COVID-19 vaccine prioritization of incarcerated people relative to other vulnerable groups: An analysis of state plans

Background Carceral facilities are epicenters of the COVID-19 pandemic, placing incarcerated people at an elevated risk of COVID-19 infection. Due to the initial limited availability of COVID-19 vaccines in the United States, all states have developed allocation plans that outline a phased distribution. This study uses document analysis to compare the relative prioritization of incarcerated people, correctional staff, and other groups at increased risk of COVID-19 infection and morbidity. Methods and findings We conducted a document analysis of the vaccine dissemination plans of all 50 US states and the District of Columbia using a triple-coding method. Documents included state COVID-19 vaccination plans and supplemental materials on vaccine prioritization from state health department websites as of December 31, 2020. We found that 22% of states prioritized incarcerated people in Phase 1, 29% of states in Phase 2, and 2% in Phase 3, while 47% of states did not explicitly specify in which phase people who are incarcerated will be eligible for vaccination. Incarcerated people were consistently not prioritized in Phase 1, while other vulnerable groups who shared similar environmental risk received this early prioritization. States’ plans prioritized in Phase 1: prison and jail workers (49%), law enforcement (63%), seniors (65+ years, 59%), and long-term care facility residents (100%). Conclusions This study demonstrates that states’ COVID-19 vaccine allocation plans do not prioritize incarcerated people and provide little to no guidance on vaccination protocols if they fall under other high-risk categories that receive earlier priority. Deprioritizing incarcerated people for vaccination misses a crucial opportunity for COVID-19 mitigation. It also raises ethical and equity concerns. As states move forward with their vaccine distribution, further work must be done to prioritize ethical allocation and distribution of COVID-19 vaccines to incarcerated people.

Studying the Effect of Channel Geometry on Different Water Quality Variables for Effective Designs and Waste Allocation Plans for Waterways

It is necessary to study the parameters that affect water quality in order to devise mitigation measures if water quality would be at risk or negatively affected by those parameters. Those parameters are physical, chemical, biological, and hydraulic characteristics. This research will study the effect of channel geometry on different water quality variables, which is important in designing new irrigation canals in order to see how its geometry will affect water quality and lessen any negative impact if possible; also this study could aid in designing more reliable waste allocation plans for waterways. The studied geometric characteristics are top width, bottom width, water depth, side-slopes and channel length. Sheikh Zayed canal in Egypt is taken as the reference case study canal. Studied water quality variables are algae, nutrients, total dissolved solids (TDS), total suspended solids (TSS), pH, alkalinity and total inorganic carbon. It was found that concentrations of all water quality variables in water changed as a result of changing channel geometry. Some water quality variables such as algae, nutrients, and TSS are greatly affected, whereas others such as pH, alkalinity and total inorganic carbon are slightly affected.

Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China

With the rapid increase of water demand in urban life, ecology and production sectors, the problem of water resources allocation has become increasingly prominent. It has hindered the sustainable development of urban areas. Based on the supply of various water sources and the water demand of different water users, a multi-objective optimal allocation model for urban water resources was proposed. The model was solved using the algorithm of particle swarm optimization (PSO). The algorithm has a fast convergence and is both simple and efficient. In this paper, the conflict over Kunming’s water resources allocation was taken as an example. The PSO algorithm was used to obtain optimized water resources allocation plans in the year 2020 and 2030, under the circumstances of a dry year (inflow guarantee rate p = 0.825) and an unusually dry year (inflow guarantee rate p = 0.885), respectively. The results showed that those allocation plans can lower the future potential water shortage rates of Kunming. At the same time, the interests of different sectors can all be satisfied. Therefore, conflicts over urban water use can be effectively alleviated.

Using Multiple Discriminant Analysis for the Assignment of Initial Water Entitlements at River Basin-Level under the Strictest Water Resources Management System Constraints in China

From the perspective of system science, in China, an assignment system of initial water entitlements at the river basin-level can be divided into two subsystems, namely the assignment subsystem of initial water entitlements at the province-level and government reserved water at the river basin-level. Under the new backdrop of implementing the strictest water resources management system (SWRMS), we propose a novel methodological framework for addressing the in-coordination of pre-allocation plans between two subsystems for Lake Tai Basin, China. First, considering total water use, pollutant discharge and water use efficiency, we establish several criteria for the discriminant analysis of pre-allocation plans. Whilst based on these criteria, we built a comprehensive discriminant criterion to further verify coupling and coordination of pre-allocation plans between two subsystems. Second, according to uncoordinated or less coordinated situations, we propose adjusted strategies to decide the direction (increase or decrease) of the adjustment for pre-allocation plans of two subsystems. Third, taking coupling and coordination as optimal objectives, and considering total water use, total pollutant discharge and water use efficiency as constraints, we built an adjusted decision-making model for the assignment of initial water entitlements of the basin. Finally, the results of this novel discriminant analysis methodology that were applied to the Lake Tai Basin show that under the water frequency of 75%, in the planning year 2030, Jiangsu Province is assigned the most initial water entitlements at the province-level, followed by Shanghai and Zhejiang Province. In this paper, results are generally in accordance with pilot plans released by China’s Ministry of Water Resources. Apart from pilot plans, our findings also show the assignment plans for government reserved water at the river basin-level, which is coordinated and coupled with assignment plans for initial water entitlements at the province-level. The novel methodological framework of this paper can also be applied as a reference to other similar river basin.

A joint-probabilistic programming method for water resources optimal allocation under uncertainty: a case study in the Beiyun River, China

In recent years, the lower reaches of the Beiyun River have suffered from growing water resource shortages due to the reduction of upstream water resource and drying up of the stream channel. More reasonable and scientifically based water allocation plans should be developed and implemented; however, uncertainties exist regarding the determination of water supply availability and spillage of extra water. To assess and manage regional water shortage, the combined effects of multiple water supply sources as well as the joint probability of typical events should be considered. The joint probability of water supply, considering upstream and local water supplies, was estimated through the copula functions. A multi-objective optimization model was then developed and solved by improved genetic algorithms to plan water resources allocation within a multi-source environment containing multiple competitive users. The framework is demonstrated, and represents a range of different water supply scenarios in terms of different probabilities of occurrence and constraint violations. The results showed that water allocation was greatly influenced by uncertainties, especially in upstream-local water supply. In addition, violating water-allocation constraint posed an extra uncertainty. This study facilitates the proposition of adaption allocation plans for uncertain environments, aiming to balance the shortage, economy, and reliability.