A simulation-based analysis for effective distribution of COVID-19 vaccines: A case study in Norway

Optimizing the COVID-19 cold chain vaccine distribution network with medical waste management: A robust optimization approach

This paper investigates the distribution problem of the COVID-19 vaccine at the provincial level in Turkey and the management of medical waste, considering the cold chain requirements and the perishable nature of vaccines. In this context, a novel multi-period multi-objective mixed-integer linear programming model is initially presented over a 12-month planning horizon for solving the deterministic distribution problem. The model includes newly structured constraints due to the feature of COVID-19 vaccines, which must be administered in two doses at specified intervals. Then, the presented model is tested for the province of Izmir with deterministic data, and the results show that the demand can be satisfied and community immunity can be achieved in the specified planning horizon. Moreover, for the first time, a robust model is created using polyhedral uncertainty sets to manage uncertainties related to supply and demand quantities, storage capacity, and deterioration rate, and it has been analyzed under different uncertainty levels. Accordingly, as the level of uncertainty increases, the percentage of meeting the demand gradually decreases. It is observed that the biggest effect here is the uncertainty in supply, and in the worst case, approximately 30% of the demand cannot be met.

Inequality in COVID-19 vaccination in Africa

Background

The COVID-19 pandemic has spread rapidly to all countries with significant health, socioeconomic, and political consequences. Several safe and effective vaccines have been developed. However, it is not certain that all African countries have successfully vaccinated their populations.

Objective

To study the distribution and determinants of COVID-19 vaccination in Africa from March 2021 to June 2022.

Methods

Using reliable open-access data, we used the proportion of fully vaccinated people with a complete schedule as a reference variable. To analyze the level of inequality in COVID-19 vaccination, we computed common inequality indicators including two percentile ratios, the Generalized Entropy index, the Gini coefficient, and the Atkinson index. We also estimated the Lorenz curve. To identify drivers of COVID-19 vaccination, we estimated univariate and multivariate regression models as a function of COVID-19-related variables, demographic, epidemiologic, socioeconomic, and health system-related variables. To overcome a potential endogeneity bias, we checked our results using simultaneous equation models.

Results

53 African countries with available data were included in the study. The proportion of fully vaccinated people increased during the study period. However, this increase remained unequal across African countries. Based on the inequality indicators and the Lorenz curve, inequalities in COVID-19 vaccination across African countries were high, although they have decreased in recent months. Total COVID-19 cases and human development index were identified as significant determinant factors that were independently associated with COVID-19 vaccination.

Conclusions

Inequality in COVID-19 vaccination in Africa was high. Promoting adequate information to the general population and providing financial and logistical support to low-income countries can help expand COVID-19 vaccination in Africa.

Label free electrochemical DNA biosensor for COVID-19 diagnosis

The COVID-19 pandemic has significantly increased the development of the development of point-of-care (POC) diagnostic tools because they can serve as useful tools for detecting and controlling spread of the disease. Most current methods require sophisticated laboratory instruments and specialists to provide reliable, cost-effective, specific, and sensitive POC testing for COVID-19 diagnosis. Here, a smartphone-assisted Sensit Smart potentiostat (PalmSens) was integrated with a paper-based electrochemical sensor to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A disposable paper-based device was fabricated, and the working electrode directly modified with a pyrrolidinyl peptide nucleic acid (acpcPNA) as the biological recognition element to capture the target complementary DNA (cDNA). In the presence of the target cDNA, hybridization with acpcPNA probe blocks the redox conversion of a redox reporter, leading to a decrease in electrochemical response correlating to SARS-CoV-2 concentration. Under optimal conditions, a linear range from 0.1 to 200 nM and a detection limit of 1.0 pM were obtained. The PNA-based electrochemical paper-based analytical device (PNA-based ePAD) offers high specificity toward SARS-CoV-2 N gene because of the highly selective PNA-DNA binding. The developed sensor was used for amplification-free SARS-CoV-2 detection in 10 nasopharyngeal swab samples (7 SARS-CoV-2 positive and 3 SARS-CoV-2 negative), giving a 100% agreement result with RT-PCR.

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights. According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.

Exploring the Role of Industry 4.0 and Simulation as a Solution to the COVID-19 Outbreak: a Literature Review

The COVID-19 pandemic was an unexpected and disruptive event that significantly affected the performance of manufacturing systems and supply chains in various sectors. In this paper, a literature review is provided, which investigates the role that Industry 4.0 technologies and simulation tools have played in addressing the effects of the pandemic crisis. Specifically, a bibliometric analysis provides an overview of the most influential technologies through a study of the most used keywords. While a document analysis, conducted on critical papers that concern real case studies, shows that so far simulation provided support in four main areas: energy consumption, healthcare supply chain & contact tracing, food supply chain, and in general supply chain management. The main outcome of this research work is that Industry 4.0 technologies and simulation models were particularly important during the pandemic crisis and their properties deserve to be deeply exploited in the near future.

Improving the distribution of covid-19 vaccines using the blockchain technology: the Italian case study

Vaccination is one of the most effective ways to prevent and control the outbreak of infectious diseases. The vaccine supply chain differs from the traditional supply chains because of the perishability of the products, which need strict transport and warehousing conditions to guarantee the health and safety of people. In addition, in case of pandemics, the big amount of doses requested for the implementation of a mass vaccination campaign forces governments to design a proper logistic network and plan a rapid and efficient distribution of vaccines. This paper studies the organization of allocation and distribution of the covid-19 vaccines in Italy. The main criticalities in managing the vaccine supply chain have been identified and, because of its peculiarities, the blockchain has been considered a suitable technology to solve them. A simulation model has been developed to reproduce the current distribution of vaccines in Italy, and a future scenario with blockchain has been studied. The findings show that it is possible to improve the performance of the vaccine supply chain and make it more resilient by implementing the blockchain technology.

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.

Data analytics during pandemics: a transportation and location planning perspective

The recent COVID-19 pandemic once again showed the value of harnessing reliable and timely data in fighting the disease. Obtained from multiple sources via different collection streams, an immense amount of data is processed to understand and predict the future state of the disease. Apart from predicting the spatio-temporal dynamics, it is used to foresee the changes in human mobility patterns and travel behaviors and understand the mobility and spread speed relationship. During this period, data-driven analytic approaches and Operations Research tools are widely used by scholars to prescribe emerging transportation and location planning problems to guide policy-makers in making effective decisions. In this study, we provide a review of studies which tackle transportation and location problems during the COVID-19 pandemic with a focus on data analytics. We discuss the major data collecting streams utilized during the pandemic era, highlight the importance of rapid and reliable data sharing, and give an overview of the challenges and limitations on the use of data.

Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies

The COVID-19 pandemic has made a significant impact on various supply chains (SCs). All around the world, the COVID-19 pandemic affects different dimensions of SCs, including but not limited to finance, lead time, demand changes, and production performance. There is an urgent need to respond to this grand challenge. The catastrophic impact of the COVID-19 pandemic prompted scholars to develop innovative SC disruption management strategies and disseminate them via numerous scientific articles. However, there is still a lack of systematic literature survey studies that aim to identify promising SC disruption management strategies through the bibliometric, network, and thematic analyses. In order to address this drawback, this study presents a set of up-to-date bibliometric, network, and thematic analyses to identify the influential contributors, main research streams, and disruption management strategies related to the SC performance under the COVID-19 settings. The conducted analyses reveal that resilience and sustainability are the primary SC topics. Furthermore, the major research themes are found to be food, health-related SCs, and technology-aided tools (e.g., artificial intelligence (AI), internet of things (IoT), and blockchains). Various disruption management strategies focusing on resilience and sustainability themes are extracted from the most influential studies that were identified as a part of this work. In addition, we draw some managerial insights to ensure a resilient and sustainable supply of critical products in the event of a pandemic, such as personal protective equipment (PPE) and vaccines.

Is COVID-19 vaccine inequality undermining the recovery from the COVID-19 pandemic?

Background

The devastating health and economic impact of the COVID-19 pandemic led to a global response in the development of effective vaccines to fight the disease in an extraordinarily short time. Both the development and the production of these vaccines opened a path of hope, but the inequality in vaccine distribution raises great concerns about the possibility of effectively eradicating the virus.

Methods

It is particularly important to analyse the extent to which vaccines are equally distributed and investigate the possible effects of vaccine inequalities as well as its major drivers. For this purpose, this paper investigates the extent of equitable vaccine distribution using some well-known inequality measures and disentangles the main drivers of the share of vaccination. In addition, the paper analyses the relationship between the vaccination rate, the GDP growth, and the incidence of the coronavirus disease, with the aim of providing empirical evidence on existing relationships worldwide.

Results

Our findings show that the situation is more challenging in less developed countries, especially African countries, due to weak health systems and low rates of vaccination. Moreover, we find a positive relationship between the share of vaccinated individuals and GDP. Consequently, the poorest, least developed countries with a lower rate of vaccine uptake will experience lower GDP growth.

Conclusions

Vaccines and the vaccination process reveal the existing inequalities between countries and how they, in turn, impact the well-being of their citizens. People who live in less developed countries have a lower probability of being vaccinated, which translates into a greater probability of dying from COVID. Countries are seeing their economic future compromised by low vaccination levels, given the positive and significant relationship between the vaccination rate and GDP growth. In short, while some countries are trying to get back to some sort of normality, even with some pandemic protocols, the situation in less developed countries is more challenging due to weak health systems and low rates of vaccination. Consequently, the poorest, least developed countries with a lower rate of vaccine penetration will experience lower GDP growth, and the pandemic will have a greater effect on their economy due to low vaccination rates.

Estimating & comparing greenhouse gas emissions for existing intramuscular COVID-19 vaccines and a novel thermostable oral vaccine

BACKGROUND

Climate impacts are rarely considered in health impact and economic assessments of public health programs. This study estimates the greenhouse gas (GHG) emissions averted by a novel oral SARS-CoV-2 (COVID-19) vaccine compared with four existing intramuscular vaccines: AstraZeneca's COVISHIELD®, Pfizer/BioNTech's COMIRNATY®, Moderna's mRNA-1273, and Johnson & Johnson's Ad26.COV2.S COVID-19 vaccine.

METHODS

We estimated GHG emissions averted for five vaccine modalities across nine countries. GHG emissions averted were derived from differences in cold chain logistics, production of vaccine supplies, and medical waste disposal. Countryspecific data including population coverage and electricity production mix were included in GHG emissions calculations. Results are presented in averted GHG per vaccine course and country level based on modeled vaccination demand.

FINDINGS

Per course, an oral vaccine is estimated to avert between 0.007 and 0.024 kgCO₂e compared with Johnson & Johnson, 0.013 to 0.048 kgCO₂e compared with AstraZeneca, 0.23 to 0.108 kgCO₂e compared with Moderna, and 0.134 to 0.466 kgCO₂e compared with Pfizer/BioNTech. The total GHG averted varied across countries based upon predicted demand, mix of electrical production, and vaccination strategy with the largest emissions reductions projected for India and the United States.

INTERPRETATION

Our results demonstrate large potential GHG emissions reductions from the use of oral vs. intramuscular vaccines for mass COVID-19 vaccination programs. Up to 82.25 million kgCO₂e could be averted from utilization of an oral vaccine in the United States alone, which is equivalent to eliminating 17,700 automobiles from the road for one year.

FUNDING

Funding was provided by Vaxart, Inc. Vaxart, Inc. is currently developing an oral COVID-19 vaccine, the characteristics of which were utilized to define the thermostable oral vaccine discussed in this study. Apart from providing data on the characteristics of the oral vaccine under development, the funders had no influence over the study design, methods, statistical analyses, results, framing of results, decision to submit the manuscript for publication, or choice of journal.

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.

Environmental friendly micro cold storage for last-mile Covid-19 vaccine logistics

Globally, vaccination plays a vital role in controlling the Covid-19 pandemic. However, the cold supply chain is essential for vaccine storage and logistics services. In a country like India, the last-mile logistics of vaccines is a challenging task. The cold chain is indispensable for the Covid-19 vaccine drive to the rural areas. The demand for cold storage increases rapidly due to the rapid Covid-19 vaccine drive. The conventional cold storage facility has a more significant threat to the grid power quality and environmental impacts. The energy demand and greenhouse gas emission of traditional cold storage lead to global warming. The micro cold storage facility has to be developed rapidly to accelerate the vaccine drive to the last mile of the county with reliable and affordable energy sources. In addition, climate change mitigation is ensured by the renewable energy utilization in the Covid-19 vaccine drive. The proposed novel micro cold storage aims to be silent, clean, mobile, without moving parts, and reliable for the last-mile vaccine logistics as a vaccine carrier to the remote rural areas. This paper deals with the novel design, development, and experimental investigation of solar photovoltaic powered thermoelectric-based micro cold storage as a Covid-19 vaccine carrier for rural areas. The design consideration of Covid-19 vaccine storage has been reported. The experimental results ensure the World Health Organization recommended vaccine storage (i.e., vaccine carrier) temperature range of +2 to +8 °C. Therefore, green energy and refrigeration system provide environmental sustainability by mitigating 700kg of annual carbon emission.

Innovative Ecosystem Model of Vaccine Lifecycle Management

The COVID-19 pandemic has severely tested humanity, revealing the need to develop and improve the medical, economic, managerial, and IT components of vaccine management systems. The vaccine lifecycle includes vaccine research and development, production, distribution, and vaccination of the population. To manage this cycle effectively the proper organizational and IT support model of the interaction of vaccine lifecycle management stakeholders is needed—which are an innovation ecosystem and an appropriate virtual platform. A literature review has revealed the lack of methodological basis for the vaccine innovation ecosystem and virtual platform. This article is devoted to the development of a complex approach for the development of an innovation ecosystem based on vaccine lifecycle management and a virtual platform which provides the data exchange environment and IT support for the ecosystem stakeholders. The methodological foundation of the solution, developed in the article, is an enterprise architecture approach, CALS technologies, supply chain management and an open innovation philosophy. The results, presented in the article, are supposed to be a reference set of models for the creation of a vaccine innovation ecosystem, both during pandemics and periods of stable viral load.

A Data-Driven Digital Application to Enhance the Capacity Planning of the COVID-19 Vaccination Process

In this paper, a decision support system (DSS) is presented that focuses on the capacity planning of the COVID-19 vaccination process in the Netherlands. With the Dutch national vaccination priority list as the starting point, the DSS aims to minimize the per-class waiting-time with respect to (1) the locations of the medical hubs (i.e., the vaccination locations) and (2) the distribution of the available vaccines and healthcare professionals (over time). As the user is given the freedom to experiment with different starting positions and strategies, the DSS is ideally suited for providing support in the dynamic environment of the COVID-19 vaccination process. In addition to the DSS, a mathematical model to support the assignment of inhabitants to medical hubs is presented. This model has been satisfactorily implemented in practice in close collaboration with the Dutch Municipal and Regional Health Service (GGD GHOR Nederland).