The potential contribution of projected ASEAN Power Grid to emission reduction

This paper analyzed the potential contribution of the projected ASEAN Power Grid (APG) with increased contribution of renewable energy (RE) in the power system, toward emission reduction in South East Asia, both in region and country level, in three different scenarios (Baseline, ASEAN Target, and Optimum RE). Data collection was done with a series of (co-creation) consultation meetings with countries in the region and international energy institutes. Estimation of emission reduction from CO2 and N2O was calculated based on projected solar and wind capacity addition to replace fossil fuel consumption in the APG. We found that the potential contribution of the projected APG toward emission reduction in South East Asia is up to 112,267 million tons of CO2 and 64 thousand tons of N2O by 2040, under the optimum RE scenario. The source of that contribution is varying at the country level. Countries with potential significant contributions are Thailand, the Philippines, Vietnam, Malaysia, and Indonesia. Countries like Singapore and Brunei that have a relatively small contribution to the region, also having progressive trends to meet the RE target and its emission reduction. This trend shows a potential progressive improvement for those countries to reduce their emission from the energy sector by 2040. With their current high base scenario, they may reach a higher target in the future to integrate variable RE to the APG and contributing to emission reduction in the region.

Estimating the Smart Readiness Indicator in the Italian Residential Building Stock in Different Scenarios

The Energy Performance of Buildings Directive 2018/844/EU introduced the smart readiness indicator (SRI) to provide a framework to evaluate and promote building smartness in Europe. In order to establish a methodological framework for the SRI calculation, two technical studies were launched, at the end of which a consolidated methodology to calculate the SRI of a building basing on a flexible and modular multicriteria assessment has been proposed. In this paper the authors applied the above-mentioned methodology to estimate the SRI of the Italian residential building stock in different scenarios. To this end, eight “smart building typologies”, representative of the Italian residential building stock, have been identified. For each smart building typology, the SRI was calculated in three scenarios: (a) base scenario (building stock as it is); (b) an “energy scenario” (simple energy retrofit) and (c) a “smart energy scenario” (energy retrofit from a smart perspective). It was therefore possible to estimate a national average SRI value of 5.0%, 15.7%, and 27.5% in the three above defined scenarios, respectively.

Pharmacy-based screening to detect persons at elevated risk of type 2 diabetes: a cost-utility analysis

Background Early identification of people at elevated risk of type 2 diabetes (T2D) is an important step in preventing or delaying its onset. Pharmacies can serve as a significant channel to reach these people. This study aimed to assess the potential health economic impact of screening and recruitment services in pharmacies in referring people to preventive interventions. Methods A decision analytic model was constructed to perform a cost-utility analysis of the expected national health economic consequences (in terms of costs and quality-adjusted life years, QALYs) of a hypothetical pharmacy-based service where people screened and recruited through pharmacies would participate in a digital lifestyle program. Cost-effectiveness was considered in terms of net monetary benefit (NMB). In addition, social return on investment (SROI) was calculated as the ratio of the intervention and recruitment costs and the net present value of expected savings. Payback time was the time taken to reach the break-even point in savings. In the base scenario, a 20-year time horizon was applied. Probabilistic and deterministic sensitivity analyses were applied to study robustness of the results. Results In the base scenario, the expected savings from the pharmacy-based screening and recruitment among the reached target cohort were 255.3 m€ (95% CI − 185.2 m€ to 717.2 m€) in pharmacy visiting population meaning 1412€ (95% CI − 1024€ to 3967€) expected savings per person. Additionally, 7032 QALYs (95% CI − 1344 to 16,143) were gained on the population level. The intervention had an NMB of 3358€ (95% CI − 1397€ to 8431€) using a cost-effectiveness threshold of 50,000 €/QALY. The initial costs were 122.2 m€ with an SROI of 2.09€ (95% CI − 1.52€ to 5.88€). The expected payback time was 10 and 8 years for women and men, respectively. Results were most sensitive for changes in effectiveness of the intervention and selected discount rate. Conclusions T2D screening and recruitment to prevention programs conducted via pharmacies was a dominant option providing both cost savings and QALY gains. The highest savings can be potentially reached by targeting recruitment at men at elevated risk of T2D.

Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach

Despite all the achievements in improving container terminal performance in terms of equipment and container stacking systems (CSS), terminal operators are still facing several challenges. One of these challenges is the lack of information about further transportation modes of the container, which leads to extra movements of the container inside the stacking area. Hence, we aimed to examine factors that affect container handling processes and to evaluate a container terminal’s overall equipment effectiveness. This study used data from a container terminal at the Port of Antwerp, Belgium. An agent-based model was developed based on a block-stacking strategy to investigate two scenarios: (1) having information about further transportation modes and (2) a base scenario. The Overall Equipment Effectiveness Index (OEE) was also adopted to evaluate the container terminal’s effectiveness in both scenarios. Results showed that having information on further transportation mode significantly increased the container outflow, and the OEE index improved compared to the base scenario’s results. Therefore, we recommend an integrated data-sharing system where all the stakeholders can share their information with no fear of losing their market share.

Overdentures as an alternative to conventional dentures: a micro-costing analysis for Public Health Service in Brazil

This study aimed to estimate cost and compatibility with public financial incentives of two technologies for treating the edentulous mandible: lower complete dentures (CD) and overdentures retained by two dental implants (OD). This study consisted of a partial economic evaluation, with a micro-costing bottom-up approach for the calculation of direct costs. The estimates involved the number of consultations, proportion of materials, equipment, instruments’ lifetime, and human resources, described in the price panel website of the Ministry of Economy in Brazil. Complementary information was obtained from a panel of experts. A sensitivity analysis was based on 20% variation. The estimated cost of a CD was R$ 189.89 (base scenario), and this varied between R$ 151.91 and R$ 227.89 according to sensibility analysis. The cost of an OD was R$ 663.05 (ranging from R$ 795.66 to R$ 530.44 - 1US=R$ 3.80/July 2019). The Ministry of Health covers appropriately the costs of the CD and OD. Both technologies showed costs that are within the limits of financial public incentives obtained by municipalities. The technologies are economically viable and should be induced through public policies due to their positive impacts on several functional domains of health.

COVID-19 control strategies and intervention effects in resource limited settings: A modeling study

Introduction Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions–a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)–implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no intervention (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Conclusion Limited resource settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

Macroeconometric Input-Output Model For Transport Sector Analysis

Effective government transport policy can be based only on realistic data, sophisticated and detailed transport sector analysis, and productive modelling. The aim of the paper is to demonstrate the main elements used to develop a relatively small macro-economic input-output model with the emphasis on transport for one European Union (EU) country. Transport sector faces similar problems in various countries linked with emissions, transport flows, road accidents and other issues hence appropriate modelling tool should be selected. The model presented in this article consists of econometric and input-output relations. The research analyses and examines three scenarios and stresses the importance of the transport investment not only for development of the transport sector, but also for the economic development in general. The scenarios imply zero, 9 million and 6.7 million additional investment in transport sector eligible to the EU funding. As the result of additional investment, GDP recovers faster leading to 0.3-1.7%points faster growth rates as compared to the base scenario with no additional investment leading to faster cohesion with the average EU level, as well as higher number and turnover of passengers in the public and commercial transport, while the number of passenger cars is lower. The model can also be applied to study regional development, if it is possible to distinguish, which regions will benefit from the investment, as well as influence on fuel consumption and CO2 emissions, if the investments are targeted to specific means of transport.

Control programs for strongyloidiasis in areas of high endemicity: an economic analysis of different approaches

Background Implementation of control programmes for Strongyloides stercoralis infection is among the targets of the World Health Organization Roadmap to 2030. Aim of this work was to evaluate the possible impact in terms of economic resources and health status of two different strategies of preventive chemotherapy (PC) compared to the current situation (strategy A, no PC): administration of ivermectin to school-age children (SAC) and adults (strategy B) versus ivermectin to SAC only (strategy C). Methods The study was conducted at the IRCCS Sacro Cuore Don Calabria hospital, Negrar di Valpolicella, Verona, Italy, at the University of Florence, Italy, and at the WHO, Geneva, Switzerland, from May 2020 to April 2021. Data for the model were extracted from literature. A mathematical model was developed in Microsoft Excel to assess the impact of strategies B and C in a standard population of 1 million subjects living in a strongyloidiasis endemic area. In a case base scenario, 15% prevalence of strongyloidiasis was considered; the 3 strategies were then evaluated at different thresholds of prevalence, ranging from 5 to 20%. The results were reported as number of infected subjects, deaths, costs, and Incremental-Effectiveness Ratio (ICER). A 1-year and a 10-year horizons were considered. Results In the case base scenario, cases of infections would reduce dramatically in the first year of implementation of PC with both strategy B and C: from 172 500 cases to 77 040 following strategy B and 146 700 following strategy C. The additional cost per recovered person was United States Dollar (USD) 2.83 and USD 1.13 in strategy B and C, respectively, compared to no treatment in the first year. For both strategies, there was a downtrend in costs per recovered person with increasing prevalence. The number of adverted deaths was larger for strategy B than C, but cost to advert one death was lower for strategy C than B. Conclusions This analysis permits to estimate the impact of two PC strategies for the control of strongyloidiasis in terms of costs and adverted infections/deaths. This could represent a basis on which each endemic country can evaluate which strategy can be implemented, based on available funds and national health priorities.

Environmental impact of personal protective equipment distributed for use by health and social care services in England in the first six months of the COVID-19 pandemic

Objective To quantify the environmental impact of personal protective equipment (PPE) distributed for use by the health and social care system to control the spread of SARS-CoV-2 in England, and model strategies for mitigating the environmental impact. Design Life cycle assessment was used to determine environmental impacts of PPE distributed to health and social care in England during the first six months of the COVID-19 pandemic. The base scenario assumed all products were single-use and disposed of via clinical waste. Scenario modelling was used to determine the effect of environmental mitigation strategies: (1) eliminating international travel during supply; (2) eliminating glove use; (3) reusing gowns and face shields; and (4) maximal recycling. Setting Royal Sussex County Hospital, Brighton, UK. Main outcome measures The carbon footprint of PPE distributed during the study period totalled 106,478 tonnes CO2e, with greatest contributions from gloves, aprons, face shields and Type IIR surgical masks. The estimated damage to human health was 239 DALYs (disability-adjusted life years), impact on ecosystems was 0.47 species.year (loss of local species per year), and impact on resource depletion was costed at US $12.7m (GBP £9.3m). Scenario modelling indicated UK manufacture would have reduced the carbon footprint by 12%, eliminating gloves by 45%, reusing gowns and gloves by 10% and maximal recycling by 35%. Results A combination of strategies may have reduced the carbon footprint by 75% compared with the base scenario, and saved an estimated 183 DALYS, 0.34 species.year and US $7.4m (GBP £5.4m) due to resource depletion. Conclusion The environmental impact of PPE is large and could be reduced through domestic manufacture, rationalising glove use, using reusables where possible and optimising waste management.

Decentralised Electricity Markets and Proactive Customer Behaviour

The energy transition in Germany takes part in decentral structures. With the ongoing integration of Renewable Energy Sources (RES) into the electricity supply system, supply-side is therefore becoming increasingly decentral and volatile due to the specific generation characteristics. A rather inflexible demand-side, on the other hand, increases the effort to gain the necessary equilibrium between generation and consumption. This paper discusses how consumer behaviour can be influenced by real-time pricing to align demand with generation. Therefore, a combination of two different approaches is used, (I) The Cellular Approach (CA) and (II) Agent Based Modelling (ABM). A model is set up considering a regional energy market, where regional electricity products can be traded peer-to-peer regarding each consumer’s preferences. The observation is made for a whole distribution grid including all types of consumers. The investigations show that energy purchases can be stimulated individually by a flexible pricing mechanism and met preferences. Moreover, benefits occur for the whole region and potentials arise to smooth the exchange balance to the superordinate grid level. Running the model for one entire year in a conservative generation scenario, hours of oversupply could be reduced by 18% and the consumption of green electricity generated regionally could be increased by over 125 MWh within the region itself, in comparison to a base scenario.