COVID-19 dynamics in Madrid (Spain): A new convolutional model to find out the missing information during the first three waves.

This article presents a novel mathematical model to describe the spread of an infectious disease in the presence of social and health events: it uses 15 compartments, 7 convolution integrals and 4 types of infected individuals, asymptomatic, mild, moderate and severe. A unique feature of this work is that the convolutions and the compartments have been selected to maximize the number of independent input parameters, leading to a 56-parameter model where only one had to evolve over time. The results show that 1) the proposed mathematical model is flexible and robust enough to describe the complex dynamic of the pandemic during the first three waves of the COVID-19 spread in the region of Madrid (Spain) and 2) the proposed model allows us to calculate the number of asymptomatic individuals and the number of persons who presented antibodies during the first waves. The study shows that the following results are compatible with the reported data: close to 28% of the infected individuals were asymptomatic during the three waves, close to 29% of asymptomatic individuals were detected during the subsequent waves and close to 26% of the Madrid population had antibodies at the end of the third wave. This calculated number of persons with antibodies is in great agreement with four direct measurements obtained from an independent sero-epidemiological research. In addition, six calculated curves (total number of confirmed cases, asymptomatic who are confirmed as positive, hospital admissions and discharges and intensive care units admissions) show good agreement with data from an epidemiological surveillance database.

Childhood obesity and risk of SARS-CoV-2 infection.

OBJECTIVE: To estimate the association between childhood obesity and the risk of SARS-CoV-2 infection in a cohort followed from 4 to 12 years of age. METHODS: The data were obtained from two independent sources: the Longitudinal Childhood Obesity Study (ELOIN) and the epidemiological surveillance system data from the Community of Madrid (Spain), which served to identify the population within the cohort with confirmed SARS-CoV-2 infection. The SARS-CoV-2 registry was cross-checked with the cohort population at 11-12 years of age. A total of 2018 eligible participants were identified in the cohort, who underwent physical examinations at 4, 6, and 9 years of age during which weight, height, and waist circumference were recorded. General obesity (GO) was determined according to the WHO-2007 criteria whereas abdominal obesity (AO) was defined based on the International Diabetes Federation (IDF) criteria. The relative risks (RRs) of infection were estimated using a Poisson regression model and adjusted by sociodemographic variables, physical activity, and perceived health reported by the parents. RESULTS: The accumulated incidence of SARS-CoV-2 infection was 8.6% (95% CI: 7.3-9.8). The estimated RR of SARS-CoV-2 infection was 2.53 (95% CI: 1.56-4.10) and 2.56 (95% CI: 1.55-4.21) for children 4-9 years old with stable GO and AO, respectively, compared with those who did not present GO. CONCLUSIONS: Childhood obesity is an independent risk factor for SARS-CoV-2 infection. This study provides new evidence that indicates that obesity increases the vulnerability of the paediatric population to infectious diseases.

[Descriptive analysis of medication errors notified by Primary Health Care: Learning from errors]. / Análisis descriptivo de los errores de medicación notificados en atención primaria: aprendiendo de nuestros errores.

INTRODUCTION AND OBJECTIVES: Aim of this study is to determine the setting, causes, and the harm of medication errors (ME) which are notified by Primary Health Care. MATERIAL AND METHODS: Setting: Primary Care Regional Health Service of Madrid. 2016. DESIGN: Descriptive and cross-sectional study. PARTICIPANTS: All ME (1,839) which were notified by Primary Care Centres by notification system of safety incidents between January 1st 2016 and November 17th 2016. MAIN MEASUREMENTS: Setting, real harm, potential harm, and cause of error. These items were classified by one researcher. Concordance was checked with another researcher. RESULTS: Just under half (47%) (95% CI: 44.8%-49.3%) of ME occurred in Primary Care Centre, 26.5% (95% CI: 24.5%-28.6%) of ME were patient medication errors, and 27.5% (95% CI: 24.1%-30.8%) of ME were potential severe harm errors. Prescribing errors were the cause of most ME in Primary Care Centre [27.4% (95% CI: 24.4%-30.4%)]. Communication between patients and doctors were the cause of most patient medication errors [66% (95% CI: 61.8%-70.2%)]. Patient mistakes and forgetfulness were also causes of patient medication errors. CONCLUSIONS: Half of all mediation errors hppened at Primary Care Center while one quarter of them were patient medication errors. One quarter of all ME were potential severe harm errors. The main causes were prescribing errors, failure of communication between patients and doctors, and patient mistakes and forgetfulness. Prescribing aid systems, communication improvements and patients aids should be implemented.