Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity.
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ABSTRACT:
SUBMITTER: Han S
PROVIDER: S-EPMC8333090 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Published series on COVID-19 support the notion that patients with cancer are a particularly vulnerable population. There is a confluence of risk factors between cancer and COVID-19, and cancer care and treatments increase exposure to the virus and may dampen natural immune responses. The available evidence supports the conclusion that patients with cancer, in particular with hematologic malignancies, should be considered among the very high-risk groups for priority COVID-19 vaccination.
| S-EPMC8053003 | biostudies-literature
Project description:ImportanceAs COVID-19 vaccine distribution continues, policy makers are struggling to decide which groups should be prioritized for vaccination.ObjectiveTo assess US adults' preferences regarding COVID-19 vaccine prioritization.Design, setting, and participantsThis survey study involved 2 independent, online surveys of US adults aged 18 years and older, 1 conducted by Gallup from September 14 to 27, 2020, and the other conducted by the COVID Collaborative from September 19 to 25, 2020. Samples were weighted to reflect sociodemographic characteristics of the US population.ExposuresRespondents were asked to prioritize groups for COVID-19 vaccine and to rank their prioritization considerations.Main outcomes and measuresThe study assessed prioritization preferences and agreement with the National Academies of Science, Engineering, and Medicine's Preliminary Framework for Equitable Allocation of COVID-19 Vaccine.ResultsA total of 4735 individuals participated, 2730 (1474 men [54.1%]; mean [SD] age, 59.2 [14.5] years) in the Gallup survey and 2005 (944 men [47.1%]; 203 participants [21.5%] aged 55-59 years) in the COVID Collaborative survey. In both the Gallup COVID-19 Panel and COVID Collaborative surveys, respondents listed health care workers (Gallup, 93.6% [95% CI, 91.2%-95.3%]; COVID Collaborative, 80.0% [95% CI, 78.0%-81.9%]) and adults of any age with serious comorbid conditions (Gallup, 78.6% [95% CI, 75.2%-81.7%]; COVID Collaborative, 72.9% [95% CI, 70.7%-74.9%]) among their 4 highest priority groups. Respondents of all political affiliations agreed with prioritizing Black, Hispanic, Native American, and other communities that have been disproportionately affected by COVID-19 (Gallup, 74.2% [95% CI, 70.6%-77.5%]; COVID Collaborative, 84.9% [95% CI, 83.1%-86.5%]), and COVID Collaborative respondents were willing to be preceded in line by teachers and childcare workers (92.5%; 95% CI, 91.2%-93.7%) and grocery workers (85.9%; 95% CI, 84.2%-87.5%). Older respondents in both surveys were significantly less likely than younger respondents to prioritize healthy adults aged 65 years and older among their 4 highest priority groups (Gallup, 23.7% vs 39.1% [χ2 = 2160.8; P < .001]; COVID Collaborative, 23.3% vs 28.8% [χ2 = 5.0198; P = .03]). COVID Collaborative respondents believed the 4 most important considerations for prioritization were preventing COVID-19 spread (78.4% [95% CI, 76.3%-80.3%]), preventing the most deaths (72.1% [95% CI, 69.9%-74.2%]), preventing long-term complications (68.9% [66.6%-71.9%]), and protecting frontline workers (63.8% [95% CI, 61.5%-66.1%]).Conclusions and relevanceUS adults broadly agreed with the National Academies of Science, Engineering, and Medicine's prioritization framework. Respondents endorsed prioritizing racial/ethnic communities that are disproportionately affected by COVID-19, and older respondents were significantly less likely than younger respondents to endorse prioritizing healthy people older than 65 years. This provides reason for caution about COVID-19 vaccine distribution plans that prioritize healthy adults older than a cutoff age without including those younger than that age with preexisting conditions, that aim solely to prevent the most deaths, or that give no priority to frontline workers or disproportionately affected communities.
| S-EPMC8035644 | biostudies-literature
Project description:In the downlink cloud radio access network (C-RAN), fronthaul compression has been developed to combat the performance bottleneck caused by the capacity-limited fronthaul links. Nevertheless, the state-of-arts focusing on fronthaul compression for spectral efficiency improvement become questionable for energy efficiency (EE) maximization, especially for meeting its requirements of large-scale implementation. Therefore, this paper aims to develop a low-complexity algorithm with closed-form solution for the EE maximization problem in a downlink C-RAN with limited fronthaul capacity. To solve such a non-trivial problem, we first derive an optimal solution using branch-and-bound approach to provide a performance benchmark. Then, by transforming the original problem into a parametric subtractive form, we propose a low-complexity two-layer decentralized (TLD) algorithm. Specifically, a bisection search is involved in the outer layer, while in the inner layer we propose an alternating direction method of multipliers algorithm to find a closed-form solution in a parallel manner with convergence guaranteed. Simulations results demonstrate that the TLD algorithm can achieve near optimal solution, and its EE is much higher than the spectral efficiency maximization one. Furthermore, the optimal and TLD algorithms are also extended to counter the channel error. The results show that the robust algorithms can provide robust performance in the case of lacking perfect channel state information.
| S-EPMC5549950 | biostudies-other
Project description: Not available
| S-EPMC9006105 | biostudies-literature
Project description:BackgroundCOVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity.MethodsWe developed a deterministic compartmental model of COVID-19 transmission to explore how age-, risk-, and dose-specific vaccine prioritisation strategies can minimise severe outcomes of COVID-19 in Sierra Leone.ResultsPrioritising booster doses to older adults and adults with comorbidities could reduce the incidence of severe disease by 23% and deaths by 34% compared to the use of these doses as primary doses for all adults. Providing a booster dose to pregnant women who present to antenatal care could prevent 38% of neonatal deaths associated with COVID-19 infection during pregnancy. The vaccination of children is not justified unless there is sufficient supply to not affect doses delivered to adults.ConclusionsOur paper supports current WHO SAGE vaccine prioritisation guidelines (released January 2022). Individuals who are at the highest risk of developing severe outcomes should be prioritised, and opportunistic vaccination strategies considered in settings with limited rollout capacity.
| S-EPMC10712073 | biostudies-literature
Project description:Vaccination against COVID-19 is making progress globally, but vaccine doses remain a rare commodity in many parts of the world. New virus variants require vaccines to be updated, hampering the availability of effective vaccines. Policymakers have defined criteria to regulate who gets priority access to the vaccination, such as age, health complications, or those who hold system-relevant jobs. But how does the public think about vaccine allocation? To explore those preferences, we surveyed respondents in Brazil, Germany, Italy, Poland, and the United States from September to December of 2020 using ranking and forced-choice tasks. We find that public preferences are consistent with expert guidelines prioritizing health-care workers and people with medical preconditions. However, the public also considers those signing up early for vaccination and citizens of the country to be more deserving than later-comers and non-citizens. These results hold across measures, countries, and socio-demographic subgroups.
| S-EPMC9735138 | biostudies-literature
Project description:BackgroundDue to competing health priorities, low- and middle-income countries (LMIC) may need to prioritize between different influenza vaccine risk groups. Risk group prioritization may differ in LMIC based upon programmatic feasibility, country-specific prevalence of risk conditions and influenza-associated morbidity and mortality.MethodsIn South Africa, we collected local disease burden data (both published and unpublished) and published vaccine efficacy data in risk groups and healthy adults. We used these data to aid policy makers with risk group prioritization for influenza vaccination. We used the following formula to assess potential vaccine averted disease in each risk group: rate of influenza-associated hospitalization (or death) per 100,000 population * influenza vaccine efficacy (VE). We further estimated the cost per hospital day averted and the cost per year of life saved by influenza vaccination.ResultsPregnant women, HIV-infected adults, and adults and children with tuberculosis disease had among the highest estimates of hospitalizations averted per 100,000 vaccinated and adults aged 65 years and older had the highest estimated deaths averted per 100,000 vaccinated. However, when assessing both the cost per hospital day averted (range: USD148-1,344) and the cost per year of life saved (range: USD112-1,230); adults and children with TB disease, HIV-infected adults and pregnant women had the lowest cost per outcome averted.DiscussionAn assessment of the potential disease outcomes averted and associated costs may aid policymakers in risk group prioritization for influenza vaccination.
| S-EPMC6470296 | biostudies-literature
Project description:BackgroundDespite the disproportionate impact of COVID-19 on Latinos, there were disparities in vaccination, especially during the early phase of COVID-19 immunization rollout.MethodsLeveraging a community-academic partnership established to expand access to SARS-CoV2 testing, we implemented community vaccination clinics with multifaceted outreach strategies and flexible appointments for limited English proficiency Latinos.ResultsBetween February 26 and May 7 2021, 2250 individuals received the first dose of COVID-19 vaccination during 18 free community events. Among them, 92.4% (95% confidence interval [CI], 91.2%-93.4%) self-identified as Hispanic, 88.7% (95% CI, 87.2%-89.9%) were limited English proficiency Spanish speakers, 23.1% (95% CI, 20.9%-25.2%) reported prior COVID-19 infection, 19.4% (95% CI, 16.9%-22.25%) had a body mass index of more than 35, 35.0% (95% CI, 32.2%-37.8%) had cardiovascular disease, and 21.6% (95% CI, 19.2%-24.0%) had diabetes. The timely second-dose completion rate was high (98.7%; 95% CI, 97.6%-99.2%) and did not vary by outreach method.ConclusionA free community-based vaccination initiative expanded access for Latinos with limited English proficiency at high risk for COVID-19 during the early phase of the immunization program in the US.
| S-EPMC9528932 | biostudies-literature
Project description:COVID-19 vaccines have been authorized in multiple countries, and more are under rapid development. Careful design of a vaccine prioritization strategy across sociodemographic groups is a crucial public policy challenge given that 1) vaccine supply will be constrained for the first several months of the vaccination campaign, 2) there are stark differences in transmission and severity of impacts from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across groups, and 3) SARS-CoV-2 differs markedly from previous pandemic viruses. We assess the optimal allocation of a limited vaccine supply in the United States across groups differentiated by age and essential worker status, which constrains opportunities for social distancing. We model transmission dynamics using a compartmental model parameterized to capture current understanding of the epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate three alternative policy objectives (minimizing infections, years of life lost, or deaths) and model a dynamic strategy that evolves with the population epidemiological status. We find that this temporal flexibility contributes substantially to public health goals. Older essential workers are typically targeted first. However, depending on the objective, younger essential workers are prioritized to control spread or seniors to directly control mortality. When the objective is minimizing deaths, relative to an untargeted approach, prioritization averts deaths on a range between 20,000 (when nonpharmaceutical interventions are strong) and 300,000 (when these interventions are weak). We illustrate how optimal prioritization is sensitive to several factors, most notably, vaccine effectiveness and supply, rate of transmission, and the magnitude of initial infections.
| S-EPMC8072365 | biostudies-literature
Project description:Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions.
| S-EPMC5821442 | biostudies-literature