Known as an artificial intelligence subarea, Swarm Robotics is a developing study field investigating bio-inspired collaborative control approaches and integrates a huge collection of agents, reasonably plain robots, in a distributed and decentralized manner. It offers an inspiring essential platform for new researchers to be engaged and share new knowledge to examine their concepts in analytical and heuristic strategies. This paper introduces an overview of current activities in Swarm Robotics and examines the present literature in this area to establish to approach between a realistic swarm robotic system and real-world enforcements. First, we review several Swarm Intelligence concepts to define Swarm Robotics systems, reporting their essential qualities and features and contrast them to generic multi-robotic systems. Second, we report a review of the principal projects that allow realistic study of Swarm Robotics. We demonstrate knowledge regarding current hardware platforms and multi-robot simulators. Finally, the forthcoming promissory applications and the troubles to surpass with a view to achieving them have been described and analyzed.

The pandemic caused by the Coronavirus 19 (Coronavirus disease 2019, COVID-19) killed countless people in 2020 and it arrived in Brazil in mid-February from the same year. It spread quickly, through its facilitated form of transmission by droplets of saliva, coughing, sneezing and contaminated surfaces. Several studies have indicated that male people over 60 years of age with comorbidities such as diabetes mellitus, chronic kidney disease, cardiovascular disease and/ or chronic lung diseases had higher rates of progression to Severe Acute Respiratory Syndrome and greater vulnerability to death. In this sense, this study aimed to describe the clinical and epidemiological profile from suspected and confirmed cases of COVID-19 in a hospital in the city of Anápolis, in the State of Goiás, Brazil, from March to December 2020. A total of 1,170 patients were included in this study, with 54.8% of the patients admitted with symptoms of COVID-19 were women (46.9%) aged between 30 and 59 years old. In addition, it was noted that 11.5% of these patients had some type of comorbidities. Furthermore, the data revealed that 82.2% of the laboratory-confirmed patients who died had comorbidities, most of them men (57%), and from the total of 68.5% had two or more comorbidities, with cardiovascular origin being the most frequent reaching 77.5% from the sample. Thus, it was concluded that the clinical-epidemiological profile of suspected and confirmed patients for COVID-19 in this research was characterized by the majority of female patients between 30 and 49 years of age, although most confirmed cases and deaths occurred in men older than 60 years of age. Most confirmed patients had two or more comorbidities, most of them of cardiovascular origin, followed by metabolic syndromes, lung diseases and others. KEY WORDS: COVID-19; epidemiology; comorbidity.