The outbreak of the COVID-19 disease, spreading all around the world and causing a worldwide pandemic, has lead to the collapse of the health systems of the most affected countries. Due to the ease of transmission, early prevention measures are proved to be fundamental to control the pandemic and, hence, the saturation of the health systems. Given the difficulty of obtaining characteristics of these systems of different countries and regions, it is necessary to define indicators based on basic information that enable the assessment of the evolution of the impact of a disease in a health system along with fair comparisons among different ones. This present paper introduces the Health Sufficiency Indicator ($HSI$), in its accumulated and daily versions. This indicator measures the additional pressure that a health care system has to deal with due to a pandemic. Hence, it allows to evaluate the capacity of a health system to give response to the corresponding needs arising from a pandemic and to compare the evolution of the disease among different regions. In addition, the Potential Occupancy Ratio ($POR$) in both its hospital ward bed and ICU bed versions is here introduced to asses the impact of the pandemic in the capacity of hospitals. These indicators and other well-known ones are applied to track the evolution of the impact of the disease on the Spanish health system during the first wave of the pandemic, both on national and regional levels. An international comparison among the most affected countries is also performed.

La COVID 19 es una enfermedad infecciosa, altamente contagiosa, que se propaga por contacto o cercanía cuando una persona infectada tose o estornuda. Según los estudios actuales la letalidad no es alta, pero a causa de la facilidad de contagio, esta enfermedad ha provocado un estado mundial de pandemia. Debido a ello, se ha originado el colapso de los sistemas sanitarios de todos los países afectados. Dada la dificultad de obtener las características de los sistemas sanitarios de los distintos países, urge obtener indicadores capaces de comparar el estado de estos sistemas y evaluar su evolución, en función de la incidencia y morbilidad de la enfermedad. En este trabajo, se presenta el Indicador de Suficiencia Sanitaria (ISS) que permite evaluar la capacidad que tiene un sistema de salud para responder a las necesidades derivadas de una pandemia. Este indicador es útil para comparar el desarrollo de la enfermedad entre los distintos países con los datos disponibles. Además, se analizan otros indicadores habituales relativos al número de casos, número de fallecidos y número de altas en el sistema de salud. Finalmente, se construyen modelos de aprendizaje máquina para la predicción del ISS y estimar el desarrollo de la enfermedad y su impacto en el sistema sanitario en España, tanto a nivel nacional como a nivel regional.

The rapid spread of biased information and disinformation has intensified in recent times due to the increased reliance on the Internet and social media platforms as primary sources of information. This issue is of particular concern in the fields of medicine and healthcare, given the critical nature of decisions and understandings in these areas. While medical experts can mitigate the repercussions of misinformation by evaluating questionable websites, this approach is time-consuming. Consequently, there is a pressing need to develop software solutions that can automate the detection of misleading information. This paper presents CO-training and Active Learning-based framework for Finding Low-credibility web Addresses in the MEdical field (COAL4FLAME) , a novel system designed to analyze health-related websites and identify misinformation. The system integrates results from multiple estimators to reach a comprehensive conclusion. COAL4FLAME uses semi-supervised learning strategies, such as multi-view learning, co-training, and active learning, to address the challenge of limited labeled data, a major strength of the presented proposal. Medical experts have rigorously tested and evaluated the system using a selected set of websites.