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As the main methods of the coronavirus disease (COVID-19) transmission are air and physical contact, actions to mitigate and suppress its spread must be developed in order to change population dynamics and provide efficient control strategies. Here, these actions are described as a simple heuristic framework to establish public policies. Two control systems were studied: the first organized in the form of an algorithm stratified into three levels and the second as a minimization problem similar to optimal control strategies, applied to both social distancing and vaccination. The possible effects of these actions are modeled and applied to an extension of the Susceptible - Infected - Removed (SIR) compartmental model. The control system is developed, which is organized in the form of an algorithm stratified into three levels. These levels intend to represent social distancing strategies implemented by sanitary authorities around the globe, representing stronger or weaker grades of isolation intensity according to the ability of the healthcare system to cope with symptomatic individuals. The algorithm control is applied in a simulation, and the results give evidence of the effectiveness of the procedures adopted against the coronavirus. The model dynamics are analyzed and validated with simulations considering parameters obtained from epidemiological data from Brazil and Uruguay and in a more detailed way for three Brazilian states: São Paulo, Minas Gerais and Rio de Janeiro. The model was validated using cumulative data on cases and deaths. For cases of death, the results were satisfactory, while for case data, the response was reasonable, considering the possibility of adding delays or variations in parameters in the model. In addition, the effective reproduction number was proposed for the cities studied in Brazil, the result being relevant because it has a qualitative behavior similar to that published by official centers. This paper also discusses the implementation and optimization of social distancing and vaccination control strategies, considering different parameters and their effects on reducing the number of cases and deaths. Model simulations present promising results for developing strategies to attack COVID-19 dissemination. [ABSTRACT FROM AUTHOR]

Since the onset of the coronavirus disease, COVID-19 pandemic, concern arose for those who might be at higher risk of a worse COVID-19 prognosis, such as those with cystic fibrosis (CF). In this context, we evaluated the features of hospitalized patients with CF due to severe acute respiratory infection (SARI) in Brazil and we also performed a systematic review including all the studies published from the beginning of the first case of COVID-19 (17 November 2019) to the date of this search (23 May 2022) which included, concomitantly, patients with CF and COVID-19 in the worldwide population. In our Brazilian data, we evaluated the period from December 2019 to March 2022, and we included 33 demographical and clinical patients' features. We classified the patients into groups: (G1) SARI due to another viral infection than severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (23; 5.4%), (G2) SARI due to an unknown etiological agent (286; 67.1%), and (G3) SARI due to SARS-CoV-2 infection (117; 27.5%). The individuals in G3 tended to be older, especially over 50 years old, and presented a higher prevalence of dyspnea, peripheral capillary oxygen saturation (SpO2) <95%, and cardiopathy. The highest prevalence for intensive care unit (ICU) treatment (52; 44.4%) and invasive mechanical ventilation (29; 24.8%) was for patients in G3. Almost half of the patients in G3 died (51; 43.6%); in contrast, none in G1 died. However, we observed 43 (15.0%) deaths in G2. In addition, 12 (4.2%) and one (0.9%) death not associated with SARI occurred, respectively, in the G2 and G3. The patients who died due to SARS-CoV-2 infection had a higher frequency of SpO2 <95% (46; 90.2%), ICU treatment (34; 66.7%), and invasive mechanical ventilation (27; 52.9%) when compared to those who recovered. The systematic review comprised a total of 31 papers published as observational studies. These studies comprised 661,386 patients in total, including children, adults, and elderly age groups. However, only 19,150 (2.9%) patients were diagnosed with CF and, from these patients, 2523 (0.4%) were diagnosed with both CF and COVID-19. It was observed that the most common outcome was the need for hospitalization (n = 322 patients with CF), and the need for oxygen support (n = 139 patients with CF). One hundred patients with CF needed intensive care units, fifty patients needed non-invasive mechanical ventilation support, and only three patients were described as receiving invasive mechanical ventilation support. Deaths were described in 38 patients with CF. Importantly, lung-transplanted patients with CF represented an increased risk of death in one publication; in accordance, another study described that lung transplantation and moderate to severe lung disease were independent risk factors for severe outcomes after SARS-CoV-2 infection. In contrast with the literature, in conclusion, Brazilian patients in G3 presented a severe phenotype, even though most of the other studies did not observe worse outcomes in patients with CF and COVID-19. [ABSTRACT FROM AUTHOR]