scholarly journals Resource Allocation for Different Types of Vaccines against COVID-19: Tradeoffs and Synergies between Efficacy and Reach

Author(s):  
Daniel Kim ◽  
Pelin Pekgün ◽  
İnci Yildirim ◽  
Pınar Keskinocak

AbstractObjectiveDuring the COVID-19 pandemic, multiple vaccine candidates were developed in record time. The primary decision for a vaccine-ordering decision-maker then becomes how to allocate limited resources between different types of vaccines. One may expect that available resources should be favored towards a vaccine with high efficacy if it can be distributed as widely as any other vaccine. However, if a high efficacy vaccine consumes more resources than a vaccine with lower efficacy due to distributional challenges, the decision is no longer trivial as a widespread vaccination is necessary to reach herd immunity.MethodsWe adapt a Susceptible-Infected-Recovered-Deceased (SIR-D) model with vaccination and simulate the level of infection attack rate (IAR) under different resource consumption ratios between two vaccine types with different resource allocation decisions.ResultsWe find that when there are limited resources, allocating resources entirely to a vaccine with high efficacy that becomes available earlier than a vaccine with lower efficacy that becomes available later does not always lead to a lower IAR, particularly if the former can immunize less than a range of 5.9% to 6.4% of the population (with the selected study parameters) before the latter becomes available. Sensitivity analyses show that this result stays robust under different efficacy levels for the higher efficacy vaccine.ConclusionsOur results show that the reach of a vaccine to be distributed widely under limited resources is a key factor to achieve low IAR levels, even though the vaccine may be of higher efficacy and may become available earlier than others. Manufacturing a novel vaccine lacking a fully developed suitable infrastructure for its effective distribution and storage may impact the potential benefits of the immunization program. Understanding the tradeoffs between efficacy and reach is critical for resource allocation decisions between different vaccine types to maximize the improvement in health outcomes.

2020 ◽  
Vol 34 (3) ◽  
pp. 87-112
Author(s):  
Bei Dong ◽  
Stefanie L. Tate ◽  
Le Emily Xu

SYNOPSIS Regulations implemented by the SEC in 2003 and 2004 simultaneously shortened the financial statement filing deadlines and increased the time required for both the preparation of financial statements and the related audit of accelerated filers (AFs). However, there were indirect, unintended negative consequences for companies not subject to the regulations, namely, non-accelerated filers (NAFs). The new regulations imposed strains on auditor resources requiring auditors to make resource allocation decisions that negatively affected NAFs. We find that NAFs with an auditor who had a high proportion of AF clients (high-AF) had longer audit delays after the regulations were implemented than NAFs of an auditor with a low proportion of AF clients (low-AF). Further, we document that NAFs with high-AF auditors were more likely to change auditors than NAFs with low-AF auditors. Finally, NAFs that switched to auditors with less AFs experienced shorter audit delays after the auditor change. JEL Classifications: M42; M48.


Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.


Author(s):  
J. Robert Sims

Risk analysis has been used extensively to inform decisions throughout government and industry for many years. Many methodologies have been developed to perform these analyses, resulting in differences in terminology and approach that make it difficult to compare the results of an analysis in one field to that in another. In particular, many approaches result only in a risk ranking within a narrow area or field of interest, so the results cannot be compared to rankings in other areas or fields. However, dealing with terrorist threats requires prioritizing the allocation of homeland defense resources across a broad spectrum of possible targets. Therefore, a common approach is needed to allow comparison of risks. This presentation summarizes an approach that will allow the results of risk analyses based on using current methodologies to be expressed in a common format with common terminology to facilitate resource allocation decisions.


2008 ◽  
Vol 24 (03) ◽  
pp. 244-258 ◽  
Author(s):  
Michael F. Drummond ◽  
J. Sanford Schwartz ◽  
Bengt Jönsson ◽  
Bryan R. Luce ◽  
Peter J. Neumann ◽  
...  

Health technology assessment (HTA) is a dynamic, rapidly evolving process, embracing different types of assessments that inform real-world decisions about the value (i.e., benefits, risks, and costs) of new and existing technologies. Historically, most HTA agencies have focused on producing high quality assessment reports that can be used by a range of decision makers. However, increasingly organizations are undertaking or commissioning HTAs to inform a particular resource allocation decision, such as listing a drug on a national or local formulary, defining the range of coverage under insurance plans, or issuing mandatory guidance on the use of health technologies in a particular healthcare system. A set of fifteen principles that can be used in assessing existing or establishing new HTA activities is proposed, providing examples from existing HTA programs. The principal focus is on those HTA activities that are linked to, or include, a particular resource allocation decision. In these HTAs, the consideration of both costs and benefits, in an economic evaluation, is critical. It is also important to consider the link between the HTA and the decision that will follow. The principles are organized into four sections: (i) “Structure” of HTA programs; (ii) “Methods” of HTA; (iii) “Processes for Conduct” of HTA; and (iv) “Use of HTAs in Decision Making.”


AGROFOR ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruth MAGRETA ◽  
Henderson NG’ONG’OLA ◽  
Julius MANGISONI ◽  
Kennedy MACHILA ◽  
Sika GBEGBELEGBE

Using household data from Lilongwe districts, along with crop phenology, agronomic management and climatic data from Chitedze Research Station, the Target-MOTAD and DSSAT-CSM models examined the resource allocation decisions of smallholder farmers in maize farming systems under climate risk in Malawi. Specific aims were to evaluate the ability of DSSAT to predict and collate DTM and non-DTM yields under climatic risk and to use a bio-economic procedure developed using DSSAT and Target-MOTAD to explore the impact of climatic risk on allocation of resources to DTM and non-DTM production. The paper argues that higher average yields observed from DTM varieties make it the most optimal maize production plan, in maximizing household incomes, food security, and minimizing deviations from the mean while meeting the set target incomes of farmers compared to non-DTM varieties. The multidisciplinary nature of this paper has contributed to the body of research by providing a powerful analytical procedure of modelling farmers’ resource allocation decisions in maize based farming systems in Malawi. This study necessitates the use of a combination of biophysical and economic procedures when evaluating promising lines prior to variety release in order to identify the high yielding variety that will continuously bring sustained profits to the farmers amidst climate change.


Sign in / Sign up

Export Citation Format

Share Document