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ObjectivesThis study investigated the impact of the COVID-19 pandemic on the primary health care (PHC) services to follow-up the child growth and development (CGD) in Brazil.MethodsA cross-sectional study was conducted using secondary data related visits to assess the growth and development of children up to five years between Apr-2017 to Mar-2021. Differences between monthly rate of visits (per thousand inhabitants up to five) during the pandemic (Apr-2020 to Mar-2021) and before (Apr-2017 to Mar-2020) were analyzed using paired t test and control diagrams (averages ± 1.96 standard deviation).ResultsA total of 39,599,313 visits for monitoring CGD was studied. The average monthly rate of visits dropped from 61.34 (per thousand) before the pandemic to 39.70 in the first 12 months of the pandemic (p < 0.001). In all states, except Rio Grande do Sul, there was a significant reduction, with differences ranging from −14.21% in São Paulo to −59.66% in Ceará. The Northeast region was the most impacted, being lower than expected in all 12 first months of pandemic.ConclusionsThe number of visits to follow-up the CGD in PHC in Brazil decreased during the first year of the COVID-19 pandemic, varying over the months and between states and regions.

The increasing concerns about fossil fuel sources have generated growth in investment in renewable sources. The slow pyrolysis of lignocellulosic materials has become favourable because to producing energy and is capable of supplying products with high added value. Accordingly, through the application of artificial neural networks, this study evaluated the kinetics of the slow pyrolysis of the powder obtained from the fruit peel of Pachira aquatica Aubl. in natural and chemical modified form to determine the kinetic parameters using the Friedman, Kissinger and Ozawa isoconversion methods and introduction of Fraser-Suzuki deconvolution method to obtain the individual kinetic parameters for the pseudo-cellulose component. The results allowed the conclusion that the applied neural network was efficient in the prediction of the thermal data, obtaining similar thermogravimetric profiles to experimental ones and high determination values. The Friedman method was the best fit for the data, and the activation energies showed that the samples submitted to chemical treatment obtained lower activation energy, due to the modification of the components of the lignocellulosic matrix.