RESUMO
This data article provides raw log files captured from automated computational experiments with an application integration platform that implements the task-based execution model. The code of a well-known enterprise application integration process was modified to record these data while running the experiments. The dataset described in this article is related to the research article entitled "On the Analysis of Makespan and Performance of the Task-based Execution Model for Enterprise Application Integration Platforms: an Empirical Study" of Frantz et al. (2021). The dataset contains two types of CSV files in text format presenting: (1) data of makespan related to experiment executions and (2) data regarding the number of messages and work-units processed during each experiment. Scientific community who works on workflow and integration process execution can benefit from these data to analyse and understand the behaviour of the task-based execution model, obtain insights to improve this model, as well as perform comparisons with other types of execution models or platforms.
RESUMO
The coronavirus disease that emerged in 2019 (COVID-19) is highly contagious and has given way to a global pandemic. A present COVID-19 has high transmission rates worldwide, including in small Brazilian cities such as Ijuí. Located in the northwest part of the state of Rio Grande do Sul (RS) and with a population of 83,475, Ijuí was selected as the site of a population-based survey involving 2,222 subjects, from April to June 2020. Subjects were tested for the presence of antibodies against coronavirus (SARS-CoV-2) and answered questions regarding social distance adherence (SDA), daily preventive routines (DPR), comorbidities, and sociodemographic characteristics. In parallel, the local government registered the official COVID-19 cases in Ijuí, as well as the mobile social distancing index (MSDI). In this study, we demonstrate that there was a decrease in the levels of SDA, DPR and MSDI before the beginning of COVID-19 community transmission in Ijuí. Furthermore, we provide predictions for the number of COVID-19 cases, hospitalizations, and deaths in the city. We conclude that insufficient social distancing, as evidenced by different methods, may be related to the rapid increase of COVID-19 cases in Ijuí. Our study predicts an approaching outbreak of COVID-19 in Ijuí through community spread, which could be avoided or attenuated with increased levels of social distancing among the population.