A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil.

We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.

Physical exercise increases global and gene-specific (interleukin-17 and interferon-γ) DNA methylation in lymphocytes from aged women.

NEW FINDINGS: What is the central question of this study? Is lymphocyte DNA methylation differentially modulated by resistance training and aerobic exercise in older women? What is the main finding and its importance? The practice of resistance training led to an increased global DNA methylation in lymphocytes. The exercise-induced increase of inflammatory genes methylation may be associated with immune function impairment during ageing. ABSTRACT: Ageing-induced increase in inflammatory gene expression through a reduction in DNA methylation might contribute to chronic diseases. Regular physical exercise practices, in turn, are associated with a decrease in the incidence of inflammatory diseases. We herein evaluated the effects of three exercise modalities on lymphocyte global and gene-specific (interferon γ (IFN-γ) and interleukin 17A (IL-17A) DNA methylation in aged women (68 ± 7.5 years). This cross-sectional study included 86 women, divided into four groups according to the physical exercise practice: 20 were practicing resistance training (RT); 24 were practicing water aerobics exercise (W); 22 were practicing water aerobics and resistance exercise (RWT), and 20 did not practice any physical exercise (CON). We evaluated volunteer functional capability using the Timed Up and Go (TUG) test, global lymphocyte DNA methylation by enzyme-linked immunosorbent assay, IFN-γ and IL-17A methylation by qPCR and CD4+ IFN-γ+ and CD4+ IL-17+ cell percentage by flow cytometry. The three physically exercised groups performed functional capability tests in a shorter period and showed a higher global lymphocyte DNA methylation and methylated CpGs of IL-17A and IFN-γ promoter regions than the control group. The practice of resistance training (RT and RWT groups) lead to high global DNA methylation. The combination of resistance training and aerobic exercise led to the increase of lymphocyte IL-17A and IFN-γ gene methylation induced by each separately. However, the percentage of IFN-γ+ and IL-17+ cells was lower only in the RT group. The exercise-induced increase of inflammatory-gene methylation may be associated with gene expression changes and immune function impairment during ageing.

A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil

We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.