Such a scenario introduces specific criticalities for healthcare organizations in densely populated areas and below congested airspace, such as the Milan metropolitan area. The authors applied a co-creation methodology to design a highly automated drone service for the delivery of pharmaceuticals at San Raffaele Hospital, Milan, Italy. The needs of the main users were identified by means of semi-structured interviews and visualization material. Based on those outcomes, a drone service was designed and validated with the main users. It emerged that the main gain point of such a service would be increasing hospital logistics efficiency. The risks tied to the operations (e.g., tampering of the delivery container) were evaluated and appropriate mitigations were identified (e.g., use of tamper-evident seals or mechatronic locks). The information required by the digital system offering the needed logistics functions was analyzed for future development. Recent conceptual and regulatory advancements in the field of Urban Air Mobility (UAM) in Europe were elaborated to outline the digital ecosystem in which aviation and non-aviation actors would exchange information to ensure operations’ efficiency, safety and regulatory compliance.

A decision support model for selecting unmanned aerial vehicle for medical supplies: context of COVID-19 pandemic

Purpose

In recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery.

Design/methodology/approach

The authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation.

Findings

The findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible.

Research limitations/implications

The methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal.

Practical implications

This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

Social implications

The proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario.

Originality/value

This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

A Conceptual Approach to Time Savings and Cost Competitiveness Assessments for Drone Transport of Biologic Samples with Unmanned Aerial Systems (Drones)

Unmanned aerial vehicles (UAVs, drones) are expected to save transport time and improve service reliability for transport of biologic samples, but few studies have evaluated the potential time savings of such services. The total transport time defined as time from sample ready for transport until arrival at the laboratory was used to assess the absolute and relative time savings of drones compared with ground transport, using ground distances from 4–7 km (urban model) to 179–262 km (rural district routes) with one to eight daily scheduled trips. Costs of existing ground transport were allocated to drone flight times as a proxy for drone cost competitiveness. Time savings were less than 20–30% in the urban model but 65–74% in the rural routes using drone speeds of 100 km/h, but the time between trips (route frequencies) and drone speeds influenced the relative time savings substantially. Cost of time gains per number of samples was less favorable using drones in the rural models due to lower transport volumes. This research concludes that drone solutions provide marginal gains for short-distance transports, whereas time savings are more promising in long transport models with appropriate scheduling and sufficiently high drone speeds.

A Socio-Analytical Approach to the Integration of Drones into Health Care Systems

The integration of drones into health care as a supplement to existing logistics methods may generate a need for cooperation and involvement across multiple resource areas. It is currently not well understood whether such integrations would merely represent a technical implementation or if they would cause more significant changes to laboratory services. By choosing socio-technical theory as the theoretical lens, this paper intends to harvest knowledge from the literature on various organizational concepts and examine possible synergies between such theories to determine optimal strategies for introducing the use of drones in a health care context. Our particular interest is to examine whether the insights generated from the multi-level perspective (MLP) may have the potential to create dynamic spin-offs related to the organizational transitions associated with the implementation of drones in health services. We built our study on a scoping literature review of topics associated with the MLP and socio-technical studies from differing arenas, supplemented with studies harvested on a broader basis. The scoping review is based on 25 articles that were selected for analysis. As a way of organizing the literature, the niche, regime, and landscape levels of the MLP are translated to the corresponding health care-related terms, i.e., clinic, institution, and health care system. Furthermore, subcategories emerged inductively during the process of analysis. The MLP provides essential knowledge regarding the context for innovation and how the interaction between the different levels can accelerate the diffusion of innovations. Several authors have put both ethical topics and public acceptance into a socio-technological perspective. Although a socio-technical approach is not needed to operate drones, it may help in the long run to invest in a culture that is open to innovation and change.

Drone Applications Fighting COVID-19 Pandemic—Towards Good Practices

Of the recent epidemics, the impact of the COVID-19 pandemic has been particularly severe, not only putting our health at risk, but also negatively affecting our daily lives. As there are no developed algorithms for the use of drones in epidemiological situations, it is ideal to analyze the experience gained on drones so far and outline the effective methods for future good practice. The author relies on a method of analyzing widely available open information, such as images and videos available on the Internet, reports from drone users, announcements by drone manufacturers and the contents of newspaper articles. Furthermore, the author has relied on the results of the relevant literature, as well as previous experience as a drone user and fire commander. The study reveals numerous possibilities associated with drone usage in epidemic related situations, but previous applications are based on previous experience gained during a non-epidemic situation, without developed algorithms. Applications can be divided into different types of groups: drones can collect data for management and provide information to the public, perform general or special logistical tasks to support health care and disinfect to reduce the risk of spreading the epidemic.

A simulation study of drone delivery of Automated External Defibrillator (AED) in Out of Hospital Cardiac Arrest (OHCA) in the UK

Background

Drones are increasingly used in healthcare, and feasibility studies of deployment of Automated External Defibrillators (AED) in Out-of-hospital cardiac arrest (OHCA) have been conducted. Despite the potential contribution of drones to healthcare, regulatory barriers exist, including limits on flights beyond visual line-of-sight (BVLOS). The aim of this project was to deliver an AED BVLOS in Wales.

Methods

We developed of a Concept of Operations (CONOPS) to identify requirements, constraints, organisation and roles and responsibilities associated with deploying a drone to deliver an AED BVLOS. We equipped a Penguin B drone with satellite-enabled technology to enhance situational awareness and safety for the remote pilot. A BVLOS Operating Safety Case and three-week flight test programme was conducted with an AED attached directly to parachute for deployment to simulated OHCA.

Results

We completed six flights totalling 92km, 1:02.5 hours of flight time and four successful parachute payload drops. We conducted a successful end-to-end flight demonstration of an AED delivered via BVLOS by drone to a simulated OHCA and resuscitation by lay responder’s in a remote location; the final delivery of 4.5km was completed in 2:50 minutes.

Conclusion

We have delivered an AED by parachute, from fixed wing drone BVLOS in the UK in simulated OHCA. This project adds to the body of knowledge required for regulatory assurance on drone use BVLOS. Further research is needed before routine use of this technology.

A systems map of the economic considerations for vaccination: Application to hard-to-reach populations

BACKGROUND

Understanding the economics of vaccination is essential to developing immunization strategies that can be employed successfully with limited resources, especially when vaccinating populations that are hard-to-reach.

METHODS

Based on the input from interviews with 24 global experts on immunization economics, we developed a systems map of the mechanisms (i.e., necessary steps or components) involved in vaccination, and associated costs and benefits, focused at the service delivery level. We used this to identify the mechanisms that may be different for hard-to-reach populations.

RESULTS

The systems map shows different mechanisms that determine whether a person may or may not get vaccinated and the potential health and economic impacts of doing so. The map is divided into two parts: 1) the costs of vaccination, representing each of the mechanisms involved in getting vaccinated (n = 23 vaccination mechanisms), their associated direct vaccination costs (n = 18 vaccination costs), and opportunity costs (n = 5 opportunity costs), 2) the impact of vaccination, representing mechanisms after vaccine delivery (n = 13 impact mechanisms), their associated health effects (n = 10 health effects for beneficiary and others), and economic benefits (n = 13 immediate and secondary economic benefits and costs). Mechanisms that, when interrupted or delayed, can result in populations becoming hard-to-reach include getting vaccines and key stakeholders (e.g., beneficiaries/caregivers, vaccinators) to a vaccination site, as well as vaccine administration at the site.

CONCLUSION

Decision-makers can use this systems map to understand where steps in the vaccination process may be interrupted or weak and identify where gaps exist in the understanding of the economics of vaccination. With improved understanding of system-wide effects, this map can help decision-makers inform targeted interventions and policies to increase vaccination coverage in hard-to-reach populations.

A Range-Based Algorithm for Autonomous Navigation of an Aerial Drone to Approach and Follow a Herd of Cattle

This paper proposes an algorithm that will allow an autonomous aerial drone to approach and follow a steady or moving herd of cattle using only range measurements. The algorithm is also insensitive to the complexity of the herd's movement and the measurement noise. Once arrived at the herd of cattle, the aerial drone can follow it to a desired destination. The primary motivation for the development of this algorithm is to use simple, inexpensive and robust sensing hence range sensors. The algorithm does not depend on the accuracy of the range measurements, rather the rate of change of range measurements. The proposed method is based on sliding mode control which provides robustness. A mathematical analysis, simulations and experimental results with a real aerial drone are presented to demonstrate the effectiveness of the proposed method.

Micro array patch (MAP) for the delivery of thermostable vaccines in Australia: A cost/benefit analysis

BACKGROUND

It is anticipated that transforming the vaccine supply chain from syringe-and-needle to thermostable vaccines enabled by Micro Array Patch (MAP) will result in reduced supply chain costs as well as reduced wastes (environmental impact) and improved safety. This paper provides a thorough cost comparison of the conventional syringe-and-needle vaccine supply chain versus the MAP vaccine supply chain for influenza vaccine delivery in Australia.

OBJECTIVE

To determine the potential cost implications and general benefits of replacing syringe-and-needle flu vaccine with MAP-enabled thermostable flu vaccine in Australia.

METHODS

We first provide a snapshot of the existing flu vaccine supply chain in Australia including its limitations and opportunities for improvement. Data/information is collected through interviewing the key stakeholders across vaccine supply chain including vaccine manufacturers, logistics providers, clinics, hospitals, and pharmacies. A cost/benefit analysis of the anticipated supply chain of the MAP-enabled vaccine will reveal the opportunities and challenges of supply chain transformation for flu vaccine delivery in Australia.

FINDINGS

Our high-level practice-informed cost/benefit analysis identifies cold chain removal as an important source of cost saving, but administrative cost savings appear to be even more significant (e.g., time saving for nurses and those involved in cold chain management). Our analysis also identifies the key benefits and limitations of vaccine supply chain transformation in Australia.

CONCLUSION

We conclude that the benefits of moving from syringe-and-needle vaccines to thermostable MAP-delivered vaccines are beyond transportation and storage cost saving. Potential benefits through cost saving, waste reduction, and service level improvement are discussed along with various safety and wellbeing consequences as well as directions for future research in this area.

A fuzzy multi-criteria framework to identify barriers and enablers of the next-generation vaccine supply chain

Purpose

Due to the introduction of new vaccines in the child immunization program and inefficient vaccine supply chain (VSC), the universal immunization program (UIP), India is struggling to provide a full schedule of vaccination to the targeted children. In this paper, the authors investigate the critical factors for improving the performance of the existing VSC system by implementing the next-generation vaccine supply chain (NGVSC) in India.

Design/methodology/approach

The authors design a fuzzy multi-criteria framework using a fuzzy analytical hierarchical process (FAHP) and fuzzy multi-objective optimization on the basis of ratio analysis (FMOORA) to identify and analyze the critical barriers and enablers for the implementation of NGVSC. Further, the authors carry out a numerical simulation to validate the model.

Findings

The outcome of the analysis contends that demand forecasting is the topmost supply chain barrier and sustainable financing is the most important/critical enabler to facilitate the implementation of the NGVSC. In addition, the simulation reveals that the results of the study are reliable.

Social implications

The findings of the study can be useful for the child immunization policymakers of India and other developing countries to design appropriate strategies for improving existing VSC performance by implementing the NGVSC.

Originality/value

To the best of the authors’ knowledge, the study is the first empirical study to propose the improvement of VSC performance by designing the NGVSC.

Path Planning Method for UAVs Based on Constrained Polygonal Space and an Extremely Sparse Waypoint Graph

Finding an optimal/quasi-optimal path for Unmanned Aerial Vehicles (UAVs) utilizing full map information yields time performance degradation in large and complex three-dimensional (3D) urban environments populated by various obstacles. A major portion of the computing time is usually wasted on modeling and exploration of spaces that have a very low possibility of providing optimal/sub-optimal paths. However, computing time can be significantly reduced by searching for paths solely in the spaces that have the highest priority of providing an optimal/sub-optimal path. Many Path Planning (PP) techniques have been proposed, but a majority of the existing techniques equally evaluate many spaces of the maps, including unlikely ones, thereby creating time performance issues. Ignoring high-probability spaces and instead exploring too many spaces on maps while searching for a path yields extensive computing-time overhead. This paper presents a new PP method that finds optimal/quasi-optimal and safe (e.g., collision-free) working paths for UAVs in a 3D urban environment encompassing substantial obstacles. By using Constrained Polygonal Space (CPS) and an Extremely Sparse Waypoint Graph (ESWG) while searching for a path, the proposed PP method significantly lowers pathfinding time complexity without degrading the length of the path by much. We suggest an intelligent method exploiting obstacle geometry information to constrain the search space in a 3D polygon form from which a quasi-optimal flyable path can be found quickly. Furthermore, we perform task modeling with an ESWG using as few nodes and edges from the CPS as possible, and we find an abstract path that is subsequently improved. The results achieved from extensive experiments, and comparison with prior methods certify the efficacy of the proposed method and verify the above assertions.

Comparative UAV Noise-Impact Assessments through Survey and Noise Measurements

Possibilities to use unmanned aerial vehicles (UAVs) are rapidly growing. With the development of battery technologies, communication, navigation, surveillance, and autonomous systems in general, many UAVs are expected to operate at relatively low altitudes. Thus, the problem of UAV noise impact on human health and well-being will be more pronounced. In this paper, we conducted noise measurements of two UAVs of different performance (quadrotor and hexarotor) in flying up and down, hovering, and overflight procedures. Respondents of good hearing who were confirmed by audiogram measurement and had participated in the survey during UAV noise measurement gave their subjective assessments on the UAV noise perception. UAV noise measurements and subjective respondents’ assessments were analysed and related. UAV noise analysis showed that the parameters measured at the same measurement point for the hexarotor were higher than those for the quadrotor in flying up and down and flying-over procedures. Low frequency noise was present in the noise spectrum of both drones. Participants were able to distinguish between the noise of UAVs and had a generally more negative experience with the hexarotor. Regardless of the noise perception, more than 80% of the respondents believe there are more pros than cons for UAV introduction into everyday life.

Containing the COVID-19 pandemic with drones - Feasibility of a drone enabled back-up transport system

The COVID-19 pandemic has profoundly altered common social and economic patterns as governments all over the world have been forced to take drastic measures to counter the spread of the disease. Among them, quarantine, the closure of borders, and social distancing are the ones that have affected transportation systems most severely. With the clear need to avoid all unnecessary direct human contact, an increased interest in contactless transportation and delivery modes emerged. Drones are a promising alternative in this regard, especially for the delivery of essential goods, such as COVID-19 viral tests. In this study, we therefore investigate how drones can be used to distribute viral tests to potentially infected patients. The novel approach that we propose is to use existing drone infrastructure to perform this task, where drones owned and operated by different public and private entities are retrofitted for the distribution of essential goods in the case of emergency. In a wider sense, we hence suggest the establishment of a drone enabled back-up transport system. Potential performance gains are analyzed through a mathematical time and cost model that was developed in close cooperation with the state Red Cross Organization and a utility drone manufacturer. Process design as well as parameter estimation are based on empirical investigation including, but not limited to, accompanying a COVID-19 mobile testing team in the field. The practical feasibility was verified by retrofitting drones initially assigned to other purposes. Additionally, policy recommendations, such as the establishment of public-public and public-private partnerships, were identified.

A Drone Logistic Model for Transporting the Complete Analytic Volume of a Large-Scale University Laboratory

We present a model for drone transport of the complete annual analytic volume of 6.5 million analyses—(routine and emergency) between two inner-city university laboratories at Oslo University Hospital located 1.8 km apart and with a time restriction for the analyses of no more than 60 min. The total laboratory activity was analyzed per min for the complete year of 2018. The time from the clinical ordering of tests to the loading of the drone, drone transport time, and analysis time after the sample arrived at the analyzing laboratory were assessed using the lead time of emergency analyses of C-reactive protein, troponin, and the international normalized ratio. The activity had characteristic diurnal patterns, with the most intensive traffic between 8 and 12 a.m. on weekdays and there being considerably less traffic for the rest of the day, at night and on weekends. Drone schedules with departures 15–60 min apart were simulated. A maximum of 15 min between flights was required to meet the emergency demand for the analyses being completed within 60 min. The required drone weight capacity was below 3.5 kg at all times. In multiple simulations, the drone times were appropriate, whereas variations in the clinic- and laboratory-related time intervals caused violations of the allowed time 50% of the time. Drone transport with regular schedules may potentially improve the transport time compared with traditional ground transport and allow the merging of large laboratories, even when the demand for emergency analyses restricts the maximum transport time. Comprehensive economic evaluations and robust drone technology are needed before such solutions can be ready for implementation.

Business model options for passenger urban air mobility

While technological progress towards passenger urban air mobility (UAM) receives high attention, relevant business models for the deployment of these increasingly sophisticated passenger-carrying air vehicles for urban applications get less attention. However, especially in early market stages with high risks of investment and in respect to an often envisioned implementation of transport services in the proximity of urban settlements, it is important that the technology adds value to society. In this paper relevant perspectives to comprehend the current UAM business environment are presented. Possible operator models and customer segments are compiled and matched in three concrete business model approaches for passenger UAM. Scrutinising UAM Airport Shuttle Services shows that even concepts with sufficient demand might still not be adequate for a valid business case due to incomplete and a so far insufficient critical analysis of the overall operational environment. Second, a so far often unconsidered business model for a Company Shuttle Service is introduced, addressing the problem of scaling up UAM services with a dynamically expandable Business-to-Business (B2B) concept. Third, UAM will be discussed as part of public transport, introducing a business model that is inclusive and in strong line with public demands. Finally, these rather different implementation concepts unlock the space for an open-minded discussion on business models in the field of passenger UAM in general.

Quantifying the Effects of Vibration on Medicines in Transit Caused by Fixed-Wing and Multi-Copter Drones

The concept of transporting medical products by drone is gaining a lot of interest amongst the medical and logistics communities. Such innovation has generated several questions, a key one being the potential effects of flight on the stability of medical products. The aims of this study were to quantify the vibration present within drone flight, study its effect on the quality of the medical insulin through live flight trials, and compare the effects of vibration from drone flight with traditional road transport. Three trials took place in which insulin ampoules and mock blood stocks were transported to site and flown using industry standard packaging by a fixed-wing or a multi-copter drone. Triaxial vibration measurements were acquired, both in-flight and during road transit, from which overall levels and frequency spectra were derived. British Pharmacopeia quality tests were undertaken in which the UV spectra of the flown insulin samples were compared to controls of known turbidity. In-flight vibration levels in both the drone types exceeded road induced levels by up to a factor of three, and predominant vibration occurred at significantly higher frequencies. Flown samples gave clear insulin solutions that met the British Pharmacopoeia specification, and no aggregation of insulin was detected.

The Moderating Role of Pro-Innovative Leadership and Gender as an Enabler for Future Drone Transports in Healthcare Systems

Drones have been suggested as an emerging technology that has the potential to disrupt and improve healthcare. The attitude among healthcare workers towards the use of drones is important for its successful implementation. Our aim was to examine individual and institutional variables among employees that may be relevant for the successful implementation of drones. This study used a self-administered questionnaire to investigate the expectations and beliefs among 400 employees at three Norwegian healthcare organizations regarding the future role of drones in the provision of healthcare. The results showed that the use of drones in healthcare is positively perceived across professional groups, age, and location. Working in an innovative environment, having experienced previous technological change in one's working environment, and having leadership that supports new ideas were identified as drivers of individual beliefs regarding the use of drones as an innovative solution in future healthcare services. Men had significantly higher scores than women, and this was associated with reporting innovative leadership. This may indicate that a future implementation of drone usage should focus on local system environments and may depend on the presence of innovative leadership. Our results are harvested from a developed health care system and should be applicable for similar technologically advanced systems where the full potential of drone solutions may benefit from the integration of drones into the overall socio-technical system.

A Quickly Deployed and UAS-Based Logistics Network for Delivery of Critical Medical Goods during Healthcare System Stress Periods: A Real Use Case in Valencia (Spain)

On the one hand, Unmanned Aircraft Systems (UASs) have experienced great applicability surge in the recent years, arising as a promising technology with a wide field of use. On the other hand, healthcare, a critical system in modern society, is subject to a heavy and unexpected pressure in the case of situations such as the COVID-19 pandemic. This article aims to leverage the flexibility of UASs as complementary support for healthcare logistic systems when under high-stress conditions, via quick deployment of an air delivery network. We have defined a logistics network model and created three scenarios based on the model and current needs in Valencia (Spain). Flight tests have been performed in these scenarios, which include urban areas and controlled airspace. Operations complied with requirements derived from the application of Specific Operations Risk Assessment (SORA) methodology, recently adopted by the European Aviation Safety Agency (EASA). Flights were successful, being able to swiftly deliver medical goods without requiring any dedicated infrastructure. However, a moderate number of contingencies took place during the tests, mainly related to control link quality and Air Traffic Management (ATM) integration, forcing the use of dedicated procedures to cope with them. Although additional development is required to ensure the safety of large-scale automated operations, the use of UASs as part of logistic networks is a feasible means to support existing structures, especially in situations in dire need.

A change of perceived innovativeness for contactless food delivery services using drones after the outbreak of COVID-19

This study aims to identify how behavioral intentions are formed in the context of drone food delivery services using the moderating role before and after the outbreak of COVID-19. A conceptual model including eight hypotheses was developed and tested based on the data of two consumer samples, one collected before and the other after the outbreak of COVID-19. The data analysis results showed that perceived innovativeness positively affects attitude. In addition, the attitude, the subjective norm, and perceived behavioral control have a positive influence on behavioral intentions. Lastly, the outbreak of COVID-19 played a moderating role in the relationship between the attitude and behavioral intentions.

Control and prevention of infectious diseases from a One Health perspective

The ongoing COVID-19 pandemic has caught the attention of the global community and rekindled the debate about our ability to prevent and manage outbreaks, epidemics, and pandemics. Many alternatives are suggested to address these urgent issues. Some of them are quite interesting, but with little practical application in the short or medium term. To realistically control infectious diseases, human, animal, and environmental factors need to be considered together, based on the One Health perspective. In this article, we highlight the most effective initiatives for the control and prevention of infectious diseases: vaccination; environmental sanitation; vector control; social programs that encourage a reduction in the population growth; control of urbanization; safe sex stimulation; testing; treatment of sexually and vertically transmitted infections; promotion of personal hygiene practices; food safety and proper nutrition; reduction of the human contact with wildlife and livestock; reduction of social inequalities; infectious disease surveillance; and biodiversity preservation. Subsequently, this article highlights the impacts of human genetics on susceptibility to infections and disease progression, using the SARS-CoV-2 infection as a study model. Finally, actions focused on mitigation of outbreaks and epidemics and the importance of conservation of ecosystems and translational ecology as public health strategies are also discussed.

Development of unmanned aerial vehicle (UAV) networks delivering early defibrillation for out-of-hospital cardiac arrests (OHCA) in areas lacking timely access to emergency medical services (EMS) in Germany: a comparative economic study

OBJECTIVES

This study wants to assess the cost-effectiveness of unmanned aerial vehicles (UAV) equipped with automated external defibrillators (AED) in out-of-hospital cardiac arrests (OHCA). Especially in rural areas with longer response times of emergency medical services (EMS) early lay defibrillation could lead to a significant higher survival in OHCA.

PARTICIPANTS

3296 emergency medical stations in Germany.

SETTING

Rural areas in Germany.

PRIMARY AND SECONDARY OUTCOME MEASURES

Three UAV networks providing 80%, 90% or 100% coverage for rural areas lacking timely access to EMS (ie, time-to-defibrillation: >10 min) were developed using a location allocation analysis. For each UAV network, primary outcome was the cost-effectiveness using the incremental cost-effectiveness ratio (ICER) calculated by the ratio of financial costs to additional life years gained compared with current EMS.

RESULTS

Current EMS with 3926 emergency stations was able to gain 1224 life years on annual average in the study area. The UAV network providing 100% coverage consisted of 1933 UAV with average annual costs of €43.5 million and 1845 additional life years gained on annual average (ICER: €23 568). The UAV network providing 90% coverage consisted of 1074 UAV with average annual costs of €24.2 million and 1661 additional life years gained on annual average (ICER: €14 548). The UAV network providing 80% coverage consisted of 798 UAV with average annual costs of €18.0 million and 1477 additional life years gained on annual average (ICER: €12 158).

CONCLUSION

These results reveal the relevant life-saving potential of all modelled UAV networks. Furthermore, all analysed UAV networks could be deemed cost-effective. However, real-life applications are needed to validate the findings.

Pathologic Blood Samples Tolerate Exposure to Vibration and High Turbulence in Simulated Drone Flights, but Plasma Samples Should be Centrifuged After Flight

Objective. Most of the previous studies of drone transport of blood samples examined normal blood samples transported under tranquil air conditions. We studied the effects of 1- and 2-hour drone flights using random vibration and turbulence simulation (10-30 g-force) on blood samples from 16 healthy volunteers and 74 patients with varying diseased. Methods: Thirty-two of the most common analytes were tested. For biochemical analytes, we used plasma collected in lithium heparin tubes with and without separator gel. Gel samples were analyzed for the effect of separation by centrifugation before or after turbulence. Turbulence was simulated in an LDS V8900 high-force shaker using random vibration (range, 5–200 Hz), with samples randomly allocated to 1- or 2-hour flights with 25 or 50 episodes of turbulence from 10 to 30 G. Results: For all hematologic and most biochemical analytes, test results before and after turbulence exposure were similar (bias < 12%, intercepts < 10%). However, aspartate aminotransferase, folate, lactate dehydrogenase and lipid index increased significantly in samples separated by gel and centrifugation prior to vibration and turbulence test. These changes increased form 10 G to 30 G, but were not observed when the samples were separated after vibration and turbulence. Conclusions: Whole blood showed little vulnerability to turbulence, whereas plasma samples separated from blood cells by gel may be significantly influenced by turbulence when separated by spinning before the exposure. Centrifugation of plasma samples collected in tubes with separator gel should be avoided before drone flights that could be subject to turbulence.

Complexity analysis of cold chain transportation in a vaccine supply chain considering activity inspection and time-delay

The development of COVID-19 vaccine is highly concerned by all countries in the world. So far, many kinds of COVID-19 vaccines have entered phase III clinical trial. However, it is difficult to deliver COVID-19 vaccines efficiently and safely to the areas affected by the epidemic. This paper focuses on vaccine transportation in a supply chain model composed of one distributor and one retailer (clinic or hospital), in which the distributor procures COVID-19 vaccines from the manufacturer and then resells them to the retailer. Distributor detects the activity level of the vaccines, and retailer is responsible for transportation of the vaccines. Firstly, we establish a difference equations model with time-delay. Secondly, we investigate the impact of time-delay on the stability of vaccine supply chain. In addition, we explore the influence of decision adjustment speed of the distributor (or retailer) on the stability of vaccine supply chain. Finally, we verify the theoretical results by a two-dimensional bifurcation diagram, the largest Lyapunov exponent, entropy, and domain of attraction. The results show that when the decision delay-time or the adjustment speed of decision variables exceeds a certain threshold, it brings a negative impact on the stability of vaccine supply chain system. The stability domain of the system shrinks as customers' sensitivity to cold chain transportation decreases and by contrast expends as customers' sensitivity to vaccine prices decreases. When the vaccine supply chain is in a state of chaos, the effect of external control over the system is superior to that of internal control over the system.

Discriminant Analysis of Voice Commands in the Presence of an Unmanned Aerial Vehicle

The aim of this study was to perform discriminant analysis of voice commands in the presence of an unmanned aerial vehicle equipped with four rotating propellers, as well as to obtain background sound levels and speech intelligibility. The measurements were taken in laboratory conditions in the absence of the unmanned aerial vehicle and the presence of the unmanned aerial vehicle. Discriminant analysis of speech commands (left, right, up, down, forward, backward, start, and stop) was performed based on mel-frequency cepstral coefficients. Ten male speakers took part in this experiment. The unmanned aerial vehicle hovered at a height of 1.8 m during the recordings at a distance of 2 m from the speaker and 0.3 m above the measuring equipment. Discriminant analysis based on mel-frequency cepstral coefficients showed promising classification of speech commands equal to 76.2% for male speakers. Evaluated speech intelligibility during recordings and obtained sound levels in the presence of the unmanned aerial vehicle during recordings did not exclude verbal communication with the unmanned aerial vehicle for male speakers.

Inflight Polymerase Chain Reaction of samples with drones

A system devised to conduct Polymerase Chain Reaction (PCR) in-flight on drones that uses the spatial displacement of capillary tubes on thermal blocks kept at 94 °C, 58 °C and 72 °C corresponding to cycling temperatures for denaturation, annealing and extension is demonstrated here. The use of acetal as the thermal block material reduced heat loss and the input power (within 18.5 W) needed to maintain the required temperatures. Tests showed that concentrations of samples down to 1.16 × 10⁶ DNA copies/μL could be significantly and consistently detected above the background emission of the fluorescence signal intensity.

Short-Range Transportation Using Unmanned Aerial Vehicles (UAVs) during Disasters in Japan

Larger types of small unmanned aerial vehicles (UAVs) are beginning to be used in the United States and Europe for commercial transportation. Additionally, some blood product transport systems have been commercialized in Rwanda and other countries and used in pandemic operations for the coronavirus disease 2019 (COVID-19) in infected areas. Conversely, implementing goods transportation for commercial purposes in Japan has been difficult, especially in urban areas, due to national legislation. This study examined UAV-assisted transportation in Japan, a natural disaster hotspot, with a focus on the potential uses of UAVs in situations where traffic blockages make ground transportation impossible. UAVs were used to transport 17 kg of medical supplies belonging to a disaster medical assistance team (DMAT), along with 100 emergency meals. We also transported insulin under controlled-temperature conditions, as well as many other emergency supplies. Using UAVs to transport emergency supplies could be an effective approach when dealing with disasters. This paper summarizes the effectiveness of this approach for medical care and disaster response activities. We present a method for using drones to bridge the gap between medical and firefighting personnel, such as DMAT personnel, who are engaged in life-saving activities at the time of a disaster, and those who are unable to transport necessary goods by land using terrestrial vehicles due to traffic interruptions.

An Evaluation of the Drone Delivery of Adrenaline Auto-Injectors for Anaphylaxis: Pharmacists’ Perceptions, Acceptance, and Concerns

Anaphylaxis is a life-threatening condition where delays in medical treatment can be fatal. Such situations would benefit from the drone delivery of an adrenaline auto-injector such as EpiPen®. This study evaluates the potential risk, reward, and impact of drone transportation on the stability of adrenaline during episodes of anaphylaxis. Further, this study examines pharmacists’ perceptions on drone delivery—pharmacists approved the use of drones to deliver EpiPen® during emergencies but had concerns with drone safety and supply chain security. Laboratory simulated onboard drone conditions reflected typical missions. In these experiments, in vitro model and pharmaceutical equivalent formulations were subjected independently to 30 min vibrations at 5, 8.43, and 13.33 Hz, and temperature storage at 4, 25, 40, and 65 °C for 0, 0.5, 3, and 24 h. The chiral composition (an indicator of chemical purity that relates to molecular structure) and concentration of these adrenaline formulations were determined using ultraviolet (UV) and circular dichroism spectroscopy (CD). Adrenaline intrinsic stability was also explored by edge-of-failure experimentation to signpost the uppermost limits for safe transportation. During drone flight with EpiPen®, the temperature and vibration g-force were 10.7 °C and 1.8 g, respectively. No adverse impact on adrenaline was observed during drone flight and laboratory-simulated conditions shown by conformation to the British Pharmacopeia standards (p > 0.05 for CD and UV). This study showed that drone delivery of EpiPen® is feasible. There are more than 15,000 community pharmacies and ≈9000 GP surgeries spanning the UK, which are likely to provide achievable ranges and distances for the direct drone delivery of EpiPen®. The authors recommend that when designing future missions, in addition to medicine stability testing that models the stresses imposed by drone flight, one must conduct a perceptions survey on the relevant group of medical professionals, because their insights, acceptance, and concerns are extremely valuable for the design and evaluation of the mission.

Drones and digital adherence monitoring for community-based tuberculosis control in remote Madagascar: A cost-effectiveness analysis

Background

Continuing tuberculosis control with current approaches is unlikely to reach the World Health Organization’s objective to eliminate TB by 2035. Innovative interventions such as unmanned aerial vehicles (or drones) and digital adherence monitoring technologies have the potential to enhance patient-centric quality tuberculosis care and help challenged National Tuberculosis Programs leapfrog over the impediments of conventional Directly Observed Therapy (DOTS) implementation. A bundle of innovative interventions referred to for its delivery technology as the Drone Observed Therapy System (DrOTS) was implemented in remote Madagascar. Given the potentially increased cost these interventions represent for health systems, a cost-effectiveness analysis was indicated.

Methods

A decision analysis model was created to calculate the incremental cost-effectiveness of the DrOTS strategy compared to DOTS, the standard of care, in a study population of 200,000 inhabitants in rural Madagascar with tuberculosis disease prevalence of 250/100,000. A mixed top-down and bottom-up costing approach was used to identify costs associated with both models, and net costs were calculated accounting for resulting TB treatment costs. Net cost per disability-adjusted life years averted was calculated. Sensitivity analyses were performed for key input variables to identify main drivers of health and cost outcomes, and cost-effectiveness.

Findings

Net cost per TB patient identified within DOTS and DrOTS were, respectively, $282 and $1,172. The incremental cost per additional TB patient diagnosed in DrOTS was $2,631 and the incremental cost-effectiveness ratio of DrOTS compared to DOTS was $177 per DALY averted. Analyses suggest that integrating drones with interventions ensuring highly sensitive laboratory testing and high treatment adherence optimizes cost-effectiveness.

Conclusion

Innovative technology packages including drones, digital adherence monitoring technologies, and molecular diagnostics for TB case finding and retention within the cascade of care can be cost effective. Their integration with other interventions within health systems may further lower costs and support access to universal health coverage.