Cost effectiveness of different cervical screening strategies in Islamic Republic of Iran: a middle-income country with a low incidence rate of cervical cancer

Objective: Invasive cervical cancer (ICC) is the fourth most common cancer among women worldwide. Cervical screening programs have reduced the incidence and mortality rates of ICC. We studied the cost-effectiveness of different cervical screening strategies in the Islamic Republic of Iran, a Muslim country with a low incidence rate of ICC. Methods: We constructed an 11-state Markov model, in which the parameters included regression and progression probabilities, test characteristics, costs, and utilities; these were extracted from primary data and the literature. Our strategies included Pap smear screening and human papillomavirus (HPV) DNA testing plus Pap smear triaging with different starting ages and screening intervals. Model outcomes included lifetime costs, life years gained, quality-adjusted life years (QALY), and incremental cost-effectiveness ratios (ICERs). One-way sensitivity analysis was performed to examine the stability of the results. Results: We found that the prevented mortalities for the 11 strategies compared with no screening varied from 26% to 64%. The most cost-effective strategy was HPV screening, starting at age 35 years and repeated every 10 years. The ICER of this strategy was $8,875 per QALY compared with no screening. We found that screening at 5-year intervals was also cost-effective based on GDP per capita in Iran. Conclusion: We recommend organized cervical screening with HPV DNA testing for women in Iran, beginning at age 35 and repeated every 10 or 5 years. The results of this study could be generalized to other countries with low incidence rates of cervical cancer

Cost-effectiveness of anatomical and functional test strategies for stable chest pain : public health perspective from a middle-income country

Objectives The aim of this research is to evaluate the relative cost-effectiveness of functional and anatomical strategies for diagnosing stable coronary artery disease (CAD), using exercise (Ex)-ECG, stress echocardiogram (ECHO), single-photon emission CT (SPECT), coronary CT angiography (CTA) or stress cardiacmagnetic resonance (C-MRI). Setting Decision-analytical model, comparing strategies of sequential tests for evaluating patients with possible stable angina in low, intermediate and high pretest probability of CAD, from the perspective of a developing nation’s public healthcare system. Participants Hypothetical cohort of patients with pretest probability of CAD between 20% and 70%. Primary and secondary outcome measures The primary outcome is cost per correct diagnosis of CAD. Proportion of false-positive or false-negative tests and number of unnecessary tests performed were also evaluated. Results Strategies using Ex-ECG as initial test were the least costly alternatives but generated more frequent false-positive initial tests and false-negative final diagnosis. Strategies based on CTA or ECHO as initial test were the most attractive and resulted in similar cost-effectiveness ratios (I$286 and I$ 305 per correct diagnosis, respectively). A strategy based on C-MRI was highly effective for diagnosing stable CAD, but its high cost resulted in unfavourable incremental cost-effectiveness (ICER) in moderate-risk and high-risk scenarios. Noninvasive strategies based on SPECT have been dominated. Conclusions An anatomical diagnostic strategy based on CTA is a cost-effective option for CAD diagnosis. Functional strategies performed equally well when based on ECHO. C-MRI yielded acceptable ICER only at low pretest probability, and SPECT was not cost-effective in our analysis

Low Cost Ataukah Differensiasi? Studi Empiris Implementasi Strategi Pada Industri Adhesive Dan Sealant Di Bursa Efek Indonesia

This research aims to test whether low cost and differentiation strategies were implemented partially or simultaneously by the firms in adhesive and sealant industry which listed on Indonesia Stock Exchange. This research also tested whether the firm size is one of the factors which contributed to its performance. The results show that both low cost and differentiation strategies were more effective to implement simultaneously rather than focusing on one strategy. For size's firm factor, the result proved that it didn't have any influence to its firm performance when implementing their strategies. Unavailability of research and development fund in the firm budget can be predicted why firm size has no influence to firm's performance

Air-to-Water Heat Pumps With Radiant Delivery in Low-Load Homes

Space conditioning represents nearly 50% of average residential household energy consumption, highlighting the need to identify alternative cost-effective, energy-efficient cooling and heating strategies. As homes are better built, there is an increasing need for strategies that are particularly well suited for high performance, low load homes. ARBI researchers worked with two test homes in hot-dry climates to evaluate the in-situ performance of air-to-water heat pump (AWHP) systems, an energy efficient space conditioning solution designed to cost-effectively provide comfort in homes with efficient, safe, and durable operation. Two monitoring projects of test houses in hot-dry climates were initiated in 2010 to test this system. Both systems were fully instrumented and have been monitored over one year to capture complete performance data over the cooling and heating seasons. Results are used to quantify energy savings, cost-effectiveness, and system performance using different operating modes and strategies. A calibrated TRNSYS model was developed and used to evaluate performance in various climate regions. This strategy is most effective in tight, insulated homes with high levels of thermal mass (i.e. exposed slab floors)

Prototyping the BOPTEST framework for simulation-based testing of advanced control strategies in buildings

Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case

Outlook for tuberculosis elimination in California: An individual-based stochastic model.

RationaleAs part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).ObjectivesTo estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.MethodsWe created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.Measurements and main resultsIn the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to$48 billion. These had an incremental cost per QALY of $657,000 to$3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.ConclusionsSubstantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks

Pooling of Samples to Increase Testing Capacity for COVID-19

Test, trace and isolate are the main pillars of the containment strategies promoted by epidemiologists in the COVID-19 pandemic. Equipment, material and labour required for testing is, however, limited, making it a challenge to adopt testing at a large scale. Pooling of samples has the potential to reduce the number of tests required for screening a population with a low infection prevalence. We provide a detailed analysis of a well-known pooling strategy called two-stage pooling which involves testing pools of a fixed size. We show that, while this approach can potentially reduce the number of tests, evaluating its cost effectiveness and configuring it optimally require existence of a reliable estimate of prevalence in the population. In the absence of such information, we propose inferring a prior distribution of the underlying prevalence using a combination of expert opinion and a limited exploratory testing of the population, and applying it with either a two-stage fixed pooling strategy, or a multi-stage adaptive pooling strategy. We explain how each of these strategies can be applied, propose algorithms for finding their corresponding optimal pool size, and identify the situations under which each of these strategies is preferred