Lifetime cost models for large, long-lived, street trees in Australia

2022 ◽  
pp. 1-21
Author(s):  
Gregory M. Moore
2021 ◽  
pp. 1-25
Author(s):  
Robert C. Schell ◽  
David R. Just ◽  
David A. Levitsky

Abstract There is a great deal of variability in estimates of the lifetime medical care cost externality of obesity, partly due to a lack of transparency in the methodology behind these cost models. Several important factors must be considered in producing the best possible estimate, including age-related weight gain, differential life expectancy, identifiability, and cost model selection. In particular, age-related weight gain represents an important new component to recent cost estimates. Without accounting for age-related weight gain, a study relies on the untenable assumption that people remain the same weight throughout their lives, leading to a fundamental misunderstanding of the evolution and development of the obesity crisis. This study seeks to inform future researchers on the best methods and data available both to estimate age-related weight gain and to accurately and consistently estimate obesity’s lifetime external medical care costs. This should help both to create a more standardized approach to cost estimation as well as encourage more transparency between all parties interested in the question of obesity’s lifetime cost and, ultimately, evaluating the benefits and costs of interventions targeting obesity at various points in the life course.


1988 ◽  
Vol 6 (1) ◽  
pp. 35-48
Author(s):  
Greg M. Thibadoux ◽  
Nicholas Apostolou ◽  
Ira S. Greenberg

1983 ◽  
Vol 2 (2) ◽  
pp. 155-164 ◽  
Author(s):  
Robert L. Thayer ◽  
James Zanetto ◽  
Bruce T. Maeda
Keyword(s):  

2002 ◽  
Vol 86 (11) ◽  
pp. 32-38
Author(s):  
Weijun Yang ◽  
Peiyomg He ◽  
Jianren Zhang

2006 ◽  
Vol 33 (8) ◽  
pp. 1065-1074 ◽  
Author(s):  
Tarek M Zayed ◽  
Ibrahim A Nosair

Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.


Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 931
Author(s):  
Chi-Leung Chiang ◽  
Sik-Kwan Chan ◽  
Shing-Fung Lee ◽  
Horace Cheuk-Wai Choi

Background: The IMbrave 150 trial revealed that atezolizumab plus bevacizumab (atezo–bev) improves survival in patients with unresectable hepatocellular carcinoma (HCC) (1 year survival rate: 67.2% vs. 54.6%). We assessed the cost-effectiveness of atezo–bev vs. sorafenib as first-line therapy in patients with unresectable HCC from the US payer perspective. Methods: Using data from the IMbrave 150, we developed a Markov model to compare the lifetime cost and efficacy of atezo–bev as first-line systemic therapy in HCC with those of sorafenib. The main outcomes were life-years, quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratio (ICER). Results: Atezo–bev demonstrated a gain of 0.44 QALYs, with an additional cost of USD 79,074. The ICER of atezo–bev was USD 179,729 per QALY when compared with sorafenib. The model was most sensitive to the overall survival hazard ratio and body weight. If we assumed that all patients at the end of the IMbrave 150 trial were cured of HCC, atezo–bev was cost-effective (ICER USD 53,854 per QALY). However, if all patients followed the Surveillance, Epidemiology, and End Results data, the ICER of atezo–bev was USD 385,857 per QALY. Reducing the price of atezo–bev by 20% and 29% would satisfy the USD 150,000/QALY and 100,000/QALY willingness-to-pay threshold. Moreover, capping the duration of therapy to ≤12 months or reducing the dosage of bev to ≤10 mg/kg would render atezo–bev cost-effective. Conclusions: The long-term effectiveness of atezo–bev is a critical but uncertain determinant of its cost-effectiveness. Price reduction would favorably influence cost-effectiveness, even if long-term clinical outcomes were modest. Further studies to optimize the duration and dosage of therapy are warranted.


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