Optimizing the Efficiency of the United States Organ Allocation System through Region Reorganization

Allocating organs for transplantation has been controversial in the United States for decades. Two main allocation approaches developed in the past are (1) to allocate organs to patients with higher priority at the same locale; (2) to allocate organs to patients with the greatest medical need regardless of their locations. To balance these two allocation preferences, the U.S. organ transplantation and allocation network has lately implemented a three-tier hierarchical allocation system, dividing the U.S. into 11 regions, composed of 59 Organ Procurement Organizations (OPOs). At present, an procured organ is offered first at the local level, and then regionally and nationally. The purpose of allocating organs at the regional level is to increase the likelihood that a donor-recipient match exists, compared to the former allocation approach, and to increase the quality of the match, compared to the latter approach. However, the question of which regional configuration is the most efficient remains unanswered. This dissertation develops several integer programming models to find the most efficient set of regions. Unlike previous efforts, our model addresses efficient region design for the entire hierarchical system given the existing allocation policy. To measure allocation efficiency, we use the intra-regional transplant cardinality. Two estimates are developed in this dissertation. One is a population-based estimate; the other is an estimate based on the situation where there is only one waiting list nationwide. The latter estimate is a refinement of the former one in that it captures the effect of national-level allocation and heterogeneity of clinical and demographic characteristics among donors and patients. To model national-level allocation, we apply a modeling technique similar to spill-and-recapture in the airline fleet assignment problem. A clinically based simulation model is used in this dissertation to estimate several necessary parameters in the analytic model and to verify the optimal regional configuration obtained from the analytic model. The resulting optimal region design problem is a large-scale set-partitioning problem in whichthere are too many columns to handle explicitly. Given this challenge, we adapt branch and price in this dissertation. We develop a mixed-integer programming pricing problem that is both theoretically and practically hard to solve. To alleviate this existing computational difficulty, we apply geographic decomposition to solve many smaller-scale pricing problems based on pre-specified subsets of OPOs instead of a big pricing problem. When solving each smaller-scale pricing problem, we also generate multiple ``promising' regions that are not necessarily optimal to the pricing problem. In addition, we attempt to develop more efficient solutions for the pricing problem by studying alternative formulations and developing strong valid inequalities. The computational studies in this dissertation use clinical data and show that (1) regional reorganization is beneficial; (2) our branch-and-price application is effective in solving the optimal region design problem

Codon usage analysis of prokaryotic mechanosensation genes

[Abstract]: In the present study, we examined GC nucleotide composition, relative synonymous codon usage (RSCU), effective number of codons (ENC), codon adaptation index (CAI) and gene length for 308 prokaryotic mechanosensitive ion channel (MSC) genes from six evolutionary groups: Euryarchaeota, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Firmicutes, and Gammaproteobacteria. Results showed that 1). a wide variation of overrepresentation of nucleotides exists in the MSC genes; 2). codon usage bias varies considerably among the MSC genes; 3). both nucleotide constraint and gene length play an important role in shaping codon usage of the bacterial MSC genes and 4). synonymous codon usage of prokaryotic MSC genes is phylogenetically conserved. Knowledge of codon usage in prokaryotic MSC genes may benefit for the study of the MSC genes in eukaryotes in which few MSC genes have been identified and functionally analysed

Optimizing strategies for population-based chlamydia infection screening among young women: an age-structured system dynamics approach

BACKGROUND: Chlamydia infection (CT) is one of the most commonly reported sexually transmitted diseases. It is often referred to as a "silent" disease with the majority of infected people having no symptoms. Without early detection, it can progress to serious reproductive and other health problems. Economical identification of asymptomatically infected is a key public health challenge. Increasing evidence suggests that CT infection risk varies over the range of adolescence. Hence, age-dependent screening strategies with more frequent testing for certain age groups of higher risk may be cost-saving in controlling the disease. METHODS: We study the optimization of age-dependent screening strategies for population-based chlamydia infection screening among young women. We develop an age-structured compartment model for CT natural progress, screening, and treatment. We apply parameter optimization on the resultant PDE-based system dynamical models with the objective of minimizing the total care spending, including screening and treatment costs during the program period and anticipated costs of treating the sequelae afterwards). For ease of practical implementation, we also search for the best screening initiation age for strategies with a constant screening frequency. RESULTS: The optimal age-dependent strategies identified outperform the current CDC recommendations both in terms of total care spending and disease prevalence at the termination of the program. For example, the age-dependent strategy that allows monthly screening rate changes can save about 5% of the total spending. Our results suggest early initiation of CT screening is likely beneficial to the cost saving and prevalence reduction. Finally, our results imply that the strategy design may not be sensitive to accurate quantification of the age-specific CT infection risk if screening initiation age and screening rate are the only decisions to make. CONCLUSIONS: Our research demonstrates the potential economic benefit of age-dependent screening strategy design for population-based screening programs. It also showcases the applicability of age-structured system dynamical modeling to infectious disease control with increasing evidence on the age differences in infection risk. The research can be further improved with consideration of the difference between first-time infection and reinfection, as well as population heterogeneity in sexual partnership

Acoustic Analysis of Vocalizations for Detecting Separation Anxiety in Dogs

Separation anxiety in dogs is a clinical condition in which a dog develops an intense dependence on their caretaker. It manifests itself in maladaptive physical and psychological behaviors that are similar to that of panic attacks in humans when the dog is isolated from its owner. These include excessive vocalizations, destructive behaviors, and in more extreme cases, self-mutilation. Currently, there are no direct ways to diagnose separation anxiety without the aid an owner’s report. To ease this diagnostic process, it would be useful to utilize a tool that can distinguish between certain vocalization patterns in dogs. Literature suggests that some vocalizations, such as whining, reveals information about the dogs wellbeing. The purpose of this study is to initiate steps to build and implement a classifier that will distinguish between different dog vocalizations. This process involved meticulously preparing the data by extracting, labeling, and separating the vocalizations in a sound editing software. Mathematical models of several acoustic parameters were constructed to obtain critical information from each file. With this information, a classifier can be built and could ultimately aid in understanding the underlying emotions in dogs suffering from separation anxiety

Optimizing strategies for population-based chlamydia infection screening among young women: An age-structured system dynamics approach Infectious Disease epidemiology

Background Chlamydia infection (CT) is one of the most commonly reported sexually transmitted diseases. It is often referred to as a “silent” disease with the majority of infected people having no symptoms. Without early detection, it can progress to serious reproductive and other health problems. Economical identification of asymptomatically infected is a key public health challenge. Increasing evidence suggests that CT infection risk varies over the range of adolescence. Hence, age-dependent screening strategies with more frequent testing for certain age groups of higher risk may be cost-saving in controlling the disease. Methods We study the optimization of age-dependent screening strategies for population-based chlamydia infection screening among young women. We develop an age-structured compartment model for CT natural progress, screening, and treatment. We apply parameter optimization on the resultant PDE-based system dynamical models with the objective of minimizing the total care spending, including screening and treatment costs during the program period and anticipated costs of treating the sequelae afterwards). For ease of practical implementation, we also search for the best screening initiation age for strategies with a constant screening frequency. Results The optimal age-dependent strategies identified outperform the current CDC recommendations both in terms of total care spending and disease prevalence at the termination of the program. For example, the age-dependent strategy that allows monthly screening rate changes can save about 5 % of the total spending. Our results suggest early initiation of CT screening is likely beneficial to the cost saving and prevalence reduction. Finally, our results imply that the strategy design may not be sensitive to accurate quantification of the age-specific CT infection risk if screening initiation age and screening rate are the only decisions to make. Conclusions Our research demonstrates the potential economic benefit of age-dependent screening strategy design for population-based screening programs. It also showcases the applicability of age-structured system dynamical modeling to infectious disease control with increasing evidence on the age differences in infection risk. The research can be further improved with consideration of the difference between first-time infection and reinfection, as well as population heterogeneity in sexual partnership

Estimating Age-Dependent Per-Encounter Chlamydia Trachomatis Acquisition Risk Via a Markov-Based State-Transition Model.

Background Chlamydial infection is a common bacterial sexually transmitted infection worldwide, caused byC. trachomatis. The screening for C. trachomatis has been proven to be successful. However, such success is not fully realized through tailoring the recommended screening strategies for different age groups. This is partly due to the knowledge gap in understanding how the infection is correlated with age. In this paper, we estimate age-dependent risks of acquiring C. trachomatisby adolescent women via unprotected heterosexual acts. Methods We develop a time-varying Markov state-transition model and compute the incidences of chlamydial infection at discrete age points by simulating the state-transition model with candidate per-encounter acquisition risks and sampled numbers of unit-time unprotected coital events at different age points. We solve an optimization problem to identify the age-dependent estimates that offer the closest matches to the observed infection incidences. We also investigate the impact of antimicrobial treatment effectiveness on the parameter estimates and the differences between the acquisition risks for the first-time infections and repeated infections. Results Our case study supports the beliefs that age is an inverse predictor of C. trachomatistransmission and that protective immunity developed after initial infection is only partial. Conclusions Our modeling method offers a flexible and expandable platform for investigating STI transmission

Maximizing the Delivery Performance of Point-of-Care CD4+ T-Cell Counting Tests in Resource-Limited Settings - A Policy Brief

Managing HIV/AIDS presents challenges to public health policymakers, frontline workers, and researchers worldwide. A key strategy in the disease management is early diagnosis and rapid treatment initiation. While the technological field of point‐of‐care HIV/AIDS diagnostics has advanced significantly in the past two decades, several critical issues remain that hinder the deployment of point‐of‐care testing devices in resource‐deprived settings. In this policy brief, we discuss these issues, including technological specifics of point‐of‐care CD4+ T‐cell counting approaches and requirements of deploying them. We also discuss cultural and religious concerns on the deployment. At the end of the brief, we propose a roadmap for the efficient and cost‐effective deployment and call for action to assemble multidisciplinary teams for the undertaking. We argue that joint effort must be taken to conduct research and development for low‐cost portable point‐of‐care testing and for tailoring the technology deployment and care delivery support system design for specific cohorts