We developed an agent-based stochastic model, based on P Systems methodology, to decipher the effects of vaccination and contact tracing on the control of COVID-19 outbreak at population level under different control measures (social distancing, mask wearing and hand hygiene) and epidemiological scenarios. Our findings suggest that without the application of protection social measures, 56.1% of the Spanish population would contract the disease with a mortality of 0.4%. Assuming that 20% of the population was protected by vaccination by the end of the summer of 2021, it would be expected that 45% of the population would contract the disease and 0.3% of the population would die. However, both of these percentages are significantly lower when social measures were adopted, being the best results when social measures are in place and 40% of contacts traced. Our model shows that if 40% of the population can be vaccinated, even without social control measures, the percentage of people who die or recover from infection would fall from 0.41% and 56.1% to 0.16% and 33.5%, respectively compared with an unvaccinated population. When social control measures were applied in concert with vaccination the percentage of people who die or recover from infection diminishes until 0.10% and 14.5%, after vaccinating 40% of the population. Vaccination alone can be crucial in controlling this disease, but it is necessary to vaccinate a significant part of the population and to back this up with social control measures.
Aims: To identify principal components of free-living patterns of sedentary behaviour in office employees with type 2 diabetes (T2D) compared to normal glucose metabolism (NGM) office employees, using principal component analysis (PCA). Methods: 213 office employees (n = 81 with T2D; n = 132 with NGM) wore an activPAL inclinometer 24 h a day for 7 consecutive days. Comparions of sedentary behaviour patterns between adults with T2D and NGM determined the dimensions that best characterise the sedentary behaviour patterns of office employees with T2D at work, outside work and at weekends. Results: The multivariate PCA technique identified two components that explained 60% of the variability present in the data of sedentary behaviour patterns in the population with diabetes. This was characterised by a fewer number of daily breaks and breaks in time intervals of less than 20 min both at work, outside work and at weekends. On average, adults with T2D took fewer 31 breaks/day than adults without diabetes. Conclusion: Effective interventions from clinical practice to tackle prolonged sedentary behaviour in office employees with T2D should focus on increasing the number of daily sedentary breaks.
Background Prolonged sedentary time is associated with an increased incidence of chronic disease including type 2 diabetes mellitus (DM2). Given that occupational sedentary time contributes significantly to the total amount of daily sedentariness, incorporating programmes to reduce occupational sedentary time in patients with chronic disease would allow for physical, mental and productivity benefits. The aim of this study is to evaluate the short-, medium- and long-term effectiveness of a mHealth programme for sitting less and moving more at work on habitual and occupational sedentary behaviour and physical activity in office staff with DM2. Secondary aims. To evaluate the effectiveness on glycaemic control and lipid profile at 6- and 12-month follow-up; anthropometric profile, blood pressure, mental well-being and work-related post-intervention outcomes at 3, 6 and 12 months. Methods Multicentre randomized controlled trial. A sample size of 220 patients will be randomly allocated into a control (n = 110) or intervention group (n = 110), with post-intervention follow-ups at 6 and 12 months. Health professionals from Spanish Primary Health Care units will randomly invite patients (18–65 years of age) diagnosed with DM2, who have sedentary office desk-based jobs. The control group will receive usual healthcare and information on the health benefits of sitting less and moving more. The intervention group will receive, through a smartphone app and website, strategies and real-time feedback for 13 weeks to change occupational sedentary behaviour. Variables: (1) Subjective and objective habitual and occupational sedentary behaviour and physical activity (Workforce Sitting Questionnaire, Brief Physical Activity Assessment Tool, activPAL3TM); 2) Glucose, HbA1c; 3) Weight, height, waist circumference; 4) Total, HDL and LDL cholesterol, triglycerides; (5) Systolic, diastolic blood pressure; (6) Mental well-being (Warwick-Edinburgh Mental Well-being); (7) Presenteeism (Work Limitations Questionnaire); (8) Impact of work on employees´ health, sickness absence (6th European Working Conditions Survey); (9) Job-related mental strain (Job Content Questionnaire). Differences between groups pre- and post- intervention on the average value of the variables will be analysed. Discussion If the mHealth intervention is effective in reducing sedentary time and increasing physical activity in office employees with DM2, health professionals would have a low-cost tool for the control of patients with chronic disease. Trial Registration ClinicalTrials.gov NCT04092738. Registered September 17, 2019.
recover, but also the number of people who die from infection, which falls from 0.41% of the population over a 130 day period without protective measures to 0.15, 0.08 and 0.06% if 25, 50 and 75% of the population had been vaccinated in combination with protective measures at the same time, respectively.
The concurrent timing of the COVID-19 pandemic and the seasonal occurrence of influenza, makes it especially important to analyze the possible effect of the influenza vaccine on the risk of contracting COVID-19, or in reducing the complications caused by both diseases, especially in vulnerable populations. There is very little scientific information on the possible protective role of the influenza vaccine against the risk of contracting COVID-19, particularly in groups at high-risk of influenza complications. Reducing the risk of contracting COVID-19 in high-risk patients (those with a higher risk of infection, complications, and death) is essential to improve public well-being and to reduce hospital pressure and the collapse of primary health centers. Apart from overlapping in time, COVID-19 and flu share common aspects of transmission, so that measures to protect against flu might be effective in reducing the risk of contracting COVID-19. In this study, we conclude that the risk of contracting COVID-19 is reduced if patients are vaccinated against flu, but the reduction is small (0.22%) and therefore not clinically important. When this reduction is analysed based on the risk factor suffered by the patient, statistically significant differences have been obtained for patients with cardiovascular problems, diabetics, chronic lung and chronic kidney disease; in all four cases the reduction in the risk of contagion does not reach 1%. It is worth highlighting the behaviour that is completely different from the rest of the data for institutionalized patients. The data for these patients does not suggest a reduction in the risk of contagion for patients vaccinated against the flu, but rather the opposite, a significant increase of 6%. Socioeconomic conditions, as measured by the MEDEA deprivation index, explain increases in the risk of contracting COVID-19, and awareness campaigns should be increased to boost vaccination programs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.