Immunosenescence, Immune Fitness and Vaccination Schedule in the Adult Respiratory Patient Inmunosenescencia, fitness inmunológico y calendario de vacunación en el paciente respiratorio adulto

Immunosenescence is the gradual deterioration of the immune system caused by advancing age. It is associated with a reduced ability to respond to infections and develop long-term immune memory. It plays a key role in the development of respiratory diseases that are more common in older people, such as asthma, COPD, diffuse interstitial disease and respiratory infections in the elderly. We call immune fitness the establishment of lifestyle habits that can improve our immune capacity. We now know that good eating habits, good social relationships, not smoking, limiting alcohol consumption, exercising, controlling stress levels and establishing a proper vaccination programme can slow down the process of immunosenescence. Influenza and pneumococcal vaccines (PCV13 and PPSV23 conjugate) are well established in the adult vaccination schedule. The new pneumococcal vaccines PCV15 and PCV20 will help to extend protection against pneumococcal disease in adults. The vaccine against COVID-19 is currently the most useful tool to prevent the disease and reduce its pathogenicity. COPD patients and others with respiratory diseases may benefit from prevention of herpes zoster and Bordetella pertussis through vaccination. Respiratory syncytial virus (RSV) vaccine may be another vaccine to be added to the schedule, pending the results of its studies.

Immunosenescence, immune fitness and vaccination schedule in the adult respiratory patient

Immunosenescence is the gradual deterioration of the immune system caused by advancing age. It is associated with a reduced ability to respond to infections and develop long-term immune memory. It plays a key role in the development of respiratory diseases that are more common in older people, such as asthma, COPD, diffuse interstitial disease and respiratory infections in the elderly. We call immune fitness the establishment of lifestyle habits that can improve our immune capacity. We now know that good eating habits, good social relationships, not smoking, limiting alcohol consumption, exercising, controlling stress levels and establishing a proper vaccination programme can slow down the process of immunosenescence. Influenza and pneumococcal vaccines (PCV13 and PPSV23 conjugate) are well established in the adult vaccination schedule. The new pneumococcal vaccines PCV15 and PCV20 will help to extend protection against pneumococcal disease in adults. The vaccine against COVID-19 is currently the most useful tool to prevent the disease and reduce its pathogenicity. COPD patients and others with respiratory diseases may benefit from prevention of herpes zoster and Bordetella pertussis through vaccination. RSV vaccine may be another vaccine to be added to the schedule, pending the results of its studies. Resumen La inmunosenescencia es el deterioro gradual del sistema inmune provocado por el avance de la edad. Se asocia a una menor capacidad para responder a las infecciones y desarrollar memoria inmune a largo plazo. Es parte fundamental en el desarrollo de aquellas enfermedades respiratorias que son más frecuentes en edades avanzadas, como son el asma, la EPOC, la patología intersticial difusa y las infecciones respiratorias del anciano. Llamamos fitness inmunológico al establecimiento de unos hábitos de vida que puedan mejorar nuestra capacidad inmunitaria. Actualmente sabemos que tener buenos hábitos alimenticios, buenas relaciones sociales, no fumar, limitar el consumo de alcohol, hacer ejercicio, controlar los niveles de estrés y establecer un correcto programa de vacunación permiten ralentizar el proceso de inmunosenescencia. Las vacunas de la gripe, las antineumocócicas (la conjugada PCV13 y la PPSV23) están bien establecidas en el calendario vacunal del adulto.  Las nuevas vacunas antineumocócicas PCV15 y PCV20 van a servir para ampliar la protección contra la enfermedad neumocócica en el adulto. La vacuna contra la COVID-19 es, en el momento actual, la herramienta más útil para prevenir la enfermedad y disminuir su patogenicidad.  Los pacientes con EPOC y otros con enfermedades respiratorias podrían beneficiarse de la prevención del herpes zoster y Bordetella Pertussis mediante la vacunación. La vacuna contra el VRS puede ser otra de las siguientes que formen parte de este calendario, en espera de los resultados de sus estudios.

A predictive model for hospitalization and survival to COVID-19 in a retrospective population-based study (preprint)

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) is highly transmissible and has been responsible for a pandemic associated with a high number of deaths. The clinical management of patients and the optimal use of resources are two important factors in reducing this mortality, especially in scenarios of high incidence. To this end, it is necessary to develop tools that allow early triage of patients with the minimal use of diagnostic tests and based on readily accessible data, such as electronic medical records. This work proposes the use of a machine learning model that allows the prediction of mortality and risk of hospitalization using simple demographic characteristics and comorbidities, using a COVID-19 dataset of 86867 patients. In addition, we developed a new method designed to deal with data imbalance problems. The model was able to predict with high accuracy (89-93%, ROC-AUC = 0.94) the patient's final status (expired/discharged) and with medium accuracy the risk of hospitalization (71-73%, ROC-AUC = 0.75). These models were obtained by assembling and using easily obtainable clinical characteristics (2 demographic characteristics and 19 predictors of comorbidities). The most relevant features of these models were the following patient characteristics: age, sex, number of comorbidities, osteoarthritis, obesity, depression, and renal failure.

A Deep Q-learning/genetic Algorithms Based Novel Methodology For Optimizing Covid-19 Pandemic Government Actions (preprint)

Whenever countries are threatened by a pandemic, as is the case with the COVID-19 virus, governments should take the right actions to safeguard public health as well as to mitigate the negative effects on the economy. In this regard, there are two completely different approaches governments can take: a restrictive one, in which drastic measures such as self-isolation can seriously damage the economy, and a more liberal one, where more relaxed restrictions may put at risk a high percentage of the population. The optimal approach could be somewhere in between, and, in order to make the right decisions, it is necessary to accurately estimate the future effects of taking one or other measures. In this paper, we use the SEIR epidemiological model (Susceptible - Exposed - Infected - Recovered) for infectious diseases to represent the evolution of the virus COVID-19 over time in the population. To optimize the best sequences of actions governments can take, we propose a methodology with two approaches, one based on Deep Q-Learning and another one based on Genetic Algorithms. The sequences of actions (confinement, self-isolation, two-meter distance or not taking restrictions) are evaluated according to a reward system focused on meeting two objectives: firstly, getting few people infected so that hospitals are not overwhelmed with critical patients, and secondly, avoiding taking drastic measures for too long which can potentially cause serious damage to the economy. The conducted experiments prove that our methodology is a valid tool to discover actions governments can take to reduce the negative effects of a pandemic in both senses. We also prove that the approach based on Deep Q-Learning overcomes the one based on Genetic Algorithms for optimizing the sequences of actions.