Vaccine Allocation Research Articles

Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic

We present a formal mathematical modeling framework for a multi-agent sequential decision problem during an epidemic. The problem is formulated as a collaboration between a vaccination agent and learning agent to allocate stockpiles of vaccines and tests to a set of zones under various types of uncertainty. The model is able to capture passive information processes and maintain beliefs over the uncertain state of the world. We designed a parameterized direct lookahead approximation which is robust and scalable under different scenarios, resource scarcity, and beliefs about the environment. We design a test allocation policy designed to capture the value of information and demonstrate that it outperforms other learning policies when there is an extreme shortage of resources (information is scarce). We simulate the model with two scenarios including a resource allocation problem to each state in the United States and another for the nursing homes in Nevada. The US example demonstrates the scalability of the model and the nursing home example demonstrates the robustness under extreme resource shortages.

Is deliberative democracy possible during a pandemic? Reflections of a bioethicist.

In 1985, Governor Mario Cuomo established the New York State Task Force on Life and the Law to provide guidance on issues at the interface of medicine, ethics and the law. During its tenure, the Task Force has been the leading state-based commission in this space producing landmark reports on end-of-life care, physician-assisted suicide, genetic testing, newborn care, brain death, surrogate decision making, assisted reproduction, and ventilator allocation in pandemic flu. These documents have informed state policy, both regulatory and statutory, and had an outsized influence on policy deliberation nationwide. Despite this notable provenance, the Task Force was missing in action during the coronavirus disease 2019 (COVID-19) pandemic. Although individual members were sought for consultation, the Task Force as a whole did not meet during the entirety of the pandemic. This article will explore the consequences of this omission and argue that as a deliberative body, the Task Force should have been an essential component of statewide debate on questions of crisis standards of care, health equity, and vaccine allocation. The COVID-19 experience exposed weaknesses in New York's process of deliberative democracy in response to the pandemic. A state with a distinguished history in this interdisciplinary space was left behind with the views of important constituencies left unheard and communities unserved. Better apprehending how this abdication of responsibility occurred. (PsycInfo Database Record (c) 2021 APA, all rights reserved) Impact Statement This has public policy significiance as it can help prevent its recurrence in the future and lead to more trustworthy, inclusive and effective public health and health law governance. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

A Newcastle disease virus expressing a stabilized spike protein of SARS-CoV-2 induces protective immune responses

Rapid development of COVID-19 vaccines has helped mitigating SARS-CoV-2 spread, but more equitable allocation of vaccines is necessary to limit the global impact of the COVID-19 pandemic and the emergence of additional variants of concern. We have developed a COVID-19 vaccine candidate based on Newcastle disease virus (NDV) that can be manufactured at high yields in embryonated eggs. Here, we show that the NDV vector expressing an optimized spike antigen (NDV-HXP-S) is a versatile vaccine inducing protective antibody responses. NDV-HXP-S can be administered intramuscularly as inactivated vaccine or intranasally as live vaccine. We show that NDV-HXP-S GMP-produced in Vietnam, Thailand and Brazil is effective in the hamster model. Furthermore, we show that intramuscular vaccination with NDV-HXP-S reduces replication of tested variants of concerns in mice. The immunity conferred by NDV-HXP-S effectively counteracts SARS-CoV-2 infection in mice and hamsters.

Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept

Geospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and population-level risk assessment. For proof of concept, we adapted a spatially explicit COVID-19 model to investigate a hypothetical geospatial targeting of COVID-19 vaccine rollout in Ohio, United States, at the early phase of COVID-19 pandemic. The population-level deterministic compartmental model, incorporating spatial-geographic components at the county level, was formulated using a set of differential equations stratifying the population according to vaccination status and disease epidemiological characteristics. Three different hypothetical scenarios focusing on geographical subpopulation targeting (areas with high versus low infection intensity) were investigated. Our results suggest that a vaccine program that distributes vaccines equally across the entire state effectively averts infections and hospitalizations (2954 and 165 cases, respectively). However, in a context with equitable vaccine allocation, the number of COVID-19 cases in high infection intensity areas will remain high; the cumulative number of cases remained >30,000 cases. A vaccine program that initially targets high infection intensity areas has the most significant impact in reducing new COVID-19 cases and infection-related hospitalizations (3756 and 213 infections, respectively). Our approach demonstrates the importance of factoring geospatial attributes to the design and implementation of vaccination programs in a context with limited resources during the early stage of the vaccine rollout.

1.B. Round table: Biological, socioeconomic, legal and environmental health determinants in the COVID-19 pandemic

COVID-19 represents a concrete global health threat that has resulted in exacerbated inequalities, threatening progress towards SDG3, and particularly SDG 3.8, i.e. UHC - leave no one behind. Underlying differences in terms of health and social care system organisation, service provision models and pre-existing epidemiological context have resulted in heterogeneous scenarios for burden of disease (BoD) distribution, both in terms of COVID-19-specific outcomes, and because of collateral damage, not only across, but also within countries and regions. Individual proximal factors such as age, gender, ethnicity, socioeconomic position, underlying comorbidities and perception of risk have contributed to increased individual risk of acquiring the infection and of developing severe disease complications, including death. In addition, systemic issues, i.e., individual financial capacity, legal status, and acute versus chronic care needs have affected access both to care and commodity. From the global health perspective, we are also witnessing determinants threatening sustainable development, with tremendous differences in terms of capacity to combat the disease and deploy disease control measures, as well as ensure financial stability, economic growth and societal resilience. Ensuring equitable allocation of test, vaccines and medicines, and the development of comprehensive strategies necessitates a deeper understanding of those at most at risk, with due protection to those most vulnerable across the world. A comprehensive approach to tackle all these challenges, whilst ensuring due consideration is paid to ethical and legal issues, necessitates sound understanding of determinants, vulnerability with systematic measurement and interdisciplinary, cross-sectoral collaboration. This RT will bring the perspective of academia, researchers and practitioners in the field, and NGOs, offering insights on emerging research, practice and strategies. It aims to broker dialogue, to identify key steps to counter the damaging effect of inequities to social cohesion and system resilience, and to inform policy making and global public health actions.Key messages Biological, socioeconomic, legal and geographical determinants are at interplay, affecting the COVID-19 pandemic dynamics both in terms of immediate and delayed health outcomes.Assessing and weighing the links of various determinants and COVID-19 is essential to inform current and future policy decisions towards attaining UHC and to ensure an equitable, resilient society.

Who should get vaccinated? Individualized allocation of vaccines over SIR network

How to allocate vaccines over heterogeneous individuals is one of the important policy decisions in pandemic times. This paper develops a procedure to estimate an individualized vaccine allocation policy under limited supply, exploiting social network data containing individual demographic characteristics and health status. We model the spillover effects of vaccination based on a Heterogeneous-Interacted-SIR network model and estimate an individualized vaccine allocation policy by maximizing an estimated social welfare (public health) criterion incorporating these spillovers. While this optimization problem is generally an NP-hard integer optimization problem, we show that the SIR structure leads to a submodular objective function, and provide a computationally attractive greedy algorithm for approximating a solution that has a theoretical performance guarantee. Moreover, we characterize a finite sample welfare regret bound and examine how its uniform convergence rate depends on the complexity and riskiness of the social network. In the simulation, we illustrate the importance of considering spillovers by comparing our method with targeting without network information.

Optimal Allocation of Vaccine and Antiviral Drugs for Influenza Containment over Delayed Multiscale Epidemic Model considering Time-Dependent Transmission Rate.

In this study, two types of epidemiological models called “within host” and “between hosts” have been studied. The within-host model represents the innate immune response, and the between-hosts model signifies the SEIR (susceptible, exposed, infected, and recovered) epidemic model. The major contribution of this paper is to break the chain of infectious disease transmission by reducing the number of susceptible and infected people via transferring them to the recovered people group with vaccination and antiviral treatment, respectively. Both transfers are considered with time delay. In the first step, optimal control theory is applied to calculate the optimal final time to control the disease within a host's body with a cost function. To this end, the vaccination that represents the effort that converts healthy cells into resistant-to-infection cells in the susceptible individual's body is used as the first control input to vaccinate the susceptible individual against the disease. Moreover, the next control input (antiviral treatment) is applied to eradicate the concentrations of the virus and convert healthy cells into resistant-to-infection cells simultaneously in the infected person's body to treat the infected individual. The calculated optimal time in the first step is considered as the delay of vaccination and antiviral treatment in the SEIR dynamic model. Using Pontryagin's maximum principle in the second step, an optimal control strategy is also applied to an SEIR mathematical model with a nonlinear transmission rate and time delay, which is computed as optimal time in the first step. Numerical results are consistent with the analytical ones and corroborate our theoretical results.

Advocating for Greater Inclusion of Marginalized and Forgotten Populations in COVID19 Vaccine Rollouts.

Objectives: Many countries recently approved a number of SARS-CoV-2 vaccines. There is therefore growing optimism around the world about their future availability and effectiveness. However, supplies are likely to be limited and restricted to certain categories of individuals, at least initially. Thus, governments have suggested prioritization schemes to allocate such limited supplies. The majority of such schemes are said to be developed to safeguard the weakest sections of society; that is, healthcare personnel and the elderly. Methods: In this work, we analyse three case studies (incarcerated people; homeless people, asylum seekers and undocumented migrants). We propose a bioethical argument that frames the discussion by describing the salient facts about each of the three populations and then argue that these characteristics entail inclusion and prioritization in the queue for vaccination in their country of residence. Results: Through an analysis informed by ethical considerations revolving around the concepts of fairness and equality, we try to raise awareness of these important issues among decision makers. Conclusion: Our goal is to advocate for the development of more inclusive policies and frameworks in SARS-CoV-2 vaccine allocation and, in general, in all scenarios in which there is a shortage of optimal care and treatments.

Coronavirus Disease 2019 on the Heels of Ebola Virus Disease in West Africa.

This study utilized modeling and simulation to examine the effectiveness of current and potential future COVID-19 response interventions in the West African countries of Guinea, Liberia, and Sierra Leone. A comparison between simulations can highlight which interventions could have an effect on the pandemic in these countries. An extended compartmental model was used to run simulations incorporating multiple vaccination strategies and non-pharmaceutical interventions (NPIs). In addition to the customary categories of susceptible, exposed, infected, and recovered (SEIR) compartments, this COVID-19 model incorporated early and late disease states, isolation, treatment, and death. Lessons learned from the 2014–2016 Ebola virus disease outbreak—especially the optimization of each country’s resource allocation—were incorporated in the presented models. For each country, models were calibrated to an estimated number of infections based on actual reported cases and deaths. Simulations were run to test the potential future effects of vaccination and NPIs. Multiple levels of vaccination were considered, based on announced vaccine allocation plans and notional scenarios. Increased vaccination combined with NPI mitigation strategies resulted in thousands of fewer COVID-19 infections in each country. This study demonstrates the importance of increased vaccinations. The levels of vaccination in this study would require substantial increases in vaccination supplies obtained through national purchases or international aid. While this study does not aim to develop a model that predicts the future, it can provide useful information for decision-makers in low- and middle-income nations. Such information can be used to prioritize and optimize limited available resources for targeted interventions that will have the greatest impact on COVID-19 pandemic response.

Ethics of resource allocation in a public health emergency context.

Resource allocation under non-emergency conditions is often challenging. Within the context of a Public Health Emergency (PHE), allocation decisions become significantly more difficult as decisions are often necessary on very short timelines, where relevant information (either evidence or information "on the ground") is changing or incomplete, there is significant potential for harm, and resources are scarce, in unpredictable supply, and likely in high demand. An intentional value-based decision-making approach in such circumstances can clarify the values that ought to guide decisions, offering transparency and consistency, among other benefits. We use the example of vaccine allocation during the COVID-19 pandemic to explore value-based decision-making within a PHE context. We describe several core values that are relevant to PHE decision-making and outline their implications for approaches to vaccine allocation. While we focus on vaccine allocation, the values discussed are relevant to other system-level decisions in both emergency and non-emergency situations. Tips for leaders wishing to adopt a value-based approach to decision-making are offered.

Cosmopolitan morality trades off in-group for the world, separating benefits and protection

Global cooperation rests on popular endorsement of cosmopolitan values-putting all humanity equal to or ahead of conationals. Despite being comparative judgments that may trade off, even sacrifice, the in-group's interests for the rest of the world, moral cosmopolitanism finds support in large, nationally representative surveys from Spain, the United Kingdom, Germany, China, Japan, the United States, Colombia, and Guatemala. A series of studies probe this trading off of the in-group's interests against the world's interests. Respondents everywhere distinguish preventing harm to foreign citizens, which almost all support, from redistributing resources, which only about half support. These two dimensions of moral cosmopolitanism, equitable security (preventing harm) and equitable benefits (redistributing resources), predict attitudes toward contested international policies, actual charitable donations, and preferences for mask and vaccine allocations in the COVID-19 response. The dimensions do not reflect several demographic variables and only weakly reflect political ideology. Moral cosmopolitanism also differs from related psychological constructs such as group identity. Finally, to understand the underlying thought structures, natural language processing reveals cognitive associations underlying moral cosmopolitanism (e.g., world, both) versus the alternative, parochial moral mindset (e.g., USA, first). Making these global or local terms accessible introduces an effective intervention that at least temporarily leads more people to behave like moral cosmopolitans.

"Hot-spotting" to improve vaccine allocation by harnessing digital contact tracing technology: An application of percolation theory.

Vaccinating individuals with more exposure to others can be disproportionately effective, in theory, but identifying these individuals is difficult and has long prevented implementation of such strategies. Here, we propose how the technology underlying digital contact tracing could be harnessed to boost vaccine coverage among these individuals. In order to assess the impact of this “hot-spotting” proposal we model the spread of disease using percolation theory, a collection of analytical techniques from statistical physics. Furthermore, we introduce a novel measure which we call the efficiency, defined as the percentage decrease in the reproduction number per percentage of the population vaccinated. We find that optimal implementations of the proposal can achieve herd immunity with as little as half as many vaccine doses as a non-targeted strategy, and is attractive even for relatively low rates of app usage.

Brief communication International cooperation in a non-ideal world: the example of COVAX.

The world witnessed one of the fasted responses in history to a new disease in terms of drug and vaccine development. However, despite the fact that safe and effective vaccines for COVID-19 were developed at a remarkable pace, international cooperation seems to have failed regarding the global equitable allocation of vaccines. This article explores challenges to international cooperation in global health and specifically to the fair allocation of vaccines at a global scale. We will present major obstacles to cooperative efforts and an interesting answer such as the COVAX facility, a cooperative redistribution scheme that has recently been launched by WHO, CEPI and Gavi. Considering COVAX a laudable and necessary first step to improve international cooperation in health, we nevertheless argue that the facility needs to identify key areas of potential improvement.

Citizens from 13 countries share similar preferences for COVID-19 vaccine allocation priorities

How does the public want a COVID-19 vaccine to be allocated? We conducted a conjoint experiment asking 15,536 adults in 13 countries to evaluate 248,576 profiles of potential vaccine recipients who varied randomly on five attributes. Our sample includes diverse countries from all continents. The results suggest that in addition to giving priority to health workers and to those at high risk, the public favors giving priority to a broad range of key workers and to those with lower income. These preferences are similar across respondents of different education levels, incomes, and political ideologies, as well as across most surveyed countries. The public favored COVID-19 vaccines being allocated solely via government programs but were highly polarized in some developed countries on whether taking a vaccine should be mandatory. There is a consensus among the public on many aspects of COVID-19 vaccination, which needs to be taken into account when developing and communicating rollout strategies.

Safety and immunogenicity of the two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in children in Sierra Leone: a randomised, double-blind, controlled trial

SummaryBackgroundChildren account for a substantial proportion of cases and deaths from Ebola virus disease. We aimed to assess the safety and immunogenicity of a two-dose heterologous vaccine regimen, comprising the adenovirus type 26 vector-based vaccine encoding the Ebola virus glycoprotein (Ad26.ZEBOV) and the modified vaccinia Ankara vectorbased vaccine, encoding glycoproteins from the Ebola virus, Sudan virus, and Marburg virus, and the nucleoprotein from the Tai Forest virus (MVA-BN-Filo), in a paediatric population in Sierra Leone.MethodsThis randomised, double-blind, controlled trial was done at three clinics in Kambia district, Sierra Leone. Healthy children and adolescents aged 1–17 years were enrolled in three age cohorts (12–17 years, 4–11 years, and 1–3 years) and randomly assigned (3:1), via computer-generated block randomisation (block size of eight), to receive an intramuscular injection of either Ad26.ZEBOV (5 × 1010 viral particles; first dose) followed by MVA-BN-Filo (1 × 108 infectious units; second dose) on day 57 (Ebola vaccine group), or a single dose of meningococcal quadrivalent (serogroups A, C, W135, and Y) conjugate vaccine (MenACWY; first dose) followed by placebo (second dose) on day 57 (control group). Study team personnel (except for those with primary responsibility for study vaccine preparation), participants, and their parents or guardians were masked to study vaccine allocation. The primary outcome was safety, measured as the occurrence of solicited local and systemic adverse symptoms during 7 days after each vaccination, unsolicited systemic adverse events during 28 days after each vaccination, abnormal laboratory results during the study period, and serious adverse events or immediate reportable events throughout the study period. The secondary outcome was immunogenicity (humoral immune response), measured as the concentration of Ebola virus glycoprotein-specific binding antibodies at 21 days after the second dose. The primary outcome was assessed in all participants who had received at least one dose of study vaccine and had available reactogenicity data, and immunogenicity was assessed in all participants who had received both vaccinations within the protocol-defined time window, had at least one evaluable post-vaccination sample, and had no major protocol deviations that could have influenced the immune response. This study is registered at ClinicalTrials.gov, NCT02509494.FindingsFrom April 4, 2017, to July 5, 2018, 576 eligible children or adolescents (192 in each of the three age cohorts) were enrolled and randomly assigned. The most common solicited local adverse event during the 7 days after the first and second dose was injection-site pain in all age groups, with frequencies ranging from 0% (none of 48) of children aged 1–3 years after placebo injection to 21% (30 of 144) of children aged 4–11 years after Ad26.ZEBOV vaccination. The most frequently observed solicited systemic adverse event during the 7 days was headache in the 12–17 years and 4–11 years age cohorts after the first and second dose, and pyrexia in the 1–3 years age cohort after the first and second dose. The most frequent unsolicited adverse event after the first and second dose vaccinations was malaria in all age cohorts, irrespective of the vaccine types. Following vaccination with MenACWY, severe thrombocytopaenia was observed in one participant aged 3 years. No other clinically significant laboratory abnormalities were observed in other study participants, and no serious adverse events related to the Ebola vaccine regimen were reported. There were no treatment-related deaths. Ebola virus glycoprotein-specific binding antibody responses at 21 days after the second dose of the Ebola virus vaccine regimen were observed in 131 (98%) of 134 children aged 12–17 years (9929 ELISA units [EU]/mL [95% CI 8172–12 064]), in 119 (99%) of 120 aged 4–11 years (10 212 EU/mL [8419–12 388]), and in 118 (98%) of 121 aged 1–3 years (22 568 EU/mL [18 426–27 642]).InterpretationThe Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen was well tolerated with no safety concerns in children aged 1–17 years, and induced robust humoral immune responses, suggesting suitability of this regimen for Ebola virus disease prophylaxis in children.FundingInnovative Medicines Initiative 2 Joint Undertaking and Janssen Vaccines & Prevention BV.

Safety and long-term immunogenicity of the two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in adults in Sierra Leone: a combined open-label, non-randomised stage 1, and a randomised, double-blind, controlled stage 2 trial

Safety and long-term immunogenicity of the two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in adults in Sierra Leone: a combined open-label, non-randomised stage 1, and a randomised, double-blind, controlled stage 2 trial

Effective vaccine allocation strategies, balancing economy with infection control against COVID-19 in Japan

Due to COVID-19, many countries including Japan have implemented a suspension of economic activities for infection control. It has contributed to reduce the transmission of COVID-19 but caused severe economic losses. Today, several promising vaccines have been developed and are already being distributed in some countries. Therefore, we evaluated various vaccine and intensive countermeasure strategies with constraint of economic loss using SEIR model to obtain knowledge of how to balance economy with infection control in Japan. Our main results were that the vaccination strategy that prioritized younger generation was better in terms of deaths when a linear relationship between lockdown intensity and acceptable economic loss was assumed. On the other hand, when a non-linearity relationship was introduced, implying that the strong lockdown with small economic loss was possible, the old first strategies were best in the settings of small basic reproduction number. These results indicated a high potential of remote work when prioritizing vaccination for the old generation. When focusing on only the old first strategies as the Japanese government has decided to do, the strategy vaccinating the young next to the old was superior to the others when a non-linear relationship was assumed due to sufficient reduction of contact with small economic loss.

Incorporating health systems engineering into COVID-19 vaccine planning and administration

The COVID-19 pandemic has created unique logistical challenges for vaccine transportation, inventory management, allocation and distribution at multiple levels — the federal government, states and healthcare institutions. Unpredictable weekly vaccine allocation from state health departments, changing population priorities, stringent vaccine requirements for ultracold storage, transportation, reconstitution and 2-dose administration intervals have presented challenges never seen before in the history of mass vaccination programmes, including those at Mayo Clinic. To meet the challenges, an efficient system of allocation and administration for COVID-19 vaccines was developed through collaboration with process engineering. To understand the challenges, ten health systems engineers from the Department of Management Engineering & Consulting at Mayo Clinic facilitated the institution-wide COVID-19 vaccine project, collaborating closely with diverse multidisciplinary teams that included physicians, nurses, pharmacists, administrative services, information technology, human resources, scheduling operations and public affairs. The internal consultants designed tools and solutions based on systems and process engineering methodologies to solve a myriad of complex problems, including identifying priority populations, using resources efficiently and minimising vaccine waste. Tools designed included a vaccine resource playbook; dynamic staffing models based on vaccine allocation, storage, inventory and distribution processes using a hub-andspoke model; workflows and staffing models for face-to-face and drive-through vaccine administration sites; and end-of-day workflows to reduce vaccine waste. Through the collaboration, modelling and engineering, multiple sites across Mayo Clinic have implemented successful COVID-19 vaccination programmes that are efficient in resource utilisation and have minimal waste. In this paper, we share what we have learned to help other healthcare organisations prepare for future mass vaccination scenarios.

Evaluation of Vaccination Strategies to Compare Efficient and Equitable Vaccine Allocation by Race and Ethnicity Across Time

Identifying the most efficient COVID-19 vaccine allocation strategy may substantially reduce hospitalizations and save lives while ensuring an equitable vaccine distribution. To simulate the association of different vaccine allocation strategies with COVID-19-associated morbidity and mortality and their distribution across racial and ethnic groups. We developed and internally validated the risk of COVID-19 infection and risk of hospitalization models on randomly split training and validation data sets. These were used in a computer simulation study of vaccine prioritization among adult health plan members who were drawn from an integrated health care delivery system. The study was conducted from January 3, 2021, to June 1, 2021, in Oakland, California, and the data were analyzed during the same period. We simulated the association of different vaccine allocation strategies, including (1) random, (2) a US Centers for Disease Control and Prevention (CDC) proxy, (3) age based, and (4) combinations of models for the risk of adverse outcomes (CRS) and COVID-19 infection (PROVID), with COVID-19-related hospitalizations between May 1, 2020, and December 31, 2020, that were randomly permuted by month across 250 simulations and assessed vaccine allocation by race and ethnicity and the neighborhood deprivation index across time. The study included 3 202 679 adult patients (mean [SD] age, 48.2 [18.0] years; 1 677 637 women [52.4%]; 1 525 042 men [47.6%]; 611 154 Asian [19.1%], 206 363 Black [6.4%], 642 344 Hispanic [20.1%], and 1 390 638 White individuals [43.4%]), of whom 36 137 (1.1%) were positive for SARS-CoV-2. A risk-based strategy (CRS/PROVID) showed the largest avoidable hospitalization estimates (4954; 95% CI, 3452-5878) followed by age-based (4362; 95% CI, 2866-5175) and CDC proxy (4085; 95% CI, 2805-5109) strategies. Random vaccination showed substantially lower reductions in adverse outcomes. Risk-based strategies also showed the largest number of avoidable COVID-19 deaths (joint CRS/PROVID) and household transmissions. Risk-based (PROVID) and CDC proxy strategies were estimated to vaccinate the highest percentage of Hispanic and Black patients in 8 months (joint CRS/PROVID: 642 570 [100%] Hispanic, 185 530 [90%] Black; PROVID: 642 570 [100%] Hispanic, 198 480 [96%] Black; CDC proxy: 605 770 [95%] Hispanic and 151 772 [74%] Black) compared with an age-based approach (438 423 [68%] Hispanic, 154 714 [75%] Black). Overall, the PROVID and joint CRS/PROVID risk-based strategies were estimated to be followed by the most patients from areas with high neighborhood deprivation index being vaccinated early. In this simulation modeling study of adults from a large integrated health care delivery system, risk-based strategies were associated with the largest estimated reductions in COVID-19 hospitalizations, deaths, and household transmissions compared with the CDC proxy and age-based strategies, with a higher proportion of Hispanic and Black patients were estimated to be vaccinated early in the process compared with the CDC strategy.

A spatial and dynamic solution for allocation of COVID-19 vaccines when supply is limited

BackgroundSince most of the global population needs to be vaccinated to reduce COVID-19 transmission and mortality, a shortage of COVID-19 vaccine supply is inevitable. We propose a spatial and dynamic vaccine allocation solution to assist in the allocation of limited vaccines to people who need them most.MethodsWe developed a weighted kernel density estimation (WKDE) model to predict daily COVID-19 symptom onset risk in 291 Tertiary Planning Units in Hong Kong from 18 January 2020 to 22 December 2020. Data of 5,409 COVID-19 onset cases were used. We then obtained spatial distributions of accumulated onset risk under three epidemic scenarios, and computed the vaccine demands to form the vaccine allocation plan. We also compared the vaccine demand under different real-time effective reproductive number (Rt) levels.ResultsThe estimated vaccine usages in three epidemiologic scenarios are 30.86% - 45.78% of the Hong Kong population, which is within the total vaccine availability limit. In the sporadic cases or clusters of onset cases scenario, when 6.26% of the total population with travel history to high-risk areas can be vaccinated, the COVID-19 transmission between higher- and lower-risk areas can be reduced. Furthermore, if the current Rt is increased to double, the vaccine usages needed will be increased by more than 7%.ConclusionsThe proposed solution can be used to dynamically allocate limited vaccines in different epidemic scenarios, thereby enabling more effective protection. The increased vaccine usages associated with increased Rt indicates the necessity to maintain appropriate control measures even with vaccines available.