Effects of meteo-oceanographic conditions on the weathering processes of oil spills in northeastern Brazil.

This paper presents the graphical results of the Lagrangian-model and the weathering processes associated with oil spills in the tropical South Atlantic, taking into account the meteorological and oceanographic conditions of the study region. The scenarios were created in the Brazilian-NE waters adjacent, with simulation times of 670 h, and densities of 35, 25, and 15API with volume of 1590 m were considered. The main results showed that the meteo-oceanographic characteristics of the study region influence the trajectories and weathering processes in the oil spill.

Quantitative ecological risk assessment of oil spills: The case of the Fernando de Noronha Archipelago.

The upward trend in maritime oil transport increases the risk of oil spills, which have the potential to cause considerable damage to the marine environment. Therefore, a formal approach to quantify such risks is required. In mid-2010, a conservative Quantitative Ecological Risk Assessment based on population modeling, was performed in the Fernando de Noronha Archipelago.

Risk-based cost-benefit analysis of alternative vaccines against COVID-19 in Brazil: Coronavac vs. Astrazeneca vs. Pfizer.

We propose a probabilistic model to quantify the cost-benefit of mass Vaccination Scenarios (VSs) against COVID-19. Through this approach, we conduct a six-month simulation, from August 31st, 2021 to March 3rd, 2022, of nine VSs, i.e.

A probabilistic epidemiological model for infectious diseases: The case of COVID-19 at global-level.

This study has developed a probabilistic epidemiological model a few weeks after the World Health Organization declared COVID-19 a pandemic (based on the little data available at that time). The aim was to assess relative risks for future scenarios and evaluate the effectiveness of different management actions for 1 year ahead. We quantified, categorized, and ranked the risks for scenarios such as business as usual, and moderate and strong mitigation.

Combining Generalized Renewal Processes with Non-Extensive Entropy-Based q-Distributions for Reliability Applications.

The Generalized Renewal Process (GRP) is a probabilistic model for repairable systems that can represent the usual states of a system after a repair: as new, as old, or in a condition between new and old. It is often coupled with the Weibull distribution, widely used in the reliability context. In this paper, we develop novel GRP models based on probability distributions that stem from the Tsallis' non-extensive entropy, namely the q-Exponential and the q-Weibull distributions.

Embedding resilience in the design of the electricity supply for industrial clients.

This paper proposes an optimization model, using Mixed-Integer Linear Programming (MILP), to support decisions related to making investments in the design of power grids serving industrial clients that experience interruptions to their energy supply due to disruptive events. In this approach, by considering the probabilities of the occurrence of a set of such disruptive events, the model is used to minimize the overall expected cost by determining an optimal strategy involving pre- and post-event actions. The pre-event actions, which are considered during the design phase, evaluate the resilience capacity (absorption, adaptation and restoration) and are tailored to the context of industrial clients dependent on a power grid.

An ecological model for quantitative risk assessment for schistosomiasis: the case of a patchy environment in the coastal tropical area of northeastern Brazil.

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case-specific features: stage-structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site-specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics.