Quantifying optimal resource allocation strategies for controlling epidemics.

Frequent emergence of communicable diseases is a major concern worldwide. Lack of sufficient resources to mitigate the disease burden makes the situation even more challenging for lower-income countries. Hence, strategy development for disease eradication and optimal management of the social and economic burden has garnered a lot of attention in recent years. In this context, we quantify the optimal fraction of resources that can be allocated to two major intervention measures, namely reduction of disease transmission and improvement of healthcare infrastructure. Our results demonstrate that the effectiveness of each of the interventions has a significant impact on the optimal resource allocation in both long-term disease dynamics and outbreak scenarios. The optimal allocation strategy for long-term dynamics exhibits non-monotonic behaviour with respect to the effectiveness of interventions, which differs from the more intuitive strategy recommended in the case of outbreaks. Further, our results indicate that the relationship between investment in interventions and the corresponding increase in patient recovery rate or decrease in disease transmission rate plays a decisive role in determining optimal strategies. Intervention programmes with decreasing returns promote the necessity for resource sharing. Our study provides fundamental insights into determining the best response strategy when controlling epidemics in resource-constrained situations.

Tackling the COVID elective surgical backlog: Prioritising need, benefit or equality?

The National Health Service (NHS) in the UK is currently facing a significant waiting list backlog following the disruption of the COVID-19 pandemic, with millions of patients waiting for elective surgical procedures. Effective treatment prioritisation has been identified as a key element of addressing this backlog, with NHS England's delivery plan highlighting the importance of ensuring that those with ‘the clinically most urgent conditions are diagnosed and treated most rapidly'. Indeed, we describe how the current clinical guidance on prioritisation issued by The Federation of Surgical Specialty Associations serves this aim. However, whilst there are strong reasons to prioritise elective surgery in accordance with clinical need, we argue that it would be a mistake to assume that prioritisation in accordance with clinical need requires only a clinical or scientific judgement. The understanding of clinical need that we choose to employ in a prioritisation system will be grounded by some key ethical judgements. Moreover, we may also have to make trade-offs between addressing clinical need, safeguarding equality, and achieving other benefits. As the UK faces up to the backlog, it is important that surgical prioritisation guidelines enshrine a broad range of values that we believe ought to determine access to care in non-emergency circumstances. Our analysis suggests that the current approach to prioritisation is not a sufficiently nuanced way of balancing the different moral values that are operative in this context. © The Author(s) 2023.

An Analytical Approach for Dispatch Operations of Emergency Medical Services: A Case Study of COVID-19

: Emergency medical services (EMS) aims to deliver timely ambulatory care to incidents in communities. However, the operations of EMS may contend with suddenly increasing demands resulting from unexpected disasters such as disease outbreaks (e.g., COVID-19) or hurricanes. To this end, it usually requires better strategical decisions to dispatch, allocate, and reallocate EMS resources to meet the demand changes over time in terms of demographic and geographic distribution of incidents. In this study, we focus on the operation of the EMS resources (i.e., ambulance dispatch) in response to a demand disruption amid the COVID-19 pandemic. Specifically, we present a analytical framework to (1) analyze the underlying demographic and geographic patterns of emergency incidents and EMS resources;(2) develop a mathematical programming model to identify potential demand gaps of EMS coverage across different districts;and (3) provide a remedial reallocation solution to the EMS system with the existing ambulance capacity. The proposed method is validated with emergency response incident data in New York City for the first COVID-19 surge from March to April 2020. We found that it takes a long incident response time to scenes which reflects unexpected incident demands during COVID-19 surge. To cover such disruptive demands, ambulances need to be reallocated between service districts while meeting the response time standard. The proposed framework can be potentially applied to similar disruptive scenarios in the future and other operational systems disrupted by other disasters. Highlights: We propose an analytical framework using optimization modeling and simulation techniques for EMS resource allocation in response to a demand disruption amid the COVID-19 pandemic.We propose mathematical programming models to identify potential demand gaps of EMS coverage across different districts.We provide a remedial reallocation solution to the EMS system with the existing ambulance capacity. © 2023, The Author(s).

Working from home challenges: Resources, tools, and quality concerns

This chapter provides a glimpse into the conversation around the resources that university staff need to thrive in their work both on campus or through telework. The COVID-19 pandemic and shifting to working from home exposed disparities in resources for staff at the University of Utah many of which existed in the on-campus work environment as well. Institutions of higher education were no exception;most non-essential employees made the change from working on campus to a teleworking environment. Because most colleges and universities still operate from a brick-and-mortar setting and primarily offer in-person instruction, this change to serving students and carrying out job responsibilities from home was a huge and unexpected shift, and very little infrastructure was in place for addressing needs and providing essential tools and resources for employee thriving in a work-at-home environment. It is found that the move to working from home revealed a broad continuum where on one end staff had access to essential resources for thriving as new telecommuters, and on the other end staff struggled from one day to the next to maintain quality services for students and co-workers due to the lack of basic resources. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Improving Healthcare Deserts in Sub-Saharan Africa: A Health Improvement Pilot Study Leveraging a Global, Cloud-Based Telemedicine Platform

Objectives: The objective of this project was to improve healthcare deserts in Sub-Saharan Africa through sustainable knowledge transfer and capacity-building leveraging an advanced cloud-based telemedicine platform. Method(s): In 2022, WTI and its network of partners delivered 2 telehealth devices as part of the effort to create a sustainable platform to address a known health desert in a previously abandoned clinic in the village of Opoji, in the state of Edo, Nigeria. Providers were trained in two cohorts. Global Experts for this project were organized with Providence Health and their Global and Domestic Engagement (GDE) department and trained in telementoring and teleconsulting. Local Specialists were first trained on the platform and then telementored by Global Experts. To better understand the health value outcomes of these interventions, observational research was employed to measure the improvement of patient-to-provider ratios. These ratios were baselined for average patient loads. Result(s): As a result of the pilot, provider-to-patient ratios were improved. Prior to the WTI program, interventions were only available 5% of the time (9 hrs/wk vs 168 hrs/wk), with very basic expertise. After the Opoji Comprehensive Medical Center was reopened and the supporting physicians were scheduled, patients could be seen with a high level of global medical expertise 100% of the time (24 hours per day). Conclusion(s): Telemedicine technology can improve capacity-building in Sub-Saharan Africa with relatively minimal resource allocation in a replicable and scalable manner. Data collection for the pilot did have limitations. The opportunity to collect patient-reported outcomes, including patient satisfaction with telemedicine visits, exists but COVID and other barriers prevented researchers from fully implementing. By mentoring the local specialty hospital staff to deliver care by cloud-based devices, the program has developed an "Africans helping Africans" approach to achieve sustainable capacity building which can be built upon and further researched.Copyright © 2023

Digitalization of the supply chain: transformation factors

PurposeThere is an increasing interest in the supply chain's digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no consensus and is still limited to research assessing the supply chain's digitalization of organizations. This study aims to explore the supply chain digitalization drivers to understand the emerging phenomena. More specifically, the authors devised from the literature the most common factors in assessing the readiness in scaling supply chain digitalization.Design/methodology/approachThis study followed a five-phased systematic literature review (SLR) methodology in this research: designing, analyzing, conducting, writing and assessing the quality of the review. The SLR is beneficial for justifying future research regardless of the complex process that requires dealing with high-level databases, information filtering and relevancies of the content. Through analysis of 347 titles and s and 40 full papers, the authors showed and discussed the supply chain digitalization: transformation factors.FindingsThe results generated three main themes: technology, people and processes. The study also generated ten subthemes/primary drivers for assessing the readiness for supply chain digitalization in organizations: IT infrastructure, cybersecurity systems, digitalization reskilling and upskilling, digitalization culture, top management support, digitalization and innovation strategy, integrated supply chain, digital innovation management, big data management and data analytics and government regulations. The importance of each factor was discussed, and future research agenda was presented.Research limitations/implicationsWhile the key drivers of the supply chain digitalization were identified, there is still a need to study the statistical correlation to confirm the interrelationships among factors. This study is also limited by the articles available in the databases and content extraction.Practical implicationsThis study supports decision-makers in understanding the critical drivers in digitalizing the supply chain. Once these factors are studied and comprehended, managers and decision-makers could better anticipate and allocate the proper resources to embark on the digitalization journey and make informed decisions.Originality/valueThe digitalization of the supply chain is more critical nowadays due to the global disruptions caused by the Coronavirus (COVID-19) pandemic and the surge of organizations moving toward the digital economy. There is a gap between the digital transformation pilot studies and implementation. The themes and factors unearthed in this study will serve as a foundation and guidelines for further theoretical research and practical implications.

Matching medical staff to long term care facilities to respond to COVID-19 outbreak.

BACKGROUND: Staff shortage is a long-standing issue in long term care facilities (LTCFs) that worsened with the COVID-19 outbreak. Different states in the US have employed various tools to alleviate this issue in LTCFs. We describe the actions taken by the Commonwealth of Massachusetts to assist LTCFs in addressing the staff shortage issue and their outcomes. Therefore, the main question of this study is how to create a central mechanism to allocate severely limited medical staff to healthcare centers during emergencies. METHODS: For the Commonwealth of Massachusetts, we developed a mathematical programming model to match severely limited available staff with LTCF demand requests submitted through a designed portal. To find feasible matches and prioritize facility needs, we incorporated restrictions and preferences for both sides. For staff, we considered maximum mileage they are willing to travel, available by date, and short- or long-term work preferences. For LTCFs, we considered their demand quantities for different positions and the level of urgency for their demand. As a secondary goal of this study, by using the feedback entries data received from the LTCFs on their matches, we developed statistical models to determine the most salient features that induced the LTCFs to submit feedback. RESULTS: We used the developed portal to complete about 150 matching sessions in 14 months to match staff to LTCFs in Massachusetts. LTCFs provided feedback for 2,542 matches including 2,064 intentions to hire the matched staff during this time. Further analysis indicated that nursing homes and facilities that entered higher levels of demand to the portal were more likely to provide feedback on the matches and facilities that were prioritized in the matching process due to whole facility testing or low staffing levels were less likely to do so. On the staffing side, matches that involved more experienced staff and staff who can work afternoons, evenings, and overnight were more likely to generate feedback from the facility that they were matched to. CONCLUSION: Developing a central matching framework to match medical staff to LTCFs at the time of a public health emergency could be an efficient tool for responding to staffing shortages. Such central approaches that help allocate a severely limited resource efficiently during a public emergency can be developed and used for different resource types, as well as provide crucial demand and supply information in different regions and/or demographics.

Counterterrorism resource allocation during a pandemic: The effects of dynamic target valuations when facing a strategic terrorist.

The outbreak of pandemics such as COVID-19 can result in cascading effects for global systemic risk. To combat an ongoing pandemic, governmental resources are largely allocated toward supporting the health of the public and economy. This shift in attention can lead to security vulnerabilities which are exploited by terrorists. In view of this, counterterrorism during a pandemic is of critical interest to the safety and well-being of the global society. Most notably, the population flows among potential targets are likely to change in conjunction with the trend of the health crisis, which leads to fluctuations in target valuations. In this situation, a new challenge for the defender is to optimally allocate his/her resources among targets that have changing valuations, where his/her intention is to minimize the expected losses from potential terrorist attacks. In order to deal with this challenge, in this paper, we first develop a defender-attacker game in sequential form, where the target valuations can change as a result of the pandemic. Then we analyze the effects of a pandemic on counterterrorism resource allocation from the perspective of dynamic target valuations. Finally, we provide some examples to display the theoretical results, and present a case study to illustrate the usability of our proposed model during a pandemic.

The Effect of Fangcang Shelter Hospitals under Resource Constraints on the Spread of Epidemics.

Since the outbreak of the COVID-19 pandemic, Fangcang shelter hospitals have been built and operated in several cities, and have played a huge role in epidemic prevention and control. How to use medical resources effectively in order to maximize epidemic prevention and control is a big challenge that the government should address. In this paper, a two-stage infectious disease model was developed to analyze the role of Fangcang shelter hospitals in epidemic prevention and control, and examine the impact of medical resources allocation on epidemic prevention and control. Our model suggested that the Fangcang shelter hospital could effectively control the rapid spread of the epidemic, and for a very large city with a population of about 10 million and a relative shortage of medical resources, the model predicted that the final number of confirmed cases could be only 3.4% of the total population in the best case scenario. The paper further discusses the optimal solutions regarding medical resource allocation when medical resources are either limited or abundant. The results show that the optimal allocation ratio of resources between designated hospitals and Fangcang shelter hospitals varies with the amount of additional resources. When resources are relatively sufficient, the upper limit of the proportion of makeshift hospitals is about 91%, while the lower limit decreases with the increase in resources. Meanwhile, there is a negative correlation between the intensity of medical work and the proportion of distribution. Our work deepens our understanding of the role of Fangcang shelter hospitals in the pandemic and provides a reference for feasible strategies by which to contain the pandemic.

Inter-hospital Transfer Decision-making During the COVID-19 Pandemic: a Qualitative Study.

BACKGROUND: Inter-hospital patient transfers to hospitals with greater resource availability and expertise may improve clinical outcomes. However, there is little guidance regarding how patient transfer requests should be prioritized when hospital resources become scarce. OBJECTIVE: To understand the experiences of healthcare workers involved in the process of accepting inter-hospital patient transfers during a pandemic surge and determine factors impacting inter-hospital patient transfer decision-making. DESIGN: We conducted a qualitative study consisting of semi-structured interviews between October 2021 and February 2022. PARTICIPANTS: Eligible participants were physicians, nurses, and non-clinician administrators involved in the process of accepting inter-hospital patient transfers. Participants were recruited using maximum variation sampling. APPROACH: Semi-structured interviews were conducted with healthcare workers across Michigan. KEY RESULTS: Twenty-one participants from 15 hospitals were interviewed (45.5% of eligible hospitals). About half (52.4%) of participants were physicians, 38.1% were nurses, and 9.5% were non-clinician administrators. Three domains of themes impacting patient transfer decision-making emerged: decision-maker, patient, and environmental factors. Decision-makers described a lack of guidance for transfer decision-making. Patient factors included severity of illness, predicted chance of survival, need for specialized care, and patient preferences for medical care. Decision-making occurred within the context of environmental factors including scarce resources at accepting and requesting hospitals, organizational changes to transfer processes, and alternatives to patient transfer including use of virtual care. Participants described substantial moral distress related to transfer triaging. CONCLUSIONS: A lack of guidance in transfer processes may result in considerable variation in the patients who are accepted for inter-hospital transfer and in substantial moral distress among decision-makers involved in the transfer process. Our findings identify potential organizational changes to improve the inter-hospital transfer process and alleviate the moral distress experienced by decision-makers.

The impact of resource allocation during the COVID-19 pandemic on cardiac surgical practice and patient outcomes: a systematic review.

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has shaken the world and placed enormous strain on healthcare systems globally. In this systematic review, we investigate the effect of resource allocation on cardiac surgery programs and the impact on patients awaiting elective cardiac surgery. METHODS: PubMed and Embase were systematically searched for articles published from 1 January 2019 to 30 August 2022. This systematic review included studies investigating the impact of the COVID-19 pandemic on resource allocation and the subsequent influence on cardiac surgery outcomes. A total of 1676 abstracts and titles were reviewed and 20 studies were included in this review. RESULTS: During the COVID-19 pandemic, resources were allocated away from elective cardiac surgery to help support the pandemic response. This resulted in increased wait times for elective patients, increased rates of urgent or emergent surgical intervention and increased rates of mortality or complications for patients awaiting or undergoing cardiac surgery during the pandemic. CONCLUSIONS: While the finite resources available during the pandemic were often insufficient to meet the needs of all patients as well as the influx of new COVID-19 patients, resource allocation away from elective cardiac surgery resulted in prolonged wait times, more frequent urgent or emergent surgeries and negative impacts on patient outcomes. Understanding the impacts of delayed access to care with regards to urgency of care, increased morbidity and mortality and increased utilization of resources per indexed case needs to be considered to navigate through pandemics to minimize the lingering effects that continue to negatively impact patient outcomes.

Acute coronary syndrome: new realities in the era of the COVID-19 pandemic

Coronavirus infection (COVID-19) pandemic is a global health problem associated with high rates of morbidity and mortality. In this difficult time, the topic of acute coronary syndrome (ACS) is complicated by a number of clinically significant issues, such as COVID-induced myocardial damage, uncertainty of this emergency management, the need for a clear optimization of diagnostic and therapeutic measures, as well as ensuring maximum protection of medical personnel. In addition, there is a decrease in the number of hospitalizations for ACS worldwide, which is associated with the reluctance of patients to seek medical help and the redirection of medical resources in favor of combating the pandemic. Given that the primary pathophysiological mechanism of COVID-19 is a significant shift in blood coagulation rates, it is necessary to establish a relationship between this infection and an increased risk of acute coronary disease. The high risk of developing ACS associated with COVID-19 may be associated with atherosclerotic plaque rupture caused by endothelial cell damage, cytokine storms and the patient's inflammatory status. In this review will present aspects of the impact of the COVID-19 pandemic on the diagnosis, clinical course and treatment of ACS, as well as published data on the results of treatment of coronary syndrome in a pandemic.Copyright © 2022 by the Author(s).

Residential Segregation as a Barrier to Covid-19 Booster Coverage in Deep South

Background: Coronavirus disease 2019 (COVID-19) had been a stronger hit in Deep South compared with other developed regions in the United States, and vaccination remains a top priority for all eligible individuals. However, there are limited data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age group, which is of critical importance for future vaccine planning. Racial/ethnic disparities were found in the COVID-19 vaccination, but the vast majority of evidence was generated from studies at the individual level. There is an urgent need for evidence at the population level to reveal and evaluate the booster coverage in racial/ethnic minority communities, which could identify vulnerable communities and inform future healthcare policymaking and resource allocation. We evaluated county-level COVID-19 booster coverage by age group in the Deep South and examined its relationship with residential segregation. Method(s): We conducted an ecological study at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of five Deep South states from December 15, 2021 to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster coverage by age group (e.g., 12 to 17 years old, 18 to 64 years old, and at least 65 years old) by the end of the study period. We examined the longitudinal relationships between residential segregation, interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson mixed model. Result(s): As of October 19, 2022, among the 418 counties, the median percentage of booster coverage was 40% (interquartile range [IQR]: 37.8-43.0%). Compared with elders, youth and adults had lower percentages of booster uptake. There was geospatial heterogeneity in the COVID-19 booster coverage. Results of the Poisson mixed model found that as time increased, higher segregated counties had lower percentages of booster coverage. Such relationships were consistent across the age groups. Conclusion(s): The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccine planning should focus on youth and adults. Healthcare facilities and resources are needed in racial/ethnic minority communities. Residential segregation and COVID-19 booster coverage by age group in the 418 counties across the five Deep South states from December 15, 2021 to October 19, 2022.

Thoughts on diagnosis and treatment plan of patients infected with severe acute respiratory syndrome coronavirus 2 omicron variant in large shelter hospitals in Shanghai

The epidemic caused by the infection of severe acute respiratory syndrome coronavirus 2 omicron variant broke out in Shanghai in Mar. 2022. Omicron variant has characteristics such as strong concealment and rapid transmission, resulting in significant differences between the current round of epidemic and that in Wuhan. The number of infected patients (mainly asymptomatic infected patients) increased rapidly in a short term. Based on dynamic zero policy, shelter hospitals were set up in time in Shanghai to treat the patients. It is suggested that medical resources and patient characteristics should be taken into account in the independent cabin of a shelter hospital with more than 10 000 beds, and the clinical medical practice should be divided to 5 modes (universal education and management, community outpatient clinic, ward duty, emergency rescue, and temporary observation and transport) to optimize the allocation of medical resources, so as to further enhance the treatment capacity and efficiency of shelter hospitals.

An infectious disease model considering the impact of imported cases on internal spread of COVID-19

The coronavirus disease 2019(COVID-19) pandemic spreads across borders with the frequent global population movement. To explore the impact of the COVID-19 pandemic on China's domestic epidemic prevention and control, based on the classical infectious disease dynamics model this paper proposes an infectious disease model that considers oversea imported cases. The model can simulate three situations:national pandemic without imported cases, no domestic cases with only imported cases, and domestic cases with international travellers entering simultaneously. By calculating the peak case number and range of infection spread duration in these situations, as well as the amount of medical resources invested, the model has shown the different results of impact of entry type on the domestic pandemic and different pressures on medical resources. Finally, the paper suggests that testing measures should be taken according to the degree of pandemic risk and resource conditions, that strict prevention and control should be applied to the people not entering through customs, and closed-loop management to the people entering through customs, that entry quarantine measures and quarantine periods should be dynamically adjusted and international exchanges should be gradually resumed in the context of ensuring domestic and overseas epidemic prevention and control in advance, and that it is necessary to integrate medical resources, improve allocation efficiency, and relieve the pressure of resource occupation.

The use of zakat in the pandemic response: the case of Islamic Relief and BAZNAS in Indonesia

This article compares two Islamic organisations, a non-governmental and a national one, in their methods of collecting and distributing zakat, and analyses how they addressed the COVID-19 crisis with these funds in the period 2020–2021. The study examines Islamic Relief as a Muslim non-governmental organisation involved in humanitarian response, and the National Board of the Zakat Republic of Indonesia (BAZNAS) as a centralised national institution. Both of them are working to improve zakat management, due to the awareness of its untapped potential, but the measure of impacts and allocation of resources diverge in strategies and efforts. Considering their different structures, a comparison based on parallel analysis of collecting methods, distributing channels and programmes financed shows the limits, potentials and best practices of these two institutions committed to zakat management and its improvement.

Health Disparities in Children with Covid-19 Early in the Pandemic: Socioeconomic Disadvantages Contributing to Severe Disease

Purpose of Study: Ethnic disparities are associated with increased risk for severe disease in pediatric patients with COVID-19. Identifying the underlying social determinants of health are necessary to lead to improved health care utilization and mitigation strategies. Methods Used: This is an observational cohort study of children with COVID-19 in Colorado (the CCC study) from March 15 2020-October 31 2020. Pediatric patients between 2-20 years of age with positive SARS-CoV-2 PCR were included. Multivariable logistical regression models were fitted to identify demographic, socioeconomic, and comorbid health conditions as predictors of severe COVID-19 disease, as defined by hospital admission and need for respiratory support. Summary of Results: We identified 1572 pediatric patients with COVID-19 (45% Hispanic, 54% Medicaid or uninsured, 16% non-English language, and 20% obese). In univariable analyses, Hispanic ethnicity was associated with severe outcomes, including hospital admission (OR 2.4, CI: 1.57, 3.80, p<0.01) and respiratory support (OR 2.4, CI: 1.38, 4.14, p<0.01). Patients who identified as Hispanic or Latino had significantly increased rates of obesity (28% vs. 14%, p<0.01), preferred non-English language (31% vs. 3%, p<0.01), and had Medicaid or no insurance (79% vs. 33%, p<0.01) when compared to non-Hispanic or Latino children. After adjusting for covariables, ethnicity was no longer associated with hospital admission (OR 0.9, CI: 0.53, 1.63, p=0.79) or respiratory support (OR 0.6, CI: 0.29, 1.21, p=0.15). Obesity (OR 1.9, CI: 1.15, 3.08, p=0.01), non-English language (OR 2.4, CI: 1.35, 4.23, p<0.01), and Medicaid insurance (OR 2.0, CI: 1.10, 3.71, p=0.02) were identified as independent risk factors for severe disease. Conclusion(s): Severe COVID-19 disease observed in Hispanic or Latino patients early in the pandemic appears to be secondary to underlying comorbid conditions, such as obesity, and socioeconomic disadvantages that may have influenced access to care, such as language and insurance status. Pediatric healthcare providers and public health officials should use this knowledge to tailor resource allocation to better target this underserved patient population.

History repeats itself: an ethic for two pandemics

The emergence of the human immunodeficiency virus (HIV) in the 1980s brought ethical conflicts that meant a bioethics challenge. Among others, issues of confidentiality, stigmatization, justice, duty of care and investigation arose. Bioethical reflection had been focused on conflicts involving respect for individual autonomy, nevertheless HIV highlighted the needs of the community. Almost four decades later, the COVID-19 pandemic has brought the ethical conflicts typical of public health back to the bioethical scene. Quarantines, various restrictions on mobility, the obligation of masks, poorly protected health care, rationing of scarce resources, rushed research, the vaccines allocation, stigmatization and discrimination, the immune passport, or the moralization of infectious disease have highlighted the need for an ethical framework that helps to reflect and justify public health decisions. In this article we review and analyze the ethical conflicts that arose with HIV and how they have reappeared and been reinterpreted with the COVID-19 pandemic.

Three for me and none for you? An ethical argument for delaying COVID-19 boosters.

This paper argues in support of the WHO's proposal to forego COVID-19 booster shots until 10% of people in every country are fully vaccinated. The Ethical Argument section shows that we save the most lives and ensure the least amount of suffering by allocating doses first to unvaccinated people. It also argues that there is a duty to support decent lives and to promote health equity, which establish that refraining from boosters is a requirement of justice, not charity. The Replies to Objections section answers objections that appeal to pragmatism, nationalism, ownership, scientific advancement, self-interest, semantics and futility. The Conclusion section emphasizes that for now, wealthy nations should not boost vaccinated people's immunity and should instead send doses to poorer nations where they are most urgently needed.

The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19.

The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supply-constrained resource allocation strategies for controlling novel disease epidemics. To address the challenge of constrained resource optimization for managing diseases with complications like pre- and asymptomatic transmission, we develop an integro partial differential equation compartmental disease model which incorporates realistic latent, incubation, and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals. Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission. To analyze the influence of these realistic features on disease controllability, we find optimal strategies for reducing total infection sizes that allocate limited testing resources between 'clinical' testing, which targets symptomatic individuals, and 'non-clinical' testing, which targets non-symptomatic individuals. We apply our model not only to the original, delta, and omicron COVID-19 variants, but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions, which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness. We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies, while the relationship between incubation-latent mismatch, controllability, and optimal strategies is complicated. In particular, though greater degrees of presymptomatic transmission reduce disease controllability, they may increase or decrease the role of non-clinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length. Importantly, our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality.