Abstract: In the context of updating the 2015 Nationally Determined Contribution (NDC), the government of Chile has updated its estimates of compliance costs for a series of mitigation actions with an emphasis on the energy sector as the main source of its greenhouse gas emissions. Using the information developed in this process, we assess the impact on compliance costs of increasing the flexibility for sources by introducing different emissions trading schemes. For this we develop a detailed optimization model that represents the operational and investment decisions that could be taken by the energy generation, industrial and mining sectors if an Emissions Trading System (ETS) was implemented. An ETS with two cap and trade options is analysed together with an offset mechanism for sources not included in the ETS. Also, two policy goals are considered: a stringent 76% sectoral reduction goal in 2050 similar to Chile's current strict NDC, and a more lax 46% goal similar to Chile's initial 2015 NDC proposal. The results show that (i) cost reductions from increased flexibility for Chile's current strict NDC are significant, and that offsets can play an important role; (ii) the stringency of the reduction goal affects the magnitude of the cost savings related to flexibility and, surprisingly, total abatement costs are negative (i.e. there are benefits) for the 46% reduction goal. In this latter case, the most significant cost reductions result from compelling firms to comply with their allowances in each sector, not increased flexibility. These results highlight the policy relevance of case by case analysis using a modelling approach similar to the one we develop here. Key policy insights ETS implementation can help Chile meet its mitigation commitment for 2050. The compliance costs can vary significantly depending on the flexibility implemented in the emissions trading schemes. Optimization models can help decision-makers define the attributes of an ETS, such as the sectors that should participate, the cap, and the percentage of offsets. The proposed methodology also highlights and quantifies the offsets that can be acquired from sectors that are not part of an ETS, such as forestry, agriculture, and the waste sector. The possibility to acquire of offsets could reduce significantly the cost for industries that participate of an ETS.

Abstract: Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics.

Abstract: In this paper, we analyze the effects of vaccination from a spatial perspective. We propose a spatial deterministic SIRS-V model, which considers a non-linear system of partial differential equations with explicit attrition and diffusion terms for the vaccination process. The model allows us to simulate numerically the spatial and temporal dynamics of an epidemic, considering different spatial strategies for the vaccination policy. In particular, in our first example we analyze the classical SIRS-V evolution with the addition of movements due to diffusion, while in the second one we focus on modeling one ring vaccination policy. We expect this model can improve spatial predictions of SIR vaccination models by taking into account the spatial dimension of the problem. (C) 2020 Elsevier Ltd. All rights reserved.

Abstract: Malaria remains a major health problem in many parts of the world, including Sub-Saharan Africa. Insecticide-treated nets, in combination with other control measures, have been effective in reducing malaria incidence over the past two decades. Nevertheless, there are concerns about improper handling and misuse of nets, producing possible health effects from intoxication and collateral environmental damage. The latter is caused, for instance, from artisanal fishing. We formulate a model of impulsive differential equations to describe the interplay between malaria dynamics, human intoxication, and ecosystem damage; affected by human awareness to these risks and levels of net usage. Our results show that an increase in mosquito net coverage reduces malaria prevalence and increases human intoxications. In addition, a high net coverage significantly reduces the risk perception to disease, naturally increases the awareness for intoxications from net handling, and scarcely increases the risk perception to collateral damage from net fishing. According to our model, campaigns aiming at reducing disease prevalence or intoxications are much more successful than those creating awareness to ecosystem damage. Furthermore, we can observe from our results that introducing closed fishing periods reduces environmental damage more significantly than strategies directed towards increasing the risk perception for net fishing.

Abstract: There have been efforts to use building demolition waste as an alternative aggregate in concrete to decrease the use of natural resources for construction. The World Green Building Council estimates that the construction industry is responsible for more than 50% of all material extracted globally and that construction and demolition waste makes up 35% of global landfills. As a result, incorporating recycled aggregate (RA) in concrete production is a prudent course of action to reduce the environmental impact. This study reviews prior research on using recycled aggregate instead of conventional ingredients in concrete. The composition and morphology of different types of RA, the behavior of RA in fresh and hardened states, keyword co-occurrence and evolution analysis, and the various additives used to enhance the inferior properties of RA are discussed. The RA showed different physical properties when compared with natural aggregate. However, the addition of pozzolanic materials and various pretreatment techniques is desirable for improving the inferior properties of RA. While building waste has been utilized as a substitute for fine and coarse aggregate, prior research has demonstrated that a modified mixing approach, an adequate mixing proportion, and the optimum replacement of cementitious materials are necessary. Based on the review, the recommendation is to use RA at a replacement level of up to 30% and the addition of precoated and pozzolanic materials as a treatment to provide concrete with adequate workability, strength, and durability for structural applications.

Abstract: Chile has lower breast cancer incidence rates compared to those in developed countries. Our public health system aims to perform 10 biennial screening mammograms in the age group of 50 to 69 years by 2020. Using a dynamic programming model, we have found the optimal ages to perform 10 screening mammograms that lead to the lowest lifetime death rate and we have evaluated a set of fixed inter-screening interval policies. The optimal ages for the 10 mammograms are 43, 47, 51, 54, 57, 61, 65, 68, 72, and 76 years, and the most effective fixed inter-screening is every four years after the 40 years. Both policies respectively reduce lifetime death rate in 6.4% and 5.7% and the cost of saving one life in 17% and 9.3% compared to the 2020 Chilean policy. Our findings show that two-year inter-screening interval policies are less effective in countries with lower breast cancer incidence; thus we recommend screening policies with a wider age range and larger inter-screening intervals for Chile.

Abstract: The growth of demand response programs and renewable generation is changing the economics of transmission. Planners and regulators require tools to address the implications of possible technology, policy, and economic developments for the optimal configuration of transmission grids. We propose a model for economic evaluation and optimization of inter-regional transmission expansion, as well as the optimal response of generators' investments to locational incentives, that accounts for Kirchhoff's laws and three important nonlinearities. The first is consumer response to energy prices, modeled using elastic demand functions. The second is resistance losses. The third is the product of line susceptance and flows in the linearized DC load flow model. We develop a practical method combining Successive Linear Programming with Gauss-Seidel iteration to co-optimize AC and DC transmission and generation capacities in a linearized DC network while considering hundreds of hourly realizations of renewable supply and load. We test our approach for a European electricity market model including 33 countries. The examples indicate that demand response can be a valuable resource that can significantly affect the economics, location, and amounts of transmission and generation investments. Further, representing losses and Kirchhoff's laws is also important in transmission policy analyses.

Abstract: A low-complexity decision model for a Home Energy Management System is proposed to follow demand trajectory sets received from a Demand Side Response aggregator. This model is designed to reduce its computational complexity and being solved by low performance processors using available Single-Board Computers as a proof of concept. To decrease the computational complexity is proposed a two-stage model, where the first stage evaluates the hourly appliance scheduling using a relaxed set of restrictions, and the second stage evaluates a reduced set of appliances in a intra-hourly interval with a detailed characterization of the scheduled appliance properties. Simulations results show the effectiveness of the proposed algorithm to follow trajectories for different sets of home appliances and operational conditions. For the studied cases, the model presents deviations in the demand for the 3.2% of the cases in the first-stage and a 12% for the second-stage model. Results show that the proposed model can schedule available appliances according to the demand aggregator requirements in a limited solving time with diverse hardware.

Abstract: This paper analyzes the impacts of the first wave of COVID-19 (March 2020 -September 2020) on the electricity demand of different types of consumers in Chile, including residential, commercial, and industrial demand. We leverage data from 230 thousand smart meters of residential and commercial consumers in 32 communes of Santiago (the capital city of Chile), which allows us to investigate the evolution of their demands with an hourly temporal resolution. Additionally, we use demand data of large industrial consumers provided by the Chilean system operator to study the impact of the pandemic on different economic sectors. This paper demonstrates that the COVID-19 pandemic, and the associated containment measures, have featured a drastically different impact on the various types of consumers in Chile. In particular, we show that the demand of residential consumers has increased throughout the first wave, even when we isolate the effects of the pandemic from those related to weather. Furthermore, we study how these effects change in different communes of Santiago, contrasting our findings with the socio-economic levels of the population. In effect, we find different demand response patterns depending on the socio-economic background of consumers. We also show that commercial demand has significantly declined due to the containment measures implemented and that the hospitality and construction economic sectors have been the most affected in the country.

Abstract: ince the detection of the first case of COVID-19 in Chile on March 3(rd), 2020, a total of 513,188 cases, including similar to 14,302 deaths have been reported in Chile as of November 2(nd), 2020. Here, we estimate the reproduction number throughout the epidemic in Chile and study the effectiveness of control interventions especially the effectiveness of lockdowns by conducting short-term forecasts based on the early transmission dynamics of COVID-19. Chile's incidence curve displays early sub-exponential growth dynamics with the deceleration of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number, R, estimated at 1.8 (95% CI: 1.6, 1.9). Our findings indicate that the control measures at the start of the epidemic significantly slowed down the spread of the virus. However, the relaxation of restrictions and spread of the virus in low-income neighborhoods in May led to a new surge of infections, followed by the reimposition of lockdowns in Greater Santiago and other municipalities. These measures have decelerated the virus spread with R estimated at similar to 0.96 (95% CI: 0.95, 0.98) as of November 2(nd), 2020. The early sub-exponential growth trend (p similar to 0.8) of the COVID-19 epidemic transformed into a linear growth trend (p similar to 0.5) as of July 7(th), 2020, after the reimposition of lockdowns. While the broad scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing and active case detection and isolation efforts to maintain the epidemic under control.
Author summary
In context of the ongoing COVID-19 pandemic, Chile has been one of the hardest-hit countries in Latin America, struggling to contain the spread of the virus. In this manuscript, we employ renewal equation to estimate the reproduction number (R) for the early ascending phase of the COVID-19 epidemic and by July 7(th), 2020 to guide the magnitude and intensity of interventions required to combat the COVID-19 epidemic. We also estimate the instantaneous reproduction number throughout the epidemic in Chile. Moreover, we generate short-term forecasts based on the epidemic trajectory using phenomenological models, and assess counterfactual scenarios to understand any additional resources required to contain the virus' spread. Our results indicate early sustained transmission of SARS-CoV-2. However, the initial control measures at the start of the epidemic significantly slowed down the spread of the virus. The easing of COVID-19 restrictions in April led to a new wave of infections, followed by the re-imposition of lockdowns in Greater Santiago and several municipalities. Most recent estimates of reproduction number indicate a decline in the virus transmission. While broad-scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing efforts.