ABSTRACT
Technology brought several advancements to the Educational area in the past few years, including digital resources such as Open Educational Resources (OER). However, higher demand associated with the lack of platforms that facilitate the search and sharing of these resources is an impeditive factor, often causing the devaluation and loss of these materials. This article presents ReaCloud, a digital repository designed to index OERs, improve the usability of adding OERs, and aligned with Brazilian standards for k-12 education. © 2021 IEEE.
ABSTRACT
The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management.
ABSTRACT
The objective of this article is to present a computational estimate from a statistical physics approach and its contributions to Covid-19 in Colombia. Based on the daily data of contagions, recoveries and deaths, during the months of March to July, the estimation of the behavior of the epidemic was made using the nonlinear regression method with adjustment of curves by minimum squares. Highlighting the benefits that this method presents in the study of physical phenomena, it was used in the present research developing two types of modeling: exponential and Gaussian, and with these some predictions were made. The coefficients of determination of the exponential model were: 0.9641 for contagions, 0.9400 for recoveries and 0.9788 for deaths, and those of the Gaussian model were: 0.9799 for contagions, 0.9606 for recoveries and 0.9894 for deaths, showing a good correlation between the models and the real behavior of the pandemic, being the Gaussian one, the most approximate. This was also evidenced by comparing the prognosis of both models with the actual data for the first 13 days of August, concluding that the pandemic is beginning to mitigate, and the curve is flattening out. © 2020 Published under licence by IOP Publishing Ltd.